A new hierarchical approach for optimal control of robot manipulators

In this paper, a new approach for optimal control of robot manipulators is presented. For this purpose, the system is considered as a two-level large-scale system where a gradient based coordination strategy is used to coordinate the overall system. This is achieved within a decomposition-coordination framework, where the robot manipulator is first decomposed into several sub-systems in such a way that each sub-system consists of several consecutive links and joints. With the aim of optimization, the control problem is first decomposed into m sub-problems, at the first level, where each sub-problem is solved using a gradient optimization method. Then, by using a new methodology which is based on the gradient of interaction prediction errors, at the second level, the coordination of the overall large-scale system is done. This approach provides a new scheme for hierarchical control of robot manipulators with high degree of freedom and the results fairly illustrate the effectiveness of the proposed coordination strategy.