GA-Based Controller Optimization Design

Jili Tao (), Ridong Zhang () and Yong Zhu ()
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Jili Tao: NingboTech University, School of Information Science and Engineering
Ridong Zhang: Hangzhou Dianzi University, The Belt and Road Information Research Institute
Yong Zhu: NingboTech University, School of Information Science and Engineering

Chapter Chapter 9 in DNA Computing Based Genetic Algorithm, 2020, pp 221-260 from Springer

Abstract: Abstract In this chapter, GA is used to optimize the controller design. First, a new PID controller is designed by using a non-minimal state-space model through predictive function control. The weighting matrix in the predictive function controller is optimized through GA so as to achieve a relatively desired closed-loop control performance. Secondly, a fuzzy neuron non-model controller is designed for a continuous casting process with strong nonlinearity and severe uncertainty, and its parameters are optimized through RNA-GA. Finally, a MOGA based on parameter stabilization space of the PID controller is used to control the first-order lag unstable process. The simulation results confirm the effectiveness of GA and its improved format in the optimization of the control system design problem.

Date: 2020
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DOI: 10.1007/978-981-15-5403-2_9

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