Multi-Objective Predictive Control : A Solution Using Metaheuristics

Autor:	Ali Mendjeli, Halim Merabti, Khaled Belarbi
Rok vydání:	2014
Předmět:	Mathematical optimization Model predictive control Optimization problem Computer science Computation Differential evolution Particle swarm optimization Heuristics Metaheuristic Multi-objective optimization
Zdroj:	International Journal of Computer Science and Information Technology. 6:147-156
ISSN:	0975-3826 0975-4660
Popis:	The application of multi objective model predictive control approaches is significantly limited with computation time associated with optimization algorithms. Metaheuristics are general purpose heuristics that have been successfully used in solving difficult optimization problems in a reasonable computation time. In this work , we use and compare two multi objective metaheuristics, Multi-Objective Particle swarm Optimization, MOPSO, and Multi-Objective Gravitational Search Algorithm, MOGSA, to generate a set of approximately Pareto-optimal solutions in a single run. Two examples are studied, a nonlinear system consisting of two mobile robots tracking trajectories and avoiding obstacles and a linear multi variable system. The computation times and the quality of the solution in terms of the smoothness of the control signals and precision of tracking show that MOPSO can be an alternative for real time applications.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e180669ca80371d0287511f4bd9e1b32 https://doi.org/10.5121/ijcsit.2014.6612 Zobrazit plný text záznamu