Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Information Sciences: an International Journal
Applied Pareto multi-objective optimization by stochastic solvers
Engineering Applications of Artificial Intelligence
Non-even spread NSGA-II and its application to conflicting multi-objective compatible control
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Multiobjective evolutionary algorithms for multivariable PI controller design
Expert Systems with Applications: An International Journal
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Trends in controller design point to the integration of several objectives to achieve new performances. Moreover, it is easy to set the controller design problem as an optimization problem. Therefore, future improvements are likely to be based on the adequate formulation and resolution of the multiobjective optimization problem. The multiobjective optimization strategy called physical programming provides controller designers with a flexible tool to express design preferences with a 'physical' meaning. For each objective (settling time, overshoot, disturbance rejection, etc.) preferences are established through categories such as desirable, tolerable, unacceptable, etc. to which numerical values are assigned. The problem is normalized and converted to a single-objective optimization problem but normally it results in a multimodal problem very difficult to solve. Genetic algorithms provide an adequate solution to this type of problems and open new possibilities in controller design and tuning.