A Nonlinear Predictive Control Method of lpv Model Based on Interior Point Method

A technology of nonlinear prediction and control methods, which is applied in the direction of adaptive control, general control system, control/regulation system, etc., and can solve problems such as QP problem solving becomes a bottleneck, large amount of online calculation, and low solution accuracy

CN104698842BActive Publication Date: 2017-11-24ZHEJIANG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2017-11-24

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Abstract

The invention discloses an LPV model nonlinear predictive control method based on an interior point method. First, at the set working point, linearize the complex mechanism model of the system to obtain multiple linear sub-models; secondly, select the weight function and weight each linear sub-model to obtain the global approximation model of the system, which is called the linear variable parameter model or LPV model ; Then, the LPV model is used as the predictive model, and the quadratic performance index function is used to construct the nonlinear predictive control proposition; finally, in the rolling optimization process, the interior point algorithm is used to solve the optimization proposition, and the optimal control sequence is obtained to complete the nonlinear predictive control. Compared with the prior art, the method of the present invention is based on the LPV model, which is fully simultaneously and directly solved, with high solution accuracy and short algorithm time-consuming; reflected in the control effect, it shortens the transition process of the system and reduces resource consumption, especially Under a wide range of variable working conditions, the control quality of the system is obviously improved.
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Description

technical field

[0001] The invention belongs to the field of industrial process control and relates to an LPV model nonlinear predictive control method based on an interior point method. Background technique

[0002] In actual industry, with the continuous pursuit of production efficiency and stricter environmental protection, industrial processes have become more and more complex, and most of them have strong nonlinear characteristics, and are complex chemical objects with constraints on control quantities. Using a single linear model to describe such a system and design a controller cannot meet the control performance requirements, and even cause system instability. Therefore, it is necessary to explore multi-model methods. The linear variable parameter model (LPV) in the multi-model method has the advantages of simple algorithm and can use the main factors that cause the nonlinearity of the system as scheduling variables. Therefore, the present invention uses the LPV mode...

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Embodiment Construction

[0058] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0059] like figure 1 Shown is the block diagram of the control system of the present invention, wherein the sub-model i, (i=1, 2, . . . p ) is a linear model set obtained after selecting working points in the operating space of the system. Since the working point variable is one of the input variables, at the sampling time k, the weight coefficient α(w) of each linear sub-model is calculated by using the weight function formula according to the distance between the actual output of the controlled object and each working point; according to the global The LPV model obtains the predicted output from time k+1 to P; at time k, use the interior point method to solve an optimization proposition on a finite time domain [k, k+P], and solve the current control increment Δu(k) act on the system. At the next sampling time, the nonlinear predic...