Periodic adaptive learning control method of input saturation mechanical arm system

A technology of adaptive learning and control method, applied in the field of periodic adaptive learning control

Inactive Publication Date: 2015-04-29
JIANGNAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to solve a cycle adaptive learning control problem of an input saturated manipulator system, and propose a cycle adaptive compensation learning manipulator torque control algorithm for a class of input saturated time-delay manipulator system

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  • Periodic adaptive learning control method of input saturation mechanical arm system
  • Periodic adaptive learning control method of input saturation mechanical arm system
  • Periodic adaptive learning control method of input saturation mechanical arm system

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Embodiment Construction

[0080] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0081] For the strongly coupled, nonlinear and time-delay manipulator periodic system with many uncertainties in the form of formula (1), x 1 (t) and x 2 (t) are the rotation angle and angular velocity of the mechanical arm respectively, the parameter mass of the mechanical arm is m=3kg, the length of the mechanical arm is l=1m, and the coefficient of inertia J m =ml 2 , gravitational acceleration g=10m / s 2 ,when When it is external disturbance, z(t)=|cos(2t)|, system period T=2π. Torque saturation input υ(t)=f(t), and the saturation boundary υ max =0.8, υ min =-0.8, at this time the manipulator system can be rewritten as formula (2) in the form:

[0082]

[0083] The structure diagram of the control system of the inventive method is as figure 1 shown. Design according to the tracking controller of formula (7) and (8) form according to the ...

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Abstract

The invention discloses a periodic adaptive learning control method of an input saturation mechanical arm system. Firstly, an input saturation nonlinear time-delay mechanical arm system model is established; then, a nonlinear time-varying mechanical arm periodic system equation with a Brunovsky standard form is constructed; a tracking controller and a compensatory learning controller are designed; stability and boundedness analysis is carried out according to a composite energy function method, and finally control parameters are selected to achieve real-time adaptive iterative learning torque control over the mechanical arm periodic system. The control method has the advantages of being better in adaptivity, capable of being well used for carrying out compensation on different degrees of saturation input, good in robustness, and capable of being popularized for achieving control over a periodic system without saturation characteristics and and popularized to a nonlinear periodic system without time-delay items; the controllers are easier and more convenient to obtain.

Description

technical field [0001] The invention relates to a cycle self-adaptive learning control method for an input saturated manipulator system, which belongs to the field of automatic control. Background technique [0002] With the development of modern digital technology, especially in engineering practice such as digital signal processing and network communication, a large number of systems such as multi-frequency sampling control, period compensation control and oscillation control have appeared, and their essence is period system. In the field of automatic control, the manipulator is also a typical repetitive cycle system. It is a high-precision, high-speed manipulator. It has been widely used in industrial manufacturing, medical, aerospace and semiconductor manufacturing. It is the most widely used automatic mechanical device in the field. On the basis of receiving instruction signals, the robotic arm can complete periodic repetitive operations such as point-to-point in three...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
Inventor 陶洪峰霰学会
Owner JIANGNAN UNIV
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