Neuro-Control for Continuous-Time Stochastic Nonlinear Systems via Online Policy Iteration Algorithm

2020 ◽  
Author(s):  
Tianmin Zhou ◽  
Jiaxu Hou ◽  
Handong Li ◽  
Zengru Di ◽  
Bo Zhao
Keyword(s):  
Nonlinear Systems ◽  
Continuous Time ◽  
Policy Iteration ◽  
Stochastic Nonlinear Systems ◽  
Iteration Algorithm ◽  
Policy Iteration Algorithm

Approximate Solution for Optimal Control of Continuous-Time Switched Systems

2016 ◽  
Author(s):  
Tohid Sardarmehni ◽  
Ali Heydari
Keyword(s):  
Optimal Control ◽  
Continuous Time ◽  
Switched Systems ◽  
Online Training ◽  
Policy Iteration ◽  
Recursive Least Squares ◽  
Iteration Algorithm ◽  
Computational Burden ◽  
Time Dynamics ◽  
Policy Iteration Algorithm

Two approximate solutions for optimal control of switched systems with autonomous subsystems and continuous-time dynamics are developed. The proposed solutions consist of online training algorithms with recursive least squares training laws. The first solution is the classic policy iteration algorithm which imposes heavy computational burden (full back-up). In order to relax the computational burden in the policy iteration algorithm, the second algorithm is presented. The convergence of the proposed algorithms to the optimal solution in online training is investigated. Simulation results are presented to illustrate the effectiveness of the discussed algorithms.

A Safety-Certified Policy Iteration Algorithm for Control of Constrained Nonlinear Systems

2020 ◽  
Vol 4 (3) ◽  
pp. 686-691
Author(s):  
Navid Moshtaghi Yazdani ◽  
Reihaneh Kardehi Moghaddam ◽  
Bahare Kiumarsi ◽  
Hamidreza Modares
Keyword(s):  
Nonlinear Systems ◽  
Policy Iteration ◽  
Iteration Algorithm ◽  
Policy Iteration Algorithm ◽  
Constrained Nonlinear Systems
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