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Adaptive Sliding Mode Control Method for Nonlinear Switched Systems Based on Compound Learning

An adaptive sliding mode and switching system technology, applied in the field of flight control, can solve problems such as poor practicability, and achieve the effects of facilitating engineering applications, improving learning accuracy, and reducing chattering

Active Publication Date: 2022-06-21
NORTHWESTERN POLYTECHNICAL UNIV +1
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Problems solved by technology

[0005] In order to overcome the shortcomings of poor practicability of existing nonlinear switching system control methods, the present invention provides an adaptive sliding mode control method for nonlinear switching systems based on compound learning

Method used

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  • Adaptive Sliding Mode Control Method for Nonlinear Switched Systems Based on Compound Learning
  • Adaptive Sliding Mode Control Method for Nonlinear Switched Systems Based on Compound Learning
  • Adaptive Sliding Mode Control Method for Nonlinear Switched Systems Based on Compound Learning

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Embodiment Construction

[0073] The present invention will now be further described in conjunction with the embodiments and accompanying drawings:

[0074] refer to figure 1 , the specific steps of the adaptive sliding mode control method of the nonlinear switching system based on compound learning of the present invention are as follows:

[0075] Step 1: Consider the variant aircraft wing rock model

[0076]

[0077] Among them, φ, and are the roll angle, roll angular rate and roll angular acceleration, respectively, and u is the control input;

[0078] The various coefficients in the model are defined as

[0079]

[0080] Among them, a 1 to a 5 is a variable related to the angle of attack, c 1 and c 2 is a constant determined by the sweep angle;

[0081] Define the state quantity x(t)=[x 1 ,x 2 ] T ∈R 2 , where x 1 =φ, Using the sweep angle as the switching signal, the wing rock model of the variant aircraft can be transformed into a second-order single-input single-output no...

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Abstract

The invention relates to an adaptive sliding mode control method for a nonlinear switching system based on compound learning, which is used to solve the technical problem of poor practicability of the existing nonlinear switching system control method. Considering the external disturbance and input nonlinearity of the nonlinear switched system, the input dead zone model of the switched system is obtained; the unknown nonlinear function and compound disturbance of the system are estimated by using the neural network and the switched disturbance observer respectively, and the representation learning performance is constructed based on the parallel estimation model Good or bad prediction error, adjust the neural network weight update law and disturbance observer through the prediction error; design an adaptive sliding mode switching controller based on the dynamic inverse technical framework and compound learning strategy; use the prediction error to construct a sliding mode time-varying gain function , reducing the chattering amplitude of sliding mode switching and improving the performance of sliding mode control; the present invention combines the characteristics of nonlinear switching system control and effectively improves the control performance by designing an adaptive sliding mode controller based on compound learning.

Description

technical field [0001] The invention relates to a control method of a nonlinear switching system, in particular to an adaptive sliding mode control method of a nonlinear switching system based on compound learning, which belongs to the field of flight control. Background technique [0002] In practical engineering, many control objects such as variant aircraft, variable frequency motors, and robots can be described by nonlinear switching systems. Therefore, the control technology of nonlinear switching systems has attracted extensive attention. researched and applied. [0003] The nonlinear switching system itself has strong uncertainty, and is easily affected by external disturbance and input dead zone. The existing control methods mostly use intelligent systems such as neural network or fuzzy logic to approximate the uncertainty, and use disturbance observer to estimate the uncertainty. external interference. These control methods only consider the approximation effect o...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 许斌程怡新马波
Owner NORTHWESTERN POLYTECHNICAL UNIV