Optimization Strategy of Bio-Inspired Metaheuristic Algorithms Tuned PID Controller for PMBDC Actuated Robotic Manipulator
| Autor: | Sudarshan K. Valluru, Madhusudan Singh |
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| Rok vydání: | 2020 |
| Předmět: |
Settling time
Computer science Robot manipulator Particle swarm optimization PID controller 020206 networking & telecommunications 02 engineering and technology Reduction (complexity) Nonlinear system Control theory 0202 electrical engineering electronic engineering information engineering Overshoot (signal) General Earth and Planetary Sciences 020201 artificial intelligence & image processing Metaheuristic General Environmental Science |
| Zdroj: | Procedia Computer Science. 171:2040-2049 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2020.04.219 |
| Popis: | The present article makes an attempt to evaluate the computational performance of genetic meta heuristic optimized control algorithms. Here, the multi-objective bio inspired algorithm (MOGA) and adaptive particle swarm optimization (APSO) algorithm are used to tune linear PID (L-PID) and nonlinear PID(NL-PID) controllers to implement performance and execution control of permanent magnet brushed DC (PMBDC) motor actuated robotic manipulator. The MOGA, APSO optimised nonlinear and linear PID controllers have been validated for their response efficacy and compared in respect of the steady-state error, overshoot and settling time of PMBDC driven robotic Manipulator. The efficacy of metaheuristics such as APSO and MOGA tuned NL-PID controller are better as compared to the L- PID controlled objects. Experimental results show that the NL-PID controller mends the controlled objects’ performace with a reduction in both the overshoot as well as the settling time, if tuned either with MOGA or APSO for L-PID controllers while NL-PID controller tuned with APSO gives satisfactory dynamic response of the system. |
| Databáze: | OpenAIRE |
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