Journal of Global Optimization
Combining convergence and diversity in evolutionary multiobjective optimization
Evolutionary Computation
Robust Control Design with MATLAB® (Advanced Textbooks in Control and Signal Processing)
Robust Control Design with MATLAB® (Advanced Textbooks in Control and Signal Processing)
Evolutionary Computation
Information Sciences: an International Journal
Well-distributed Pareto front by using the ∉-MOGA evolutionary algorithm
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Multiobjective evolutionary algorithms for multivariable PI controller design
Expert Systems with Applications: An International Journal
Comparison of design concepts in multi-criteria decision-making using level diagrams
Information Sciences: an International Journal
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Controller design has evolved to a multiobjective task, i.e., today is necessary to take into account, besides any performance requirement, robustness requisites, frequency domain specifications and uncertain model parameters in the design process. The designer (control engineer), as Decision Maker, has to select the best choice according to his preferences and the trade-off he wants to achieve between conflicting objectives. In this work, a new multiobjective optimization approach using Differential Evolution (DE) algorithm is presented for the design of (but not limited to) Laplace domain controllers. The methodology is used to propose a set of solutions for an engineering control benchmark, all of them non-dominated and pareto-optimal. The obtained results shows the viability of this approach to give a higher degree of flexibility to the control engineer at the decision making stage.