PID (Proportion Integration Differentiation) controller optimizing design method based on particle swarm membrane algorithm

Abstract

The invention relates to a PID controller parameter optimizing method, and especially discloses a PID controller optimizing design method based on a particle swarm membrane algorithm. The method comprises that an optimal particle is obtained from a swarm, different dimension values of the particle are successively assigned to to-be-optimized parameters Kp, Ki and Kd, a control system model is operated, performance indexes output by the system are obtained, and it is determined whether the evolution rule is used again to search for the optimal particle so that the optimal control effect can be obtained. The PID controller optimizing design method combines membrane computing with traditional PSO (Particle Swarm Optimization), fully utilizes the partition function and transport communication rules, can obtain a set of more proper PID control parameters, and finally enables a controlled system to achieve the optimal control effect. According the PID controller optimizing design method, the controlled system can obtain the set of more proper PID control parameters and achieves the optimal control effect under the condition that the controller structure is not changed.

Description

technical field [0001] The invention relates to the technical field of industrial process control, in particular to a PID (proportional-integral-derivative) controller parameter optimization method based on a particle swarm membrane algorithm. Background technique [0002] The emergence of industrial automation has brought huge economic benefits while greatly improving production efficiency. As its key link, the control system has developed rapidly both in theory and in technical applications. In the industrial process, when the control system is put into operation, the controller must be optimized, so that the control system can obtain the best control performance as much as possible to obtain greater economic benefits. The optimal design of the controller generally includes two aspects, namely, the optimization of the controller structure and the optimization of the controller parameters. The optimization design of the controller of the present invention refers to the opt...

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Problems solved by technology

Traditional PID controller optimization design methods mainly include Ziegler-Nichols method (Z-N method), simplex method, relay tuning method, etc. The common advantage of these methods is simplicity, but they have the same problems in the process of PID controller optimization design. That is, it is difficult to achieve the optimal setting of parameters, and it is easy to generate oscillation and large overshoot, and the adjustment time is often long

However, intelligent PID controller optimization design methods such as genetic algorithm (GA) and particle swarm algorithm (PSO) are prone to fall into premature phenomenon in the optimization design process of high-order systems or systems with pure lag links and cannot obtain the global optimal value. As a result, the controlled system cannot obtain a satisfactory control effect.

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