Multivariable PID controller parameter setting method

Abstract

The invention relates to a multivariable PID controller parameter setting method. The multivariable PID controller parameter setting method comprises following steps of leading in a model of a control system, and generating a reference point set in dependence on the target number of design models and a system sampling method; generating an initial population which is distributed uniformly randomly, wherein each individual in the population is a multivariable PID controller parameter; carrying out genetic algorithm operation to the population by Comprehensively considering a plurality of system performance indexes such as the steady state error, the rise time, the adjusting time and the overshoot to obtain a new population; mixing the obtained new population with the initial population, and achieving multivariable PID controller parameter setting. Under the condition that the same stability index is satisfied, the dynamic performance and the static performance of the optimization scheme provided by the invention are better.

Description

technical field [0001] The invention relates to the technical field of automatic control, in particular to a multivariable PID controller parameter tuning method based on a high-dimensional multi-objective genetic algorithm. Background technique [0002] With the continuous development of industrial technology, the production process has become more complex and compact, which means that the traditional single variable control has been difficult to meet the control needs of the actual production process. However, PID has been widely used due to its own advantages. In order to meet the needs of complex production processes, how to set multi-variable PID parameters has important practical significance. [0003] At present, the academic and engineering circles at home and abroad usually convert the performance index of the system into a weighted objective function through its importance, and then use the traditional single-objective optimization algorithm to optimize and solve i...

AI Technical Summary

Problems solved by technology

However, these existing methods generally have defects such as difficulty in setting weight coefficients accurately, configuration schemes are difficult to guide engineering practice, etc.

Although some researchers have used traditional multi-objective optimization methods to try to solve multi-variable PID control parameter tuning, traditional multi-objective optimization algorithms can only effectively deal with 2-3 objectives, and cannot fully consider the full performance of the system. Low efficiency, not convenient for specific project implementation

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