The problem of optimal tracking control for robot–environment interaction is studied in this article. The environment is regarded as a linear system and an admittance control with iterative linear quadratic regulator method is obtained to guarantee the compliant behaviour. Meanwhile, an adaptive dynamic programming-based controller is proposed. Under adaptive dynamic programming frame, the critic network is performed with radial basis function neural network to approximate the optimal cost, and the neural network weight updating law is incorporated with an additional stabilizing term to eliminate the requirement for the initial admissible control. The stability of the system is proved by Lyapunov theorem. The simulation results demonstrate the effectiveness of the proposed control scheme.

中文翻译：

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基于自适应动态规划的机器人-环境交互导纳控制器

本文研究了机器人-环境交互的最优跟踪控制问题。环境被视为一个线性系统，并通过迭代线性二次调节器方法获得导纳控制，以保证合规行为。同时，提出了一种基于自适应动态规划的控制器。在自适应动态规划框架下，批评网络采用径向基函数神经网络来逼近最优成本，并在神经网络权重更新律中加入额外的稳定项，以消除对初始容许控制的要求。系统的稳定性由李雅普诺夫定理证明。仿真结果证明了所提出的控制方案的有效性。