Title: An intelligent optimal control approach for motion/force control of constrained non-holonomic mobile manipulators
Authors: Komal Rani; Naveen Kumar
Addresses: Department of Mathematics, National Institute of Technology Kurukshetra, Haryana-136119, India; Babu Anant Ram Janta College Kaul, Kaithal, Haryana-136021, India ' Department of Mathematics, National Institute of Technology Kurukshetra, Haryana-136119, India
Abstract: This paper presents motion/force control problem of constrained non-holonomic mobile manipulators in the presence of uncertainties and external disturbances. The paper proposes an intelligent control scheme utilising the optimal control technique, neural network and adaptive bounds. Firstly, dynamics of mobile manipulator is reduced into state-space form and two sets of variables are created to describe the constrained and unconstrained motion separately. Then the optimal control, which is the explicit solution of Hamilton-Jacobi-Bellman (HJB) equation, is obtained from an algebraic Riccati equation. The nonlinear dynamics of the system are compensated using radial basis function neural network. Bounds on uncertainties of the system and neural network approximation error are estimated with adaptive bound part. The neural networks are trained in online manner using weight update algorithms derived with Lyapunov approach to guarantee the stability of the system. Finally, the proposed approach is verified through numerical simulation studies.
Keywords: optimal motion/force control; mobile manipulator; RBFNN; non-holonomic and holonomic constraint; Hamilton-Jacobi-Bellman optimisation; performance index; asymptotic stability.
International Journal of Mechatronics and Automation, 2021 Vol.8 No.3, pp.151 - 161
Received: 10 Dec 2020
Accepted: 19 Aug 2021
Published online: 25 Oct 2021 *