To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method...To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method proposed provides a novel way to predict the impact point of projectile for moving tank.First,bidirectional stability constraints and stability constraint-following error are constructed using the Udwadia-Kalaba theory,and an adaptive robust constraint-following controller is designed considering uncertainties.Second,the exterior ballistic ordinary differential equation with uncertainties is integrated into the controller,and the pointing control of stability system is extended to the impact-point control of projectile.Third,based on the interval uncertainty analysis method combining Chebyshev polynomial expansion and affine arithmetic,a prediction method of projectile-target intersection is proposed.Finally,the co-simulation experiment is performed by establishing the multi-body system dynamic model of tank and mathematical model of control system.The results demonstrate that the prediction method of projectile-target intersection based on uncertainty analysis can effectively decrease the uncertainties of system,improve the prediction accuracy,and increase the hit probability.The adaptive robust constraint-following control can effectively restrain the uncertainties caused by road excitation and model error.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
The acquisition,tracking,and pointing(ATP)system is widely used in target tracking,counter-UAV operations,and other related fields.As UAV technology develops,there is a growing demand to enhance the tracking capabilit...The acquisition,tracking,and pointing(ATP)system is widely used in target tracking,counter-UAV operations,and other related fields.As UAV technology develops,there is a growing demand to enhance the tracking capabilities of ATP systems.However,in practical applications,ATP systems face various design constraints and functional limitations,making it infeasible to indefinitely improve hardware performance to meet tracking requirements.As a result,tracking algorithms are required to execute increasingly complex tasks.This study introduces a multi-rate feedforward predictive controller to address issues such as low image feedback frequency and significant delays in ATP systems,which lead to tracking jitter,poor tracking performance,low precision,and target loss.At the same time,the pro-posed approach aims to improve the tracking capabilities of ATP systems for high-speed and highly maneuverable targets under conditions of low sampling feedback rates and high feedback delays.The method suggested is also characterized by its low order,fast response,and robustness to model parameter variations.In this study,an actual ATP system is built for target tracking test,and the proposed algorithm is fully validated in terms of simulation and actual system application verification.Results from both simulations and experiments demonstrate that the method effectively compensates for delays and low sampling rates.For targets with relative angular velocities ranging from 0 to 90°/s and angular accelerations between 0 and 470°/s^(2),the system improved tracking accuracy by 70.0%-89.9%at a sampling frequency of 50 Hz and a delay of 30 m s.Moreover,the compensation algorithm demonstrated consistent performance across actuators with varying characteristics,further confirming its robustness to model insensitivity.In summary,the proposed algorithm considerably enhances the tracking accuracy and capability of ATP systems for high-speed and highly maneuverable targets,reducing the probability of target loss from high speed.This approach offers a practical solution for future multi-target tracking across diverse operational scenarios.展开更多
In the forward channel of a networked control system （NCS）, by defining the network states as a hidden Markov chain and quantizing the network-induced delays to a discrete sequence distributing over a finite time in...In the forward channel of a networked control system （NCS）, by defining the network states as a hidden Markov chain and quantizing the network-induced delays to a discrete sequence distributing over a finite time interval, the relation between the network states and the network-induced delays is modelled as a discrete-time hidden Markov model （DTHMM）. The expectation maximization （EM） algorithm is introduced to derive the maximumlikelihood estimation （MLE） of the parameters of the DTHMM. Based on the derived DTHMM, the Viterbi algorithm is introduced to predict the controller-to-actuator （C-A） delay during the current sampling period. The simulation experiments demonstrate the effectiveness of the modelling and predicting methods proposed.展开更多
This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,...This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.展开更多
Abstract： Two-tier heterogeneous networks （HetNets）, where the current cellular networks, i.e., macrocells, are overlapped with a large number of randomly distributed femtocells, can potentially bring significant b...Abstract： Two-tier heterogeneous networks （HetNets）, where the current cellular networks, i.e., macrocells, are overlapped with a large number of randomly distributed femtocells, can potentially bring significant benefits to spectral utilization and system capacity. The interference management and access control for open and closed femtocells in two-tier HetNets were focused. The contributions consist of two parts. Firstly, in order to reduce the uplink interference caused by MUEs （macrocell user equipments） at closed femtocells, an incentive mechanism to implement interference mitigation was proposed. It encourages femtoeells that work with closed-subscriber-group （CSG） to allow the interfering MUEs access in but only via uplink, which can reduce the interference significantly and also benefit the marco-tier. The interference issue was then studied in open-subscriber-group （OSG） femtocells from the perspective of handover and mobility prediction. Inbound handover provides an alternative solution for open femtocells when interference turns up, while this accompanies with PCI （physical cell identity） confusion during inbound handover. To reduce the PCI confusion, a dynamic PCI allocation scheme was proposed, by which the high handin femtocells have the dedicated PCI while the others share the reuse PCIs. A Markov chain based mobility prediction algorithm was designed to decide whether the femtoeell status is with high handover requests. Numerical analysis reveals that the UL interference is managed well for the CSG femtocell and the PCI confusion issue is mitigated greatly in OSG femtocell compared to the conventional approaches.展开更多
With the advantage of exceptional long-range traffic perception capabilities and data fusion computational prowess,the cloud control system(CCS)has exhibited formidable poten-tial in the realm of connected assisted dr...With the advantage of exceptional long-range traffic perception capabilities and data fusion computational prowess,the cloud control system(CCS)has exhibited formidable poten-tial in the realm of connected assisted driving,such as the adap-tive cruise control(ACC).Based on the CCS architecture,this paper proposes a cloud-based predictive ACC(PACC)strategy,which fully considers the road slope information and the preced-ing vehicle status.In the cloud,based on the dynamic program-ming(DP),the long-term economic speed planning is carried out by using the slope information.At the vehicle side,the real-time fusion planning of the economic speed and the preceding vehi-cle state is realized based on the model predictive control(MPC),taking into account the safety and economy of driving.In order to ensure the safety and stability of the vehicle-cloud cooperative control system,an event-triggered cruise mode switching method is proposed based on the state of each sub-system of the vehicle-cloud-network-map.Simulation results indicate that the PACC system can still ensure stable cruising under delays and some complex conditions.Moreover,under normal conditions,compared to the ACC system,the PACC sys-tem can further improve economy while ensuring safety and improve the overall energy efficiency of the vehicle,thus achiev-ing fuel savings of 3%to 8%.展开更多
The robust stabilization problem for a class of uncertain discrete-time switched systems is presented. A predictive sliding mode control strategy is proposed, and a discrete-time reaching law is improved. By applying ...The robust stabilization problem for a class of uncertain discrete-time switched systems is presented. A predictive sliding mode control strategy is proposed, and a discrete-time reaching law is improved. By applying a predictive sliding surface and a reference trajectory, combining with the state feedback correction and rolling optimization method in the predictive control strategy, a predictive sliding mode controller is synthesized, which guarantees the asymptotic stability for the closed-loop systems. The designed control strategy has stronger robustness and chattering reduction property to conquer with the system uncertainties. In addition, a unique nonswitched sliding surface is designed. The reason is to avoid the repetitive jump of the trajectories of the state components of the closed-loop system between sliding surfaces because it might cause the possible instability. Finally, a numerical example is given to illustrate the effectiveness of the proposed theory.展开更多
This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatl...This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result.展开更多
In view of DC speed control system, this paper presents a predictive control algorithm to replace traditional PID control. System predictive model requires little information of the controlled object, and because it...In view of DC speed control system, this paper presents a predictive control algorithm to replace traditional PID control. System predictive model requires little information of the controlled object, and because it adopts rolling optimum method, system展开更多
A robust model predictive control algorithm for discrete linear systems with both state and input delays subjected to constrained input control is presented, where the polytopic uncertainties exist in both state matri...A robust model predictive control algorithm for discrete linear systems with both state and input delays subjected to constrained input control is presented, where the polytopic uncertainties exist in both state matrices and input matrices. The algorithm optimizes an upper bound with respect to a state feedback control law. The feedback control law is presented based on the construction of a parameter-dependent Lyapunov function. The above optimization problem can be formulated as a LMI-based optimization. The feasibility of the optimization problem guarantees that the algorithm is robustly stable. The simulation results verify the effectiveness of the proposed algorithm.展开更多
A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and th...A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.展开更多
Compared with the one-dimensional trajectory correction technology which adjusts longitudinal range, not only does the two-dimensional trajectory correction technology adjust the force in velocity direction, but also ...Compared with the one-dimensional trajectory correction technology which adjusts longitudinal range, not only does the two-dimensional trajectory correction technology adjust the force in velocity direction, but also need to modulate the lateral force or trajectory (perpendicular to the vertical plane of fire direction). Therefore, the structure of control cabin of two-dimensional trajectory correction projectile (TDTCP) is more complicated than that of one-dimensional trajectory correction projectile (ODTCP). To simplify the structure of control cabin of TDTCP and reduce the cost, a scheme of adding a damping disk to the control cabin of ODTCP has been developed recently. The damping disk is unfolded at the right moment during its flight to change the ballistic drift of spin stabilized projectile. For this technical scheme of TDTCP, a fast and accurate impact point prediction method based on extended Kalman filter is presented. An approximate formula for predicting the ballistic drift and trajectory correction quantity is deduced. And the lateral correction capability for different fire angles and its influencing factors are analyzed. All the work is valuable for further research.展开更多
Based on a Hill equation and a nonlinear equation describing the desired and real dynamics of relative motion separately, a predictive controller is brought forward, which makes the real state track the desired ones t...Based on a Hill equation and a nonlinear equation describing the desired and real dynamics of relative motion separately, a predictive controller is brought forward, which makes the real state track the desired ones to keep satellite formation. The stability and robustness of the controller are analyzed. Finally, comparing the simulation results of the proposed controller with that of the traditional, proportional-differential controller shows that the former one is capable of keeping the satellite formation more favorably, considering the disturbances such as the J2 perturbations.展开更多
The problem of observer-based robust predictive control is studied for the singular systems with norm-bounded uncertainties and time-delay, and the design method of robust predictive observer-based controller is propo...The problem of observer-based robust predictive control is studied for the singular systems with norm-bounded uncertainties and time-delay, and the design method of robust predictive observer-based controller is proposed. By constructing the Lyapunov function with the error terms, the infinite time domain ＂min-max＂ optimization problems are converted into convex optimization problems solving by the linear matrix inequality （LMI）, and the sufficient conditions for the existence of this control are derived. It is proved that the robust stability of the closed-loop singular systems can be guaranteed by the initial feasible solutions of the optimization problems, and the regular and the impulse-free of the singular systems are also guaranteed. A simulation example illustrates the efficiency of this method.展开更多
Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional(2D) general predictive iterativ...Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional(2D) general predictive iterative learning control(2D-MGPILC) strategy based on the multi-model with time-varying weights was introduced for optimizing the tracking performance of desired temperature profile. This strategy was modeled based on an iterative learning control(ILC) algorithm for a 2D system and designed in the generalized predictive control(GPC) framework. Firstly, a multi-model structure with time-varying weights was developed to describe the complex operation of a general semi-batch reactor. Secondly, the 2 D-MGPILC algorithm was proposed to optimize simultaneously the dynamic performance along the time and batch axes. Finally, simulation for the controller design of a semi-batch reactor with multiple reactions was involved to demonstrate that the satisfactory performance could be achieved despite of the repetitive or non-repetitive disturbances.展开更多
For a class of linear discrete-time systems that is subject to randomly occurred networked packet loss in industrial cyber physical systems, a novel robust model predictive control method with active compensation mech...For a class of linear discrete-time systems that is subject to randomly occurred networked packet loss in industrial cyber physical systems, a novel robust model predictive control method with active compensation mechanism was proposed. The probability distribution of packet loss is described as the Bernoulli distributed white sequences. By using the Lyapunov stability theory, the existing sufficient conditions of the controller are derived from solving a group of linear matrix inequalities. Moreover, dropout-rate with uncertainty and unknown dropout-rate are also considered, which can greatly reduce the conservativeness of the controller. The designed robust model predictive control method not only efficiently eliminates the negative effects of the networked data loss in industrial cyber physical systems but also ensures the stability of closed-loop system. Two examples were provided to illustrate the superiority and effectiveness of the proposed method.展开更多
Controlling the looper height and strip tension is important in hot strip mills because these variables affect both the strip quality and strip threading. Many researchers have proposed and applied a variety of contro...Controlling the looper height and strip tension is important in hot strip mills because these variables affect both the strip quality and strip threading. Many researchers have proposed and applied a variety of control schemes for this problem, but the increasingly strict market demand for strip quality requires further improvements. This work describes a dynamic matrix predictive control(DMC) strategy that realizes the optimal control of a hydraulic looper multivariable system. Simulation experiments for a traditional controller and the proposed DMC controller were conducted using MATLAB/Simulink software. The simulation results show that both controllers acquire good control effects with model matching. However, when the model is mismatched, the traditional controller produces an overshoot of 32.4% and a rising time of up to 2120.2 ms, which is unacceptable in a hydraulic looper system. The DMC controller restricts the overshoot to less than 0.08%, and the rising time is less than 48.6 ms in all cases.展开更多
The mechanical system with backlash is distinguished between a＂backlash mode＂and a＂contact mode＂.The inherent switching between the two operating modes makes the system a prime example of hybrid system.For elimina...The mechanical system with backlash is distinguished between a＂backlash mode＂and a＂contact mode＂.The inherent switching between the two operating modes makes the system a prime example of hybrid system.For eliminating the bad effect of backlash, a piecewise affine（PWA） model of the mechanical servo system with backlash is built.The optimal control of constrained PWA system is obtained by taking advantage of model predictive control（MPC） method, and the explicit solution of MPC in a look-up table form is figured out by combining the dynamic programming and multi-parametric quadratic programming, thereby establishing an explicit hybrid model predictive controller.Furthermore, a piecewise quadratic（PWQ） function for guaranteeing the stability of closed-loop control is found by formulating the search of PWQ function as a semi-definite programming problem.In the tracking experiments, it is demonstrated that the explicit hybrid model predictive controller has a good traction control effect on the mechanical system with backlash.The error meets the demands of real system.Further, compared to the direct on-line computation, the computation burden is reduced by the explicit solution, thereby being suitable for real-time control of system with short sampling time.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant 52175099)the China Postdoctoral Science Foundation(Grant No.2020M671494)+1 种基金the Jiangsu Planned Projects for Postdoctoral Research Funds(Grant No.2020Z179)the Nanjing University of Science and Technology Independent Research Program(Grant No.30920021105)。
文摘To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method proposed provides a novel way to predict the impact point of projectile for moving tank.First,bidirectional stability constraints and stability constraint-following error are constructed using the Udwadia-Kalaba theory,and an adaptive robust constraint-following controller is designed considering uncertainties.Second,the exterior ballistic ordinary differential equation with uncertainties is integrated into the controller,and the pointing control of stability system is extended to the impact-point control of projectile.Third,based on the interval uncertainty analysis method combining Chebyshev polynomial expansion and affine arithmetic,a prediction method of projectile-target intersection is proposed.Finally,the co-simulation experiment is performed by establishing the multi-body system dynamic model of tank and mathematical model of control system.The results demonstrate that the prediction method of projectile-target intersection based on uncertainty analysis can effectively decrease the uncertainties of system,improve the prediction accuracy,and increase the hit probability.The adaptive robust constraint-following control can effectively restrain the uncertainties caused by road excitation and model error.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
基金supported by the National Natural Science Foun-dation of China(Grant No.52275099).
文摘The acquisition,tracking,and pointing(ATP)system is widely used in target tracking,counter-UAV operations,and other related fields.As UAV technology develops,there is a growing demand to enhance the tracking capabilities of ATP systems.However,in practical applications,ATP systems face various design constraints and functional limitations,making it infeasible to indefinitely improve hardware performance to meet tracking requirements.As a result,tracking algorithms are required to execute increasingly complex tasks.This study introduces a multi-rate feedforward predictive controller to address issues such as low image feedback frequency and significant delays in ATP systems,which lead to tracking jitter,poor tracking performance,low precision,and target loss.At the same time,the pro-posed approach aims to improve the tracking capabilities of ATP systems for high-speed and highly maneuverable targets under conditions of low sampling feedback rates and high feedback delays.The method suggested is also characterized by its low order,fast response,and robustness to model parameter variations.In this study,an actual ATP system is built for target tracking test,and the proposed algorithm is fully validated in terms of simulation and actual system application verification.Results from both simulations and experiments demonstrate that the method effectively compensates for delays and low sampling rates.For targets with relative angular velocities ranging from 0 to 90°/s and angular accelerations between 0 and 470°/s^(2),the system improved tracking accuracy by 70.0%-89.9%at a sampling frequency of 50 Hz and a delay of 30 m s.Moreover,the compensation algorithm demonstrated consistent performance across actuators with varying characteristics,further confirming its robustness to model insensitivity.In summary,the proposed algorithm considerably enhances the tracking accuracy and capability of ATP systems for high-speed and highly maneuverable targets,reducing the probability of target loss from high speed.This approach offers a practical solution for future multi-target tracking across diverse operational scenarios.
基金supported in part by the National Natural Science Foundation of China (60774098 60843003+3 种基金 50905172)the Science Foundation of Anhui Province (090412071 090412040)the University of Science and Technology of China Initiative Foundation
文摘In the forward channel of a networked control system （NCS）, by defining the network states as a hidden Markov chain and quantizing the network-induced delays to a discrete sequence distributing over a finite time interval, the relation between the network states and the network-induced delays is modelled as a discrete-time hidden Markov model （DTHMM）. The expectation maximization （EM） algorithm is introduced to derive the maximumlikelihood estimation （MLE） of the parameters of the DTHMM. Based on the derived DTHMM, the Viterbi algorithm is introduced to predict the controller-to-actuator （C-A） delay during the current sampling period. The simulation experiments demonstrate the effectiveness of the modelling and predicting methods proposed.
基金“National Science and Technology Council”(NSTC 111-2221-E-027-088)。
文摘This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.
基金Project(2012AA01A301-01)supported by the National High-Tech Research and Development Plan of ChinaProjects(61301148,61272061)supported by the National Natural Science Foundation of China+3 种基金Projects(20120161120019,2013016111002)supported by the Research Fund for the Doctoral Program of Higher Education of ChinaProjects(14JJ7023,10JJ5069)supported by the Natural Science Foundation of Hunan Province,ChinaProject(ISN12-05)supported by State Key Laboratory of Integrated Services Networks Open Foundation,ChinaProject(531107040276)supported by the Fundamental Research Funds for the Central Universities,China
文摘Abstract： Two-tier heterogeneous networks （HetNets）, where the current cellular networks, i.e., macrocells, are overlapped with a large number of randomly distributed femtocells, can potentially bring significant benefits to spectral utilization and system capacity. The interference management and access control for open and closed femtocells in two-tier HetNets were focused. The contributions consist of two parts. Firstly, in order to reduce the uplink interference caused by MUEs （macrocell user equipments） at closed femtocells, an incentive mechanism to implement interference mitigation was proposed. It encourages femtoeells that work with closed-subscriber-group （CSG） to allow the interfering MUEs access in but only via uplink, which can reduce the interference significantly and also benefit the marco-tier. The interference issue was then studied in open-subscriber-group （OSG） femtocells from the perspective of handover and mobility prediction. Inbound handover provides an alternative solution for open femtocells when interference turns up, while this accompanies with PCI （physical cell identity） confusion during inbound handover. To reduce the PCI confusion, a dynamic PCI allocation scheme was proposed, by which the high handin femtocells have the dedicated PCI while the others share the reuse PCIs. A Markov chain based mobility prediction algorithm was designed to decide whether the femtoeell status is with high handover requests. Numerical analysis reveals that the UL interference is managed well for the CSG femtocell and the PCI confusion issue is mitigated greatly in OSG femtocell compared to the conventional approaches.
基金supported by the National Key R&D Program of China(2021YFB2501000)the Consultancy Research Project on the Strategic Study of the Integration and Innovative Development of Intelligent Connected Vehicles and New Energy Ecology in Zhejiang Province(2023ZL0007)+1 种基金the Hetao Shenzhen-HongKong Science and Technology Innovation Cooperation Zone(HZQB-KCZYZ-2021055)the Open Project of the Key Laboratory of Modern Measurement and Control Technology of the Ministry of Education(KF2022-1123202).
文摘With the advantage of exceptional long-range traffic perception capabilities and data fusion computational prowess,the cloud control system(CCS)has exhibited formidable poten-tial in the realm of connected assisted driving,such as the adap-tive cruise control(ACC).Based on the CCS architecture,this paper proposes a cloud-based predictive ACC(PACC)strategy,which fully considers the road slope information and the preced-ing vehicle status.In the cloud,based on the dynamic program-ming(DP),the long-term economic speed planning is carried out by using the slope information.At the vehicle side,the real-time fusion planning of the economic speed and the preceding vehi-cle state is realized based on the model predictive control(MPC),taking into account the safety and economy of driving.In order to ensure the safety and stability of the vehicle-cloud cooperative control system,an event-triggered cruise mode switching method is proposed based on the state of each sub-system of the vehicle-cloud-network-map.Simulation results indicate that the PACC system can still ensure stable cruising under delays and some complex conditions.Moreover,under normal conditions,compared to the ACC system,the PACC sys-tem can further improve economy while ensuring safety and improve the overall energy efficiency of the vehicle,thus achiev-ing fuel savings of 3%to 8%.
基金supported by the Youth Science and Innovation Foundation of Harbin(2007RFQXG052).
文摘The robust stabilization problem for a class of uncertain discrete-time switched systems is presented. A predictive sliding mode control strategy is proposed, and a discrete-time reaching law is improved. By applying a predictive sliding surface and a reference trajectory, combining with the state feedback correction and rolling optimization method in the predictive control strategy, a predictive sliding mode controller is synthesized, which guarantees the asymptotic stability for the closed-loop systems. The designed control strategy has stronger robustness and chattering reduction property to conquer with the system uncertainties. In addition, a unique nonswitched sliding surface is designed. The reason is to avoid the repetitive jump of the trajectories of the state components of the closed-loop system between sliding surfaces because it might cause the possible instability. Finally, a numerical example is given to illustrate the effectiveness of the proposed theory.
文摘This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result.
文摘In view of DC speed control system, this paper presents a predictive control algorithm to replace traditional PID control. System predictive model requires little information of the controlled object, and because it adopts rolling optimum method, system
文摘A robust model predictive control algorithm for discrete linear systems with both state and input delays subjected to constrained input control is presented, where the polytopic uncertainties exist in both state matrices and input matrices. The algorithm optimizes an upper bound with respect to a state feedback control law. The feedback control law is presented based on the construction of a parameter-dependent Lyapunov function. The above optimization problem can be formulated as a LMI-based optimization. The feasibility of the optimization problem guarantees that the algorithm is robustly stable. The simulation results verify the effectiveness of the proposed algorithm.
基金This Project was supported by the National Natural Science Foundation of China (60374037 and 60574036)the Opening Project Foundation of National Lab of Industrial Control Technology (0708008).
文摘A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.
文摘Compared with the one-dimensional trajectory correction technology which adjusts longitudinal range, not only does the two-dimensional trajectory correction technology adjust the force in velocity direction, but also need to modulate the lateral force or trajectory (perpendicular to the vertical plane of fire direction). Therefore, the structure of control cabin of two-dimensional trajectory correction projectile (TDTCP) is more complicated than that of one-dimensional trajectory correction projectile (ODTCP). To simplify the structure of control cabin of TDTCP and reduce the cost, a scheme of adding a damping disk to the control cabin of ODTCP has been developed recently. The damping disk is unfolded at the right moment during its flight to change the ballistic drift of spin stabilized projectile. For this technical scheme of TDTCP, a fast and accurate impact point prediction method based on extended Kalman filter is presented. An approximate formula for predicting the ballistic drift and trajectory correction quantity is deduced. And the lateral correction capability for different fire angles and its influencing factors are analyzed. All the work is valuable for further research.
文摘Based on a Hill equation and a nonlinear equation describing the desired and real dynamics of relative motion separately, a predictive controller is brought forward, which makes the real state track the desired ones to keep satellite formation. The stability and robustness of the controller are analyzed. Finally, comparing the simulation results of the proposed controller with that of the traditional, proportional-differential controller shows that the former one is capable of keeping the satellite formation more favorably, considering the disturbances such as the J2 perturbations.
基金supported by the National Natural Science Foundation of China(60774016).
文摘The problem of observer-based robust predictive control is studied for the singular systems with norm-bounded uncertainties and time-delay, and the design method of robust predictive observer-based controller is proposed. By constructing the Lyapunov function with the error terms, the infinite time domain ＂min-max＂ optimization problems are converted into convex optimization problems solving by the linear matrix inequality （LMI）, and the sufficient conditions for the existence of this control are derived. It is proved that the robust stability of the closed-loop singular systems can be guaranteed by the initial feasible solutions of the optimization problems, and the regular and the impulse-free of the singular systems are also guaranteed. A simulation example illustrates the efficiency of this method.
基金Projects(61673205,21727818,61503180)supported by the National Natural Science Foundation of ChinaProject(2017YFB0307304)supported by National Key R&D Program of ChinaProject(BK20141461)supported by the Natural Science Foundation of Jiangsu Province,China
文摘Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional(2D) general predictive iterative learning control(2D-MGPILC) strategy based on the multi-model with time-varying weights was introduced for optimizing the tracking performance of desired temperature profile. This strategy was modeled based on an iterative learning control(ILC) algorithm for a 2D system and designed in the generalized predictive control(GPC) framework. Firstly, a multi-model structure with time-varying weights was developed to describe the complex operation of a general semi-batch reactor. Secondly, the 2 D-MGPILC algorithm was proposed to optimize simultaneously the dynamic performance along the time and batch axes. Finally, simulation for the controller design of a semi-batch reactor with multiple reactions was involved to demonstrate that the satisfactory performance could be achieved despite of the repetitive or non-repetitive disturbances.
基金Project(61673199)supported by the National Natural Science Foundation of ChinaProject(ICT1800400)supported by the Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China
文摘For a class of linear discrete-time systems that is subject to randomly occurred networked packet loss in industrial cyber physical systems, a novel robust model predictive control method with active compensation mechanism was proposed. The probability distribution of packet loss is described as the Bernoulli distributed white sequences. By using the Lyapunov stability theory, the existing sufficient conditions of the controller are derived from solving a group of linear matrix inequalities. Moreover, dropout-rate with uncertainty and unknown dropout-rate are also considered, which can greatly reduce the conservativeness of the controller. The designed robust model predictive control method not only efficiently eliminates the negative effects of the networked data loss in industrial cyber physical systems but also ensures the stability of closed-loop system. Two examples were provided to illustrate the superiority and effectiveness of the proposed method.
基金Project(N160704004)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(20131033)supported by the Ph D Start-up Fund of Natural Science Foundation of Liaoning Province,China
文摘Controlling the looper height and strip tension is important in hot strip mills because these variables affect both the strip quality and strip threading. Many researchers have proposed and applied a variety of control schemes for this problem, but the increasingly strict market demand for strip quality requires further improvements. This work describes a dynamic matrix predictive control(DMC) strategy that realizes the optimal control of a hydraulic looper multivariable system. Simulation experiments for a traditional controller and the proposed DMC controller were conducted using MATLAB/Simulink software. The simulation results show that both controllers acquire good control effects with model matching. However, when the model is mismatched, the traditional controller produces an overshoot of 32.4% and a rising time of up to 2120.2 ms, which is unacceptable in a hydraulic looper system. The DMC controller restricts the overshoot to less than 0.08%, and the rising time is less than 48.6 ms in all cases.
基金supported by the Beijing Education Committee Cooperation Building Foundation Project (XK100070532)
文摘The mechanical system with backlash is distinguished between a＂backlash mode＂and a＂contact mode＂.The inherent switching between the two operating modes makes the system a prime example of hybrid system.For eliminating the bad effect of backlash, a piecewise affine（PWA） model of the mechanical servo system with backlash is built.The optimal control of constrained PWA system is obtained by taking advantage of model predictive control（MPC） method, and the explicit solution of MPC in a look-up table form is figured out by combining the dynamic programming and multi-parametric quadratic programming, thereby establishing an explicit hybrid model predictive controller.Furthermore, a piecewise quadratic（PWQ） function for guaranteeing the stability of closed-loop control is found by formulating the search of PWQ function as a semi-definite programming problem.In the tracking experiments, it is demonstrated that the explicit hybrid model predictive controller has a good traction control effect on the mechanical system with backlash.The error meets the demands of real system.Further, compared to the direct on-line computation, the computation burden is reduced by the explicit solution, thereby being suitable for real-time control of system with short sampling time.
