Model-free adaptive control method based on control input saturation

A technology of model-free self-adaptation and control method, which is applied in the direction of self-adaptive control, general control system, control/regulation system, etc., and can solve problems such as insufficient avoidance of saturation

Active Publication Date: 2016-10-26
南京杰峰实业有限公司
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Problems solved by technology

Sometimes the saturation problem in the actual system is not caused by the controller design. When the reference trajectory setting is unreasonable, the correct controller design cannot fully avoid the saturation problem.

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  • Model-free adaptive control method based on control input saturation
  • Model-free adaptive control method based on control input saturation
  • Model-free adaptive control method based on control input saturation

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Embodiment Construction

[0119] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0120]The invention provides a model-free adaptive control method based on control input saturation. The invention considers that the control input has position and velocity saturation, and designs an adaptive neural network constraint controller based on observer technology. During the design process A dynamic anti-saturation compensator is proposed to adjust the reference setpoint in real time to ensure that the control input does not enter the saturation region. Firstly, the feedback linearization method is used to transform the general affine nonlinear system, and then a neural network observer and constraint controller are designed for the transformed system, and a dynamic anti-saturation algorithm is given to adjust the reference set value on-line so that The controller's input always operates within the constrained range.

[0121] Step 1...

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Abstract

The invention provides a model-free adaptive control method based on control input saturation. Under the condition of considering control input has position and rate saturation, the invention designs an adaptive neural network constraint controller based on observer technology; and in the design process, a dynamic anti-saturation compensator is provided for adjusting reference preset value in real time to ensure control input does not enter a saturation region. The method is characterized by, to begin with, carrying out model transformation on a common affine nonlinear system through a feedback linearization method; and then, designing a neural network observer and a constraint controller for the transformed system, and providing a dynamic anti-saturation algorithm to adjust a reference set value online to enable the input of the controller to be always within a constraint range.

Description

technical field [0001] The invention relates to the field of high-order nonlinear system control methods, in particular to a model-free adaptive control method based on control input saturation. Background technique [0002] Practical control systems are nonlinear, and there are always a large number of constraints. When the state of the system changes within a relatively small range, it can generally be described by a linear differential equation, and it can be analyzed and designed with a relatively mature linear system theory. If a large-scale working area of ​​the system is to be considered, and the system state will be limited by constraints, it is difficult to effectively solve it by using the linear system theory [1]. [0003] The saturation problem is relatively common in various nonlinear systems. For example: the motor can only reach a limited speed due to physical limitations, the output of the operational amplifier generally does not exceed its power supply vol...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/02
CPCG05B13/027
Inventor 周洪成陈正宇杨娟
Owner 南京杰峰实业有限公司
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