Journal
APPLIED SOFT COMPUTING
Volume 93, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2020.106342
Keywords
Meta-heuristics; Multi-objective optimization; Controller tuning; Intelligent control
Categories
Funding
- Consejo Nacional de Ciencia y Tecnologia (CONACyT)
- CONACyT [220522]
- Secretaria de Investigacion y Posgrado (SIP) [SIP-20200150]
Ask authors/readers for more resources
Multi-objective optimization has been adopted in many engineering problems where a set of requirements must be met to generate successful applications. Among them, there are the tuning problems from control engineering, which are focused on the correct setting of the controller parameters to properly govern complex dynamic systems to satisfy desired behaviors such as high accuracy, efficient energy consumption, low cost, among others. These requirements are stated in a multi-objective optimization problem to find the most suitable controller parameters. Nevertheless, these parameters are tough to find because of the conflicting control performance requirements (i.e., a requirement cannot be met without harming the others). Hence, the use of techniques from computational intelligence and soft computing is necessary to solve multi-objective problems and handle the trade-offs among control performance objectives. Meta-heuristics have shown to obtain outstanding results when solving complex multi-objective problems at a reasonable computational cost. In this survey, the literature related to the use of multi-objective meta-heuristics in intelligent control focused on the controller tuning problem is reviewed and discussed. (C) 2020 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available