An optimal control approach for hybrid motion/force control of coordinated multiple nonholonomic mobile manipulators using neural network
by Komal Rani; Naveen Kumar
International Journal of Modelling, Identification and Control (IJMIC), Vol. 37, No. 2, 2021

Abstract: This paper presents an intelligent optimal control approach for motion/force control of cooperative multiple nonholonomic mobile robot manipulators carrying a single rigid object. Firstly, a state-space form of error dynamics is derived for quadratic optimisation using a combined model of multiple mobile manipulators and the object. The explicit solution of Hamilton Jacobi Bellman (HJB) equation for optimal control is obtained by Riccati equation. The linear optimal control, neural network and adaptive bound are utilised to design the proposed controller. The radial basis function neural network approximates the unknown dynamics and adaptive compensator estimates the bounds on neural network approximation error and the unstructured uncertainties of the system. The asymptotical stability of the closed-loop system is demonstrated using Lyapunov stability analysis and the optimal control theory. Finally, the simulation results are produced with two identical mobile manipulators grasping the single rigid object in comparative manner to show the efficacy of proposed scheme.

Online publication date: Tue, 11-Jan-2022

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