Approximate Optimal tracking Control for Nonlinear Discrete-time Switched Systems via Approximate Dynamic Programming

Qin, Chunbin; Huang, Yizhe; Yang, Yabin; Zhang, Jishi; Liu, Xianxing

doi:10.1109/ccdc.2019.8832761

Cited by 1 publication

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Inserting equations (10) and (11) into the Hamiltonian function, the time-varying HJ equations can be derived…”

Section: Problem Transformationmentioning

confidence: 99%

“…To approximate the performance index function and the feedback controller, the adaptive dynamic programming (ADP) technique was proposed by using two neural networks (NNs) [4]. The ADP technique has been applied successfully to strict-feedback non-linear systems [5,6], discrete-time non-linear systems [7,8] and nonlinear switched systems [9,10]. Very recently, the ADP technique was extended to derive the decentralised tracking controller for non-linear interconnected systems [11,12].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Finite‐horizon optimal tracking control for constrained‐input nonlinear interconnected system using aperiodic distributed nonzero‐sum games

Duan

Liu

2021

IET Control Theory & Appl

View full text Add to dashboard Cite

This paper proposes a distributed adaptive dynamic programming scheme to investigate the optimal tracking control problem for finite-horizon non-linear interconnected systems with constraint inputs under aperiodic sampling. A N-player nonzero-sum differential game system is constructed with the presented non-linear interconnected system and the tracking error system by introducing the augment vectors. To address the problems of constrained-input and finite-horizon control, a non-quadratic utility function and a finitehorizon cost function are utilized which will arise in the time-varying Hamilton-Jacobi (HJ) equation. Then, a periodic event-triggered scheme is designed to realize aperiodic sampling, where the consumption of communication resources is reduced and the Zeno behavior is avoided. Under the designed periodic event-triggered scheme, the time-varying HJ equation is almost impossible to get an analytical solution due to its hybrid properties and non-linearity. Therefore, the critic neural networks are used to estimate the optimal solution of the HJ equation, and the weight update law is constructed to guarantee the uniformly ultimate bounded of approximated errors. Further, the hybrid nonzero-sum differential game is confirmed to be uniformly ultimate bounded by using the Lyapunov theory. Finally, the obtained distributed PET control strategy is successfully applied to dispose the missile-target intercepter problem. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

“…Inserting equations (10) and (11) into the Hamiltonian function, the time-varying HJ equations can be derived…”

Section: Problem Transformationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Finite‐horizon optimal tracking control for constrained‐input nonlinear interconnected system using aperiodic distributed nonzero‐sum games

Duan

Liu

2021

IET Control Theory & Appl

View full text Add to dashboard Cite

show abstract

Approximate Optimal tracking Control for Nonlinear Discrete-time Switched Systems via Approximate Dynamic Programming

Cited by 1 publication

References 13 publications

Finite‐horizon optimal tracking control for constrained‐input nonlinear interconnected system using aperiodic distributed nonzero‐sum games

Finite‐horizon optimal tracking control for constrained‐input nonlinear interconnected system using aperiodic distributed nonzero‐sum games

Contact Info

Product

Resources

About