Nonlinear predictive control of a mobile robot: a solution using metaheuristcs
| Autor: | Billel Bouchemal, Halim Merabti, Khaled Belarbi |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
0209 industrial biotechnology
Engineering Mathematical optimization Optimization problem business.industry Ant colony optimization algorithms MathematicsofComputing_NUMERICALANALYSIS General Engineering Particle swarm optimization Mobile robot 02 engineering and technology Model predictive control 020901 industrial engineering & automation Obstacle avoidance 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business Heuristics Metaheuristic |
| Zdroj: | Journal of the Chinese Institute of Engineers. 39:282-290 |
| ISSN: | 2158-7299 0253-3839 |
| Popis: | The basic features of model-based predictive control (MBPC) make it an interesting candidate for the control of mobile robots. However, fast solution procedures remain a challenge for nonlinear MBPC problems such as the one arising in mobile robot control. Metaheuristics are general purpose heuristics which have been successful in solving difficult optimization problems in a reasonable computation time. In this work, we present a comparison between the uses of three different heuristics, namely particle swarm optimization (PSO), ant colony optimization, and gravitational search algorithm for the solution of the nonlinear MBPC for a mobile robot tracking trajectory with dynamic obstacle avoidance. The computation times obtained show that PSO is a feasible alternative for real-time applications. The MBPC based on the PSO is applied to controlling a LEGO mobile robot with encouraged results. |
| Databáze: | OpenAIRE |
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