Saturation Compensation Control Method of Manipulator System Based on Neural Network Dynamic Surface Sliding Mode Control
A technology of neural network and control method, applied in the field of manipulator system saturation compensation control, which can solve the problems of complexity explosion, ineffective saturation compensation of manipulator servo system, uncertainty of model parameters, etc.
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[0088] The present invention will be further described below in conjunction with the accompanying drawings.
[0089] refer to Figure 1-Figure 5 , a control method for saturation compensation of a manipulator system based on neural network dynamic surface sliding mode control, comprising the following steps:
[0090] Step 1, establish the dynamic model of the servo system of the manipulator, initialize the system state, sampling time and control parameters, the process is as follows:
[0091] 1.1 The expression form of the dynamic model of the manipulator servo system is
[0092]
[0093] Among them, q and θ are the angles of the manipulator connecting rod and the motor, respectively; g is the acceleration of gravity; I is the inertia of the connecting rod; J is the inertia of the motor; K is the spring stiffness coefficient; length; u is the control signal; v(u) is saturation, expressed as:
[0094]
[0095] Where sgn(u) is an unknown nonlinear function; v max is th...
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