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PSO Based Multi-Objective Approach for Controlling PID Controller 被引量:4
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作者 Harsh Goud Prakash Chandra Sharma +6 位作者 Kashif Nisar Ag.Asri Ag.Ibrahim Muhammad Reazul Haque Narendra Singh Yadav pankaj swarnkar Manoj Gupta Laxmi Chand 《Computers, Materials & Continua》 SCIE EI 2022年第6期4409-4423,共15页
CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system efficiency.It has a highly nonlinear characteristic that includes complexities... CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system efficiency.It has a highly nonlinear characteristic that includes complexities in its control and design.Dynamic performance is compassionate to change in system parameterswhich need more effort for planning a significant controller for CSTR.The reactor temperature changes in either direction from the defined reference value.It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature,and deviation from reference values may cause degradation of biomass quality.Design and implementation of an appropriate adaptive controller for such a nonlinear system are essential.In this paper,a conventional Proportional Integral Derivative(PID)controller is designed.The conventional techniques to deal with constraints suffer severe limitations like it has fixed controller parameters.Hence,A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s limitation.In the proposed technique,PID parameters are tuned by Particle Swarm Optimization(PSO).It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal response.In this article,a multi-objective function is proposed for PSO based controller design of CSTR. 展开更多
关键词 Particle swarm optimization multi-objective PSO continuous stirred tank reactor proportional integral derivative controller
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Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System
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作者 Harsh Goud Prakash Chandra Sharma +6 位作者 Kashif Nisar Muhammad Reazul Haque Ag.Asri Ag.Ibrahim Narendra Singh Yadav pankaj swarnkar Manoj Gupta Laxmi Chand 《Computers, Materials & Continua》 SCIE EI 2022年第8期3481-3492,共12页
Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response,less human interference,high dependability,improved hygiene,and reduced aging effects.That is ... Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response,less human interference,high dependability,improved hygiene,and reduced aging effects.That is why,in recent years,robotic aid has emerged as a blossoming solution to many challenges in the medical industry.In this manuscript,meta-heuristics(MH)algorithms,specifically the Firefly Algorithm(FF)and Genetic Algorithm(GA),are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd.The controller is used to control Mobile Robot System(MRS)at the required set point.The FF arrangements are made based on various pre-analysis.A detailed simulation study indicates that the proposed PID controller tuned with Firefly Algorithm(FF-PID)for MRSis beneficial and suitable to achieve desired closed-loop system response.The FF is touted as providing an easy,reliable,and efficient tuning technique for PID controllers.The most suitable ideal performance is accomplished with FF-PID,according to the display in the time response.Further,the observed response is compared to those received by applying GA and conventional off-line tuning techniques.The comparison of all tuning methods exhibits supremacy of FF-PID tuning of the given nonlinear Mobile Robot System than GA-PID tuning and conventional controller. 展开更多
关键词 Metaheuristic algorithm genetic algorithm PID controller mobile robot system firefly algorithm
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