Method for carrying out multi-objective optimization on parameters of nonlinear MIMO (multiple input multiple output) PID (proportional-integral-derivative) controller

Abstract

The invention discloses a method for carrying out multi-objective optimization on parameters of a nonlinear MIMO (multiple input multiple output) PID (proportional-integral-derivative) controller, and is characterized in that: 1. optimization objective: under the premise of satisfying a condition that the maximum overshoot is 50% less than a preset value and the static error is 1% less than a preset value, the sum of accumulated errors is minimized, and the energy consumption is lowest; 2. an operation of optimization problem solving is performed by using a multi-objective genetic algorithm; and an operation of algorithm improvement comprises a step of introducing quaternary codes, crossover and mutation operators and an adaptive density information based elite reservation and strategy; and 3. the numeric selection range of parameters is set according to the algorithm provided by the method, and the parameters of the controller is optimized. The method disclosed by the invention has the advantages that an operation of repeated debugging is not required to be performed, the multi-objective optimization can be performed on parameters in a given mode, and parameters with small static error, small overshoot and low energy consumption can be found out quickly; the method is intuitive, easy to operate and can carry out multivariable control on the expansion of objects; and a first-order time delay model and a PID controller are widely used in the existing industrial process, and an object model facilitates the industrial measurement.

Description

technical field [0001] The invention relates to a multi-objective optimization method for nonlinear MIMO PID controller parameters. Background technique [0002] Multiple-input multiple-output (MIMO) processes with time delays are ubiquitous in industrial production processes. Due to the coupling effect between the output channels, most of the developed univariate control methods are difficult to apply to multivariable processes. How to realize decoupling regulation and control is a research problem in the field of process control. At present, by setting static decoupling and dynamic decoupling controllers, and based on the unit feedback closed-loop control structure, decoupling controller design can be carried out, and some good control effects have been achieved, but these methods are cumbersome to deduce and difficult to apply in engineering promote. A multivariable closed-loop control system with n-dimensional input and m-dimensional output such as figure 1 shown. In...

AI Technical Summary

Problems solved by technology

Due to the strong coupling characteristics of MIMO systems, general parameter estimation methods cannot be directly applied

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