Data-driven integral sliding mode constrained control method based on full-form dynamic linearization

An integral sliding mode, data-driven technology, applied in the direction of adaptive control, general control system, control/adjustment system, etc., can solve the problem of poor steady-state performance of tracking error, etc., to eliminate offset error, suppress disturbance, and enhance stability sexual effect

Active Publication Date: 2022-04-22
JIHUA LAB
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Problems solved by technology

[0003] At present, most of the MFAC methods are based on compact form dynamic linearization (CFDL) and partial form dynamic linearization (PFDL). For discrete nonlinear systems with external disturbances and input constraints, the existing compact and local Type dynamic linearization methods perform poorly in eliminating offset errors and suppressing disturbances in the tracking error steady state

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  • Data-driven integral sliding mode constrained control method based on full-form dynamic linearization
  • Data-driven integral sliding mode constrained control method based on full-form dynamic linearization
  • Data-driven integral sliding mode constrained control method based on full-form dynamic linearization

Examples

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Embodiment 1

[0200] For a steam-water heat exchanger system, which is a discrete nonlinear system with external disturbances and input constraints, it is expressed as:

[0201] ;

[0202] in, for the first The output data at time (specifically the output temperature), for the first Input data at time (specifically input power), for the first The intermediate parameter of the moment.

[0203] Suppose the tracking target is , that is, the target output at any time Both are 2.5; the external disturbance is , where t is time, is the disturbance value, for the external disturbance value at time k , is the sampling period; the value of the preset function parameters involved is 0.11, is 2.7, for ; Boundary convergence constant is 0.2, the initial value and 1.672 and 1, respectively; the correction constant is 0.5; the initial value of the compensation value is 0; the input amplitude and input rate of the system are subject to the following constraints...

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Abstract

This application belongs to the technical field of automation control, and discloses a data-driven integral sliding mode constraint control method based on full-form dynamic linearization. The formal dynamic linearization method is used to control, and the discrete extended state observer is used to estimate the external disturbance, and the input compensator based on the integral sliding mode function is used to compensate the input. Compared with the traditional compact and local dynamic linear The optimization method retains more input and output information at the pre-sequence time, which will provide more useful information for the control process and improve system performance; the input limited compensator can be used to suppress the impact of input limitation on system performance, which can effectively Eliminate the offset error of the tracking error steady state, by introducing the integral sliding mode function, the parameters contained in it can better suppress the disturbance and enhance the stability of the system.

Description

technical field [0001] The present application relates to the technical field of automation control, in particular, to a data-driven integral sliding mode constraint control method based on full-form dynamic linearization. Background technique [0002] Because the model-based control (MBC) method needs to establish an accurate mathematical model for the controlled object, and for many actual complex objects, it is usually difficult to establish an accurate mathematical model or the model is too complex, which leads to the MBC method in reality. Use is restricted in . Compared with the MBC method, the MFAC (Model Free Adaptive Control) method does not need to establish an accurate mathematical model of the controlled object, and has a better application prospect. [0003] At present, most of the MFAC methods are based on compact form dynamic linearization (CFDL) and partial form dynamic linearization (PFDL). For discrete nonlinear systems with external disturbances and input...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 黄秀韦董志岩李志建邓涛古家威陈海龙霍震何昊名
Owner JIHUA LAB
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