Bi‐criteria optimal control of redundant robot manipulators using LVI‐based primal‐dual neural network

Abstract

AbstractIn this paper, a bi‐criteria weighting scheme is proposed for the optimal motion control of redundant robot manipulators. To diminish the discontinuity phenomenon of pure infinity‐norm velocity minimization (INVM) scheme, the proposed bi‐criteria redundancy‐resolution scheme combines the minimum kinetic energy scheme and the INVM scheme via a weighting factor. Joint physical limits such as joint limits and joint‐velocity limits could also be incorporated simultaneously into the scheme formulation. The optimal kinematic control scheme can be reformulated finally as a quadratic programming (QP) problem. As the real‐time QP solver, a primal‐dual neural network (PDNN) based on linear variational inequalities (LVI) is developed as well with a simple piecewise‐linear structure and global exponential convergence to optimal solutions. Since the LVI‐based PDNN is matrix‐inversion free, it has higher computational efficiency in comparison with dual neural networks. Computer simulations performed based on the PUMA560 manipulator illustrate the validity and advantages of such a bi‐criteria neural optimal motion‐control scheme for redundant robots. Copyright © 2009 John Wiley & Sons, Ltd.