PID Control for Nonlinear Processes
This chapter presents a proportional-integral-derivative (PID) Takagi-Sugeno fuzzy system controller that can be trained by the particle swarm optimization-cuckoo search (PSOCS) technique to control nonlinear multi-input multi-output (MIMO) systems. Instead of the standard methods that are widely us...
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| Autores principales: | , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2023
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/83451 |
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| Sumario: | This chapter presents a proportional-integral-derivative (PID) Takagi-Sugeno fuzzy system controller that can be trained by the particle swarm optimization-cuckoo search (PSOCS) technique to control nonlinear multi-input multi-output (MIMO) systems. Instead of the standard methods that are widely used in the literature, the PSOCS is used to adjust all of the PID parameters by the minimization of a given objective function. A nonlinear MIMO system has been selected to be controlled by this controller. The simulation results show the notable control accuracy and generalization ability of this MIMO controller. Finally, a comparative study with a PSO algorithm and CS algorithm shows the superiority of the PSOCS over these two optimization methods in terms of guaranteeing the desired performance. |
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| ISBN: | 978-1-80356-584-2 |
| DOI: | 10.5772/intechopen.106820 |