Adaptive dynamic programming enhanced admittance control for robots with environment interaction and actuator saturation

Abstract This paper focuses on the optimal tracking control problem for robot systems with environment interaction and actuator saturation. A scheme combined admittance adaptation adaptive dynamic programming (ADP) is developed. The unknown modelled as a linear system controller derived to achieve compliant behaviour of robot. In ADP framework, cost function defined non-quadratic form critic network designed radial basis neural which introduces obtain an approximate Hamilton–Jacobi–Bellman equation, guarantees trajectory tracking. stability analysed by Lyapunov theorem simulations demonstrate effectiveness proposed strategy.