Optimal control scheme for nonlinear systems with saturating actuator using ε-iterative adaptive dynamic programming

2012 ◽  
Author(s):  
Xiaofeng Lin ◽  
Yuanjun Huang ◽  
Nuyun Cao ◽  
Yuzhang Lin
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Nonlinear Systems ◽  
Adaptive Dynamic Programming ◽  
Adaptive Dynamic ◽  
Control Scheme ◽  
Optimal Control Scheme

scholarly journals Adaptive Dynamic Programming based Control Scheme for Uncertain Two-Wheel Robots

2021 ◽  
Author(s):  
Linh Nguyen
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Adaptive Dynamic Programming ◽  
Control Law ◽  
Parameter Uncertainties ◽  
Adaptive Dynamic ◽  
Uncertain Dynamics ◽  
Control Scheme ◽  
State Controller ◽  
Optimal Control Scheme

<div>The paper addresses the problem of effectively controlling a two-wheel robot given its inherent non-linearity and parameter uncertainties. In order to deal with the unknown</div><div>and uncertain dynamics of the robot, it is proposed to employ the adaptive dynamic programming, a reinforcement learning based technique, to develop an optimal control law. It is interesting that the proposed algorithm does not require kinematic parameters while finding the optimal state controller is guaranteed. Moreover, convergence of the optimal control scheme is theoretically proved. The proposed approach was implemented in a synthetic</div><div>two-wheel robot where the obtained results demonstrate its</div><div>effectiveness.</div>

scholarly journals Adaptive Dynamic Programming based Control Scheme for Uncertain Two-Wheel Robots

2021 ◽  
Author(s):  
Linh Nguyen
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Adaptive Dynamic Programming ◽  
Control Law ◽  
Parameter Uncertainties ◽  
Adaptive Dynamic ◽  
Uncertain Dynamics ◽  
Control Scheme ◽  
State Controller ◽  
Optimal Control Scheme

<div>The paper addresses the problem of effectively controlling a two-wheel robot given its inherent non-linearity and parameter uncertainties. In order to deal with the unknown</div><div>and uncertain dynamics of the robot, it is proposed to employ the adaptive dynamic programming, a reinforcement learning based technique, to develop an optimal control law. It is interesting that the proposed algorithm does not require kinematic parameters while finding the optimal state controller is guaranteed. Moreover, convergence of the optimal control scheme is theoretically proved. The proposed approach was implemented in a synthetic</div><div>two-wheel robot where the obtained results demonstrate its</div><div>effectiveness.</div>

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