Abstract
For achieving trajectory tracking issue of the lower limb exoskeleton robot, a novel optimal robust control with cooperative game theory is proposed. The uncertainties are considered (possible time-varying, bounded and fast) and the fuzzy set theory is creatively adopted to describe the boundary. From the view of analytical mechanics, the trajectory tracking is treated as the constraints control problem, including holonomic and nonholonomic constraints. A robust control is designed with two adjustable parameters to guarantee the uniform boundedness and uniform ultimate boundedness. For obtaining the optimal selection of two adjustable parameters, a novel optimal control employed cooperative game theory is proposed. Combining the robust control and optimal design, optimal robust control is formulated. The Pareto optimal solution is obtained to guarantee the minimum control cost. In the simulation, the adaptive robust control of Sun is chosen as a comparison. The existence of Pareto optimality and the effectiveness of optimal robust control have been verified via simulation results.
Forward and Inverse Predictive Model for the Trajectory Tracking Control of a Lower Limb Exoskeleton for Gait Rehabilitation: Simulation modelling analysis
