In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis...In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.展开更多
This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method ...This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm(MGPC) is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.展开更多
The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function mod...The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function model parameters and time delay are alternately fixed to estimate each other.The instrumental variable technique is applied to guarantee consistent estimation against measurement noise.A noteworthy merit of the proposed method is that it can handle fractional time delay estimation,compared to existing methods commonly assuming that the time delay is an integer multiple of the sampling interval.The identifiability analysis for time delay is addressed and correspondingly,some guidelines are provided for practical implementation of the proposed method.Numerical and experimental examples are presented to illustrate the effectiveness of the proposed method.展开更多
A great number of pipelines in China are in unsatisfactory condition and faced with problems of corrosion and cracking,but there are very few approaches for underwater pipeline detection.Pipeline detection autonomous ...A great number of pipelines in China are in unsatisfactory condition and faced with problems of corrosion and cracking,but there are very few approaches for underwater pipeline detection.Pipeline detection autonomous underwater vehicle(PDAUV) is hereby designed to solve these problems when working with advanced optical,acoustical and electrical sensors for underwater pipeline detection.PDAUV is a test bed that not only examines the logical rationality of the program,effectiveness of the hardware architecture,accuracy of the software interface protocol as well as the reliability and stability of the control system but also verifies the effectiveness of the control system in tank experiments and sea trials.The motion control system of PDAUV,including both the hardware and software architectures,is introduced in this work.The software module and information flow of the motion control system of PDAUV and a novel neural network-based control(NNC) are also covered.Besides,a real-time identification method based on neural network is used to realize system identification.The tank experiments and sea trials are carried out to verify the feasibility and capability of PDAUV control system to complete underwater pipeline detection task.展开更多
The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by...The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.展开更多
Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotiv...Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.展开更多
In order to improve the control performance of strip rolling mill, theoretical model of the hydraulic gap control(HGC) system was established. HGC system offline identification scheme was designed for a tandem cold st...In order to improve the control performance of strip rolling mill, theoretical model of the hydraulic gap control(HGC) system was established. HGC system offline identification scheme was designed for a tandem cold strip mill, the system model parameters were identified by ARX model, and the identified model was verified. Taking the offline identified parameters as the initial values, online identification using recursive least square was carried out with model parameters changing. For the purpose of improving system robustness and decreasing the sensitivity due to model errors, the HGC system based on generalized predictive control(GPC) was designed, and simulation experiments for traditional controller and GPC controller were conducted. The results show that both controllers acquire good control effect with model matching. When the model mismatches, for the traditional controller, the overshot will increase to 76.7% and the rising time will increase to 165.7 ms, which cannot be accepted by HGC system; for the GPC controller, the overshot is less than 8.5%, and the rising time is less than 26 ms in any case.展开更多
We are engaged in solving two difficult problems in adaptive control of the large-scale time-variant aerospace system. One is parameter identification of time-variant continuous-time state-space modei; the other is ho...We are engaged in solving two difficult problems in adaptive control of the large-scale time-variant aerospace system. One is parameter identification of time-variant continuous-time state-space modei; the other is how to solve algebraic Riccati equation (ARE) of large order efficiently. In our approach, two neural networks are employed to independently solve both the system identification problem and the ARE associated with the optimal control problem. Thus the identification and the control computation are combined in closed-loop, adaptive, real-time control system . The advantage of this approach is that the neural networks converge to their solutions very quickly and simultaneously.展开更多
A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established...A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established by black-box identification. And a quadratic objective function with receding horizon was selected to obtain the controller output. By solving a nonlinear optimization problem with equality constraint of model output and boundary constraint of controller output using Nelder-Mead simplex direct search method, a sub-optimal control law was achieved in feature space. The effect of the controller was demonstrated on a recognized benchmark problem and a continuous-stirred tank reactor. The simulation results show that the multi-step-ahead predictive controller can be well applied to nonlinear system, with better performance in following reference trajectory and disturbance-rejection.展开更多
The problem of variable sampling time interval which appears in application of Kalman Filtering is analyzed and the corresponding filtering process with or without present transition matrix is suggested, then an appli...The problem of variable sampling time interval which appears in application of Kalman Filtering is analyzed and the corresponding filtering process with or without present transition matrix is suggested, then an application experiment for astronomical surveying is introduced. In this process, the known stochastically variable sampling time intervals play the roles as deterministic input sequences of the state-space description, and the corresponding matrix and (if needed) state transition matrix can be established by performing real-time and structure-linear system identification.展开更多
文摘In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.
基金Projects(61573052,61273132)supported by the National Natural Science Foundation of China
文摘This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm(MGPC) is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.
文摘The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function model parameters and time delay are alternately fixed to estimate each other.The instrumental variable technique is applied to guarantee consistent estimation against measurement noise.A noteworthy merit of the proposed method is that it can handle fractional time delay estimation,compared to existing methods commonly assuming that the time delay is an integer multiple of the sampling interval.The identifiability analysis for time delay is addressed and correspondingly,some guidelines are provided for practical implementation of the proposed method.Numerical and experimental examples are presented to illustrate the effectiveness of the proposed method.
基金Project(2011AA09A106)supported by the Hi-tech Research and Development Program of ChinaProject(51179035)supported by the National Natural Science Foundation of ChinaProject(2015ZX01041101)supported by Major National Science and Technology of China
文摘A great number of pipelines in China are in unsatisfactory condition and faced with problems of corrosion and cracking,but there are very few approaches for underwater pipeline detection.Pipeline detection autonomous underwater vehicle(PDAUV) is hereby designed to solve these problems when working with advanced optical,acoustical and electrical sensors for underwater pipeline detection.PDAUV is a test bed that not only examines the logical rationality of the program,effectiveness of the hardware architecture,accuracy of the software interface protocol as well as the reliability and stability of the control system but also verifies the effectiveness of the control system in tank experiments and sea trials.The motion control system of PDAUV,including both the hardware and software architectures,is introduced in this work.The software module and information flow of the motion control system of PDAUV and a novel neural network-based control(NNC) are also covered.Besides,a real-time identification method based on neural network is used to realize system identification.The tank experiments and sea trials are carried out to verify the feasibility and capability of PDAUV control system to complete underwater pipeline detection task.
基金supported by the National Natural Science Foundation of China(61863034)
文摘The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.
基金Project supported by the Centre for Smart Grid and Information Convergence(CeSGIC)at Xi’an Jiaotong-Liverpool University,China
文摘Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.
基金Project(51074051)supported by the National Natural Science Foundation of ChinaProject(20131033)supported by the Ph D Start-up Fund of Natural Science Foundation of Liaoning Province,ChinaProject(N140704001)supported by the Fundamental Research Funds for the Central Universities,China
文摘In order to improve the control performance of strip rolling mill, theoretical model of the hydraulic gap control(HGC) system was established. HGC system offline identification scheme was designed for a tandem cold strip mill, the system model parameters were identified by ARX model, and the identified model was verified. Taking the offline identified parameters as the initial values, online identification using recursive least square was carried out with model parameters changing. For the purpose of improving system robustness and decreasing the sensitivity due to model errors, the HGC system based on generalized predictive control(GPC) was designed, and simulation experiments for traditional controller and GPC controller were conducted. The results show that both controllers acquire good control effect with model matching. When the model mismatches, for the traditional controller, the overshot will increase to 76.7% and the rising time will increase to 165.7 ms, which cannot be accepted by HGC system; for the GPC controller, the overshot is less than 8.5%, and the rising time is less than 26 ms in any case.
文摘We are engaged in solving two difficult problems in adaptive control of the large-scale time-variant aerospace system. One is parameter identification of time-variant continuous-time state-space modei; the other is how to solve algebraic Riccati equation (ARE) of large order efficiently. In our approach, two neural networks are employed to independently solve both the system identification problem and the ARE associated with the optimal control problem. Thus the identification and the control computation are combined in closed-loop, adaptive, real-time control system . The advantage of this approach is that the neural networks converge to their solutions very quickly and simultaneously.
文摘A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established by black-box identification. And a quadratic objective function with receding horizon was selected to obtain the controller output. By solving a nonlinear optimization problem with equality constraint of model output and boundary constraint of controller output using Nelder-Mead simplex direct search method, a sub-optimal control law was achieved in feature space. The effect of the controller was demonstrated on a recognized benchmark problem and a continuous-stirred tank reactor. The simulation results show that the multi-step-ahead predictive controller can be well applied to nonlinear system, with better performance in following reference trajectory and disturbance-rejection.
文摘The problem of variable sampling time interval which appears in application of Kalman Filtering is analyzed and the corresponding filtering process with or without present transition matrix is suggested, then an application experiment for astronomical surveying is introduced. In this process, the known stochastically variable sampling time intervals play the roles as deterministic input sequences of the state-space description, and the corresponding matrix and (if needed) state transition matrix can be established by performing real-time and structure-linear system identification.
