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Model-free Optimal Tracking Control for an Aircraft Skin Inspection Robot with Constrained-input and Input Time-delay via Integral Reinforcement Learning

Xuewei Wu and Congqing Wang*
International Journal of Control, Automation, and Systems, vol. 18, no. 1, pp.245-257, 2020

Abstract : This paper presents a model-free optimal tracking control algorithm for an aircraft skin inspection robot with constrained-input and input time-delay. To tackle the input time-delay problem, the original system is transformed into a delay-free system with constrained-input and unknown input coupling term. In order to overcome the optimal control problem subject to constrained-input,a discounted value function is employed. In general, it is known that the HJB equation does not admit a classical smooth solution. Moreover, since the input coupling term of the delay-free system is unknown, a model-free integral reinforcement learning(IRL) algorithm which only requires the system sampling data generated by arbitrary different control inputs and external disturbances is proposed. The model-free IRL method is implemented on an actor-critic neural network (NN) structure. A system sampling data set is utilized to learn the value function and control policy. Finally, the simulation verifies the effectiveness of the proposed algorithm.

Keyword : Constrained-input, input time-delay, model-free, reinforcement learning

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