Cyber-physical systems integrate computing,network and physical environments to make the systems more efficient and cooperative,and have important and extensive application prospects,such as the Internet of things.Thi...Cyber-physical systems integrate computing,network and physical environments to make the systems more efficient and cooperative,and have important and extensive application prospects,such as the Internet of things.This paper studies the control problem of nonlinear cyber-physical systems with unknown dynamics and communication delays.A networked learning predictive control scheme is proposed for unknown nonlinear cyber-physical systems.This scheme recursively learns unknown system dynamics,actively compensates for communication delays and accurately tracks a desired reference.Learning multi-step predictors are presented to predict various step ahead outputs of the unknown nonlinear cyber-physical systems.The optimal design of controllers minimises a performance cost function which measures the tracking error predictions and control input increment predictions.The system analysis leads to the stability criteria of closed-loop nonlinear cyber-physical systems employing the networked learning predictive control scheme.An example illustrates the outcomes of the proposed scheme.展开更多
This paper presents a novel observer-based predictive control method for networked systems where random network-induced delays,packet disorders and packet dropouts in both feedback and forward channels are considered....This paper presents a novel observer-based predictive control method for networked systems where random network-induced delays,packet disorders and packet dropouts in both feedback and forward channels are considered.The proposed method has three significant features:i)A concept of destination-based lumped(DBL)delay is introduced to represent the combined effects of random communication constraints in each channel;ii)in view of different natures of the random DBL delays in the feedback and forward channels,different compensation schemes are designed;and iii)it is actual control inputs rather than predicted ones that are employed to generate future control signals based on the latest system state estimate available in the controller.For the resulting closed-loop system,a necessary and sufficient stability condition is derived,which is less conservative and also independent of random communication constraints in both channels.Simulation results are provided to demonstrate the effectiveness of the proposed method.展开更多
基金the National Natural Science Foundation of China under Grant No.61773144。
文摘Cyber-physical systems integrate computing,network and physical environments to make the systems more efficient and cooperative,and have important and extensive application prospects,such as the Internet of things.This paper studies the control problem of nonlinear cyber-physical systems with unknown dynamics and communication delays.A networked learning predictive control scheme is proposed for unknown nonlinear cyber-physical systems.This scheme recursively learns unknown system dynamics,actively compensates for communication delays and accurately tracks a desired reference.Learning multi-step predictors are presented to predict various step ahead outputs of the unknown nonlinear cyber-physical systems.The optimal design of controllers minimises a performance cost function which measures the tracking error predictions and control input increment predictions.The system analysis leads to the stability criteria of closed-loop nonlinear cyber-physical systems employing the networked learning predictive control scheme.An example illustrates the outcomes of the proposed scheme.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.61673023 and 61773144the Youth Talent Support Program of Beijing Municipality+2 种基金the NCUT Yujie Talent Training Programthe NCUT Science and Technology Innovation Projectthe BMEC Basic Scientific Research Foundation。
文摘This paper presents a novel observer-based predictive control method for networked systems where random network-induced delays,packet disorders and packet dropouts in both feedback and forward channels are considered.The proposed method has three significant features:i)A concept of destination-based lumped(DBL)delay is introduced to represent the combined effects of random communication constraints in each channel;ii)in view of different natures of the random DBL delays in the feedback and forward channels,different compensation schemes are designed;and iii)it is actual control inputs rather than predicted ones that are employed to generate future control signals based on the latest system state estimate available in the controller.For the resulting closed-loop system,a necessary and sufficient stability condition is derived,which is less conservative and also independent of random communication constraints in both channels.Simulation results are provided to demonstrate the effectiveness of the proposed method.
