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
In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive fun...In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.展开更多
Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs ...Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.展开更多
In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering th...In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering the constraints of vehicle physical limits,in which a forward-backward integration scheme was introduced to generate a time-optimal speed profile subject to the tire-road friction limit.Moreover,this scheme was further extended along one moving prediction window.In the MPC controller,the prediction model was an 8-degree-of-freedom(DOF)vehicle model,while the plant was a 14-DOF vehicle model.For lateral control,a sequence of optimal wheel steering angles was generated from the MPC controller;for longitudinal control,the total wheel torque was generated from the PID speed controller embedded in the MPC framework.The proposed controller was implemented in MATLAB considering arbitrary curves of continuously varying curvature as the reference trajectory.The simulation test results show that the tracking errors are small for vehicle lateral and longitudinal positions and the tracking performances for trajectory and speed are good using the proposed controller.Additionally,the case of extended implementation in one moving prediction window requires shorter travel time than the case implemented along the entire path.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
The theoretical study of a semi-active predictive control(SAPC) system with magnetorheological(MR) dampers to reduce the responses of seismically excited structures was presented.The SAPC scheme is based on a predicti...The theoretical study of a semi-active predictive control(SAPC) system with magnetorheological(MR) dampers to reduce the responses of seismically excited structures was presented.The SAPC scheme is based on a prediction model of the system response to obtain the control actions by minimizing an object function,which has a function of self-compensation for time delay occurring in real application.A double-ended shear mode combined with a valve mode MR damper,named MRF-04K damper,with the maximum force of 20 kN was designed and manufactured,and parameters of the Bouc-Wen hysteresis model were determined to portray the behavior of this damper.As an example,a 5-story building frame equipped with 2 MRF-04K dampers was presented to demonstrate the performance of the proposed SAPC scheme for addressing time delay and reducing the structural responses under different earthquakes.Comparison with the uncontrolled structure,the passive-off and passive-on cases indicates that both the peak and the norm values of structural responses are all clearly reduced,and the SAPC scheme has a better performance than the two passive cases.展开更多
Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approa...Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approach, the maximum and minimum of partial derivative for input and output nonlinearities are solved in the neighbourhood of the equilibrium. And several parameter-dependent Lyapunov functions, each one corresponding to a different vertex of polytopic descriptions models, are introduced to analyze the stability of Hammerstein-Wiener systems, but only one Lyapunov function is utilized to analyze system stability like the traditional method. Consequently, the conservation of the traditional quadratic stability is removed, and the terminal regions are enlarged. Simulation and field trial results show that the proposed algorithm is valid. It has higher control precision and shorter blowing time than the traditional approach.展开更多
Nonlinear model predictive controllers(NMPC)can predict the future behavior of the under-controlled system using a nonlinear predictive model.Here,an array of hyper chaotic diagonal recurrent neural network(HCDRNN)was...Nonlinear model predictive controllers(NMPC)can predict the future behavior of the under-controlled system using a nonlinear predictive model.Here,an array of hyper chaotic diagonal recurrent neural network(HCDRNN)was proposed for modeling and predicting the behavior of the under-controller nonlinear system in a moving forward window.In order to improve the convergence of the parameters of the HCDRNN to improve system’s modeling,the extent of chaos is adjusted using a logistic map in the hidden layer.A novel NMPC based on the HCDRNN array(HCDRNN-NMPC)was proposed that the control signal with the help of an improved gradient descent method was obtained.The controller was used to control a continuous stirred tank reactor(CSTR)with hard-nonlinearities and input constraints,in the presence of uncertainties including external disturbance.The results of the simulations show the superior performance of the proposed method in trajectory tracking and disturbance rejection.Parameter convergence and neglectable prediction error of the neural network(NN),guaranteed stability and high tracking performance are the most significant advantages of the proposed scheme.展开更多
An improved model predictive control algorithm is proposed for Hammerstein-Wiener nonlinear systems.The proposed synthesis algorithm contains two parts:offline design the polytopic invariant sets,and online solve the ...An improved model predictive control algorithm is proposed for Hammerstein-Wiener nonlinear systems.The proposed synthesis algorithm contains two parts:offline design the polytopic invariant sets,and online solve the min-max optimization problem.The polytopic invariant set is adopted to replace the traditional ellipsoid invariant set.And the parameter-correlation nonlinear control law is designed to replace the traditional linear control law.Consequently,the terminal region is enlarged and the control effect is improved.Simulation and experiment are used to verify the validity of the wind tunnel flow field control algorithm.展开更多
In this work, the effect of various effective dimensionless numbers and moisture contents on initiation of instability in combustion of moisty organic dust is calculated. To have reliable model, effect of thermal radi...In this work, the effect of various effective dimensionless numbers and moisture contents on initiation of instability in combustion of moisty organic dust is calculated. To have reliable model, effect of thermal radiation is taken into account. One- dimensional flame structure is divided into three zones： preheat zone, reaction zone and post-flame zone. To investigate pulsating characteristics of flame, governing equations are rewritten in dimensionless space-time （（, r/, ~） coordinates. By solving these newly achieved governing equations and combining them, which is completely discussed in body of article, a new expression is obtained. By solving this equation, it is possible to predict initiation of instability in organic dust flame. According to the obtained results by increasing Lewis number, threshold of instability happens sooner. On the other hand, pulsating is postponed by increasing Damk6hler number, pyrolysis temperature or moisture content. Also, by considering thermal radiation effect, burning velocity predicted by our model is closer to experimental results.展开更多
To promote the modeling standardization process of the integrated circuits, an improved electrical simulation model for a direct power injection （DPI） setup which was used to measure the conducted immunity of a 16-b...To promote the modeling standardization process of the integrated circuits, an improved electrical simulation model for a direct power injection （DPI） setup which was used to measure the conducted immunity of a 16-bit microcontroller to radio frequency aggression was investigated. Based on the existing model of the same microcontroller, the PDN module was modified by adding the core, PLL and MD network models, which could reflect the actual electric distribution situation within the microcontroller more accurately. By comparing the simulation results with the measurement results, the effectiveness of the modified model can be improved to 500 MHz, and its uncertainty is within ＋1.8 dB （＋2 dB is acceptable）. Then, to improve the simulation accuracy of the complete model in the high frequency range, the I/O model which contained the dynamic and nonlinear characteristics reflecting the variation of the internal impedance of the microcontroller with increasing the frequency of the external noise was introduced. By comparing the simulation results with the measurement results, the effectiveness of the second modified model can be improved up to 1.4 GHz with the uncertainty of ~1.8 dB. Thus, a conclusion can be reached that the proposed model can be applied to a much wider frequency range with a smaller uncertainty than the latest model of the similar type. Furthermore, associated with the electromagnetic emission testing platform model, the PDN module can also be used to predict the electromagnetic conducted and radiated emission characteristics. This modeling method can also be applied to other integrated circuits, which is very helpful to the standardization of the IC electromagnetic compatibility （EMC） modeling process.展开更多
This work considers those road networks in which there are multi-route choices for bifurcation-destination(or origin-destination) pairs, and designs a real-time variable message sign(VMS)-based routing control strateg...This work considers those road networks in which there are multi-route choices for bifurcation-destination(or origin-destination) pairs, and designs a real-time variable message sign(VMS)-based routing control strategy in the model predictive control(MPC) framework. The VMS route recommendation provided by the traffic management authority is directly considered as the control variable, and the routing control model is established, in which a multi-dimensional control vector is introduced to describe the influence of route recommendations on flow distribution. In the MPC framework, a system optimum routing strategy with the constraints regarding drivers' acceptability with recommended routes is designed, which can not only meet the traffic management authority's control requirement but also improve drivers' satisfaction with the route guidance system. The simulation carried out shows that the proposed routing control can effectively mitigate traffic congestion, reduces followers' time delay, and improves drivers' satisfaction with routing control in road networks.展开更多
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(2007AA04Z162) supported by the National High-Tech Research and Development Program of ChinaProjects(2006T089, 2009T062) supported by the University Innovation Team in the Educational Department of Liaoning Province, China
文摘In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.
基金Project(2002CB312200) supported by the National Key Fundamental Research and Development Program of China project(60574019) supported by the National Natural Science Foundation of China
文摘Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.
基金Project(20180608005600843855-19)supported by the International Graduate Exchange Program of Beijing Institute of Technology,China。
文摘In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering the constraints of vehicle physical limits,in which a forward-backward integration scheme was introduced to generate a time-optimal speed profile subject to the tire-road friction limit.Moreover,this scheme was further extended along one moving prediction window.In the MPC controller,the prediction model was an 8-degree-of-freedom(DOF)vehicle model,while the plant was a 14-DOF vehicle model.For lateral control,a sequence of optimal wheel steering angles was generated from the MPC controller;for longitudinal control,the total wheel torque was generated from the PID speed controller embedded in the MPC framework.The proposed controller was implemented in MATLAB considering arbitrary curves of continuously varying curvature as the reference trajectory.The simulation test results show that the tracking errors are small for vehicle lateral and longitudinal positions and the tracking performances for trajectory and speed are good using the proposed controller.Additionally,the case of extended implementation in one moving prediction window requires shorter travel time than the case implemented along the entire path.
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Projects(90815025,51178034) supported by the National Natural Science Foundation of China
文摘The theoretical study of a semi-active predictive control(SAPC) system with magnetorheological(MR) dampers to reduce the responses of seismically excited structures was presented.The SAPC scheme is based on a prediction model of the system response to obtain the control actions by minimizing an object function,which has a function of self-compensation for time delay occurring in real application.A double-ended shear mode combined with a valve mode MR damper,named MRF-04K damper,with the maximum force of 20 kN was designed and manufactured,and parameters of the Bouc-Wen hysteresis model were determined to portray the behavior of this damper.As an example,a 5-story building frame equipped with 2 MRF-04K dampers was presented to demonstrate the performance of the proposed SAPC scheme for addressing time delay and reducing the structural responses under different earthquakes.Comparison with the uncontrolled structure,the passive-off and passive-on cases indicates that both the peak and the norm values of structural responses are all clearly reduced,and the SAPC scheme has a better performance than the two passive cases.
基金Project(61074074) supported by the National Natural Science Foundation,ChinaProject(KT2012C01J0401) supported by the Group Innovative Fund,China
文摘Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approach, the maximum and minimum of partial derivative for input and output nonlinearities are solved in the neighbourhood of the equilibrium. And several parameter-dependent Lyapunov functions, each one corresponding to a different vertex of polytopic descriptions models, are introduced to analyze the stability of Hammerstein-Wiener systems, but only one Lyapunov function is utilized to analyze system stability like the traditional method. Consequently, the conservation of the traditional quadratic stability is removed, and the terminal regions are enlarged. Simulation and field trial results show that the proposed algorithm is valid. It has higher control precision and shorter blowing time than the traditional approach.
文摘Nonlinear model predictive controllers(NMPC)can predict the future behavior of the under-controlled system using a nonlinear predictive model.Here,an array of hyper chaotic diagonal recurrent neural network(HCDRNN)was proposed for modeling and predicting the behavior of the under-controller nonlinear system in a moving forward window.In order to improve the convergence of the parameters of the HCDRNN to improve system’s modeling,the extent of chaos is adjusted using a logistic map in the hidden layer.A novel NMPC based on the HCDRNN array(HCDRNN-NMPC)was proposed that the control signal with the help of an improved gradient descent method was obtained.The controller was used to control a continuous stirred tank reactor(CSTR)with hard-nonlinearities and input constraints,in the presence of uncertainties including external disturbance.The results of the simulations show the superior performance of the proposed method in trajectory tracking and disturbance rejection.Parameter convergence and neglectable prediction error of the neural network(NN),guaranteed stability and high tracking performance are the most significant advantages of the proposed scheme.
基金Project(61074074)supported by the National Natural Science Foundation,ChinaProject(KT2012C01J0401)supported by the Group Innovation Fund,China
文摘An improved model predictive control algorithm is proposed for Hammerstein-Wiener nonlinear systems.The proposed synthesis algorithm contains two parts:offline design the polytopic invariant sets,and online solve the min-max optimization problem.The polytopic invariant set is adopted to replace the traditional ellipsoid invariant set.And the parameter-correlation nonlinear control law is designed to replace the traditional linear control law.Consequently,the terminal region is enlarged and the control effect is improved.Simulation and experiment are used to verify the validity of the wind tunnel flow field control algorithm.
文摘In this work, the effect of various effective dimensionless numbers and moisture contents on initiation of instability in combustion of moisty organic dust is calculated. To have reliable model, effect of thermal radiation is taken into account. One- dimensional flame structure is divided into three zones： preheat zone, reaction zone and post-flame zone. To investigate pulsating characteristics of flame, governing equations are rewritten in dimensionless space-time （（, r/, ~） coordinates. By solving these newly achieved governing equations and combining them, which is completely discussed in body of article, a new expression is obtained. By solving this equation, it is possible to predict initiation of instability in organic dust flame. According to the obtained results by increasing Lewis number, threshold of instability happens sooner. On the other hand, pulsating is postponed by increasing Damk6hler number, pyrolysis temperature or moisture content. Also, by considering thermal radiation effect, burning velocity predicted by our model is closer to experimental results.
基金Project(2007dfa71250) supported by the International Science and Technology Cooperative Program of ChinaProject(20062250) supported by the Doctor Fund of North China Electric Power University, China
文摘To promote the modeling standardization process of the integrated circuits, an improved electrical simulation model for a direct power injection （DPI） setup which was used to measure the conducted immunity of a 16-bit microcontroller to radio frequency aggression was investigated. Based on the existing model of the same microcontroller, the PDN module was modified by adding the core, PLL and MD network models, which could reflect the actual electric distribution situation within the microcontroller more accurately. By comparing the simulation results with the measurement results, the effectiveness of the modified model can be improved to 500 MHz, and its uncertainty is within ＋1.8 dB （＋2 dB is acceptable）. Then, to improve the simulation accuracy of the complete model in the high frequency range, the I/O model which contained the dynamic and nonlinear characteristics reflecting the variation of the internal impedance of the microcontroller with increasing the frequency of the external noise was introduced. By comparing the simulation results with the measurement results, the effectiveness of the second modified model can be improved up to 1.4 GHz with the uncertainty of ~1.8 dB. Thus, a conclusion can be reached that the proposed model can be applied to a much wider frequency range with a smaller uncertainty than the latest model of the similar type. Furthermore, associated with the electromagnetic emission testing platform model, the PDN module can also be used to predict the electromagnetic conducted and radiated emission characteristics. This modeling method can also be applied to other integrated circuits, which is very helpful to the standardization of the IC electromagnetic compatibility （EMC） modeling process.
基金Projects(61304203,51409157)supported by the National Natural Science Foundation of ChinaProject(12ZR1444800)supported by the Natural Science Foundation of Shanghai,China
文摘This work considers those road networks in which there are multi-route choices for bifurcation-destination(or origin-destination) pairs, and designs a real-time variable message sign(VMS)-based routing control strategy in the model predictive control(MPC) framework. The VMS route recommendation provided by the traffic management authority is directly considered as the control variable, and the routing control model is established, in which a multi-dimensional control vector is introduced to describe the influence of route recommendations on flow distribution. In the MPC framework, a system optimum routing strategy with the constraints regarding drivers' acceptability with recommended routes is designed, which can not only meet the traffic management authority's control requirement but also improve drivers' satisfaction with the route guidance system. The simulation carried out shows that the proposed routing control can effectively mitigate traffic congestion, reduces followers' time delay, and improves drivers' satisfaction with routing control in road networks.
