Multi-constraint self-adaptive control method for motor-driven manipulator

The invention discloses a multi-constraint adaptive control method for a motor-driven manipulator, and the method comprises the steps: firstly building a dynamic model of the manipulator, integrating an uncertain part in the dynamic model with a derivative of an inversion virtual control law, and obtaining a state space expression; based on the state space expression, the action executed by the manipulator is divided into n steps; a Mamdani fuzzy system is adopted to carry out approximation on a nonlinear function in each step of action; iterating in sequence, and calculating a virtual control rate and an adaptive rate of each step of action; and the virtual control rate and the self-adaption rate of the nth step serve as actual self-adaption control output signals, and the actual self-adaption control output signals are used for controlling the manipulator to act. The method is used for solving the problems existing in a control method of a motor-driven manipulator in the prior art, and the purpose of stable