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Intelligent Control of Biped Robots: Optimal Fuzzy Tracking Control via Multi- Objective Particle Swarm Optimization and Genetic Algorithms | ||
| AUT Journal of Mechanical Engineering | ||
| مقاله 3، دوره 4، شماره 2، شهریور 2020، صفحه 183-192 اصل مقاله (773.82 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajme.2019.16171.5808 | ||
| نویسندگان | ||
| Mohammad Javad Mahmoodabadi* 1؛ Milad Taherkhorsandi2 | ||
| 1Department of Mechanical Engineering, Sirjan University of Technology, Sirjan, Iran. | ||
| 2Department of Mechanical Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA. | ||
| چکیده | ||
| This paper is concerned with fuzzy tracking control optimized via multi-objective particle swarm optimization for stable walking of biped robots. To present an optimal control approach, multi-objective particle swarm optimization is used to design the parameters of the control method in comparison to three effectual multi-objective optimization algorithms in the literature. In particle swarm optimization, a dynamic elimination technique is utilized as a novel approach to prune the archive effectively. Moreover, a turbulence operator is used to skip the local optima and the personal best position of each particle is determined by making use of the Sigma method. Normalized summation of angles errors and normalized summation of control efforts are two conflicting objective functions addressed by dint of multi-objective optimization algorithms in the present investigation. By contrasting the Pareto front of multi-objective particle swarm optimization with the Pareto fronts of other methods, it is illustrated that multi-objective particle swarm optimization performs with high accuracy, convergence and diversity of solutions in the design of fuzzy tracking control for nonlinear dynamics of biped robots. Finally, the proper performance of the proposed controller is demonstrated by the results presenting an appropriate tracking system and optimal control inputs. Indeed, the appropriate tracking system and optimal control inputs prove the efficiency of optimal fuzzy tracking control in dealing with the nonlinear dynamics of biped robots. | ||
| کلیدواژه‌ها | ||
| Fuzzy Tracking Control؛ Multi-objective optimization؛ Particle swarm optimization؛ Genetic algorithm optimization؛ Biped robots | ||
| مراجع | ||
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