Adaptive control method and system for non-standard discrete-time nonlinear systems
A nonlinear system and adaptive control technology, applied in the field of control, can solve problems such as nonlinear parameterization uncertainty, non-standard discrete-time nonlinear systems cannot adapt to standard discrete-time nonlinear system control methods, etc.
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example 1
[0310] The self-adaptive control method of a non-standard discrete-time nonlinear system proposed by the invention can be effectively used in the design of the control law of a single-link flexible joint robot. For the sake of simplicity, the influence of damping is ignored in the actual control. First, a brief introduction to this type of robot system is given.
[0311] like figure 2 As shown, the motion equation of the single-link flexible joint robot is described as follows:
[0312]
[0313]
[0314] In the formula, q 1 ,q 2 is the angular position of the connecting rod and the motor, I and J are the moments of inertia, g is the acceleration due to gravity, k is the elastic constant of the joint spring, M and L represent the mass of the connecting rod and the position of the center of gravity, and u is the torque applied to the motor. First convert it into a mathematical model with control signals. make x 1 =q 1 , x 3 =q 2 , Then equations (53)(54) can ...
example 2
[0343] Take the following numerical simulation model as an example:
[0344]
[0345] x 2 (t+1)=0.2x 2 (t)5arctanx 1 (t)+1.3sinx 3 (t)
[0346] x 3 (t+1)=0.2x 3 (t)+1.6sinx 2 (t)
[0347] in, i=1, 2, 3 are the 3 state variables of the system, is the system input.
[0348] The system model is parameterized as
[0349]
[0350] y(t)=Cx(t)
[0351] in A known, and
[0352]
[0353] in
[0354] φ f (x(t))=[sinx 1 (t)cosx 3 (t), arctanx 1 (t), sin x 3 (t), sinx 2 (t)] T , C=[0,1,0] T . suppose C is unknown, φ f , φ g is known.
[0355] but,
[0356] Step 1: Suppose the system output y=x 2 (t), to establish a system output dynamic model;
[0357] It can be seen from the above that y(t+1)=0.2x 2 (t)+1.5arctanx 1 (t)+1.3sinx 3 (t) does not include the control input, so there are
[0358]
[0359] This means that y(t+2) contains both linear and nonlinear parameter uncertainties, and the nonlinearity depends on the control input. ...
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