A computational successive improvement scheme for adaptive optimal control processes

1972 ◽  
Vol 10 (2) ◽  
pp. 78-93 ◽  
Author(s):  
S. E. Dreyfus ◽  
H. L. Stalford
Keyword(s):  
Optimal Control ◽  
Adaptive Optimal Control ◽  
Control Processes ◽  
Improvement Scheme

Adaptive optimal control of unknown nonlinear systems with different time scales

2017 ◽  
Vol 238 ◽  
pp. 179-190 ◽  
Author(s):  
Zhi-Jun Fu ◽  
Wen-Fang Xie ◽  
Subhash Rakheja ◽  
Dong-Dong Zheng
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Time Scales ◽  
Adaptive Optimal Control ◽  
Different Time Scales

scholarly journals Online Adaptive Optimal Control of Vehicle Active Suspension Systems Using Single-Network Approximate Dynamic Programming

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Zhi-Jun Fu ◽  
Bin Li ◽  
Xiao-Bin Ning ◽  
Wei-Dong Xie
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Approximate Dynamic Programming ◽  
Control Method ◽  
Active Suspension ◽  
Suspension System ◽  
Lyapunov Theory ◽  
Adaptive Optimal Control ◽  
Suspension Systems ◽  
Optimal Control Method

In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation) for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP). Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR) approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass) and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.

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