1995
DOI: 10.1016/0098-1354(94)00044-o
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A multiobjective design algorithm: Application to the design of siso control systems

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Cited by 21 publications
(8 citation statements)
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“…Though the technique seems to have low sensitivity to the starting values used for the optimization, the final approach includes a sort of trial and error until the most favorable values are selected. An alternative as been the use of a multiobjective programming approach aimed at finding Pareto optimal solutions characterized as a solution set in which any improvement in one performance criterion necessarily implies the degradation in some other. This last technique has to also solve a number of optimization problems, in an iterative fashion, to adjust a controller having a fixed predetermined structure.…”
Section: Design-and-tuning Problem Formulationmentioning
confidence: 99%
“…Though the technique seems to have low sensitivity to the starting values used for the optimization, the final approach includes a sort of trial and error until the most favorable values are selected. An alternative as been the use of a multiobjective programming approach aimed at finding Pareto optimal solutions characterized as a solution set in which any improvement in one performance criterion necessarily implies the degradation in some other. This last technique has to also solve a number of optimization problems, in an iterative fashion, to adjust a controller having a fixed predetermined structure.…”
Section: Design-and-tuning Problem Formulationmentioning
confidence: 99%
“…En este sentido, la optimización multiobjetivo de controladores PID permanece como un tema abierto de investigación, a pesar de que ha sido estudiado por varias décadas: en [4] se utiliza un tipo de optimización multiobjetivo para sintonizar controladores PID en un proceso de moldeo por inyección de plástico; en [5], un algoritmo basado en una serie de optimizaciones es propuesto para encontrar los parámetros óptimos de un controlador PID que toma en cuenta varios criterios de rendimiento.…”
Section: Introductionunclassified
“…Transfer function based controllers were tuned by Abbas & Sawyer (1995) considering the underlying ideas of the multiple criteria decision analysis theory. The tuning goals were indicators such as the overshoot, rise time, settling time, steadystate error and the maximum output values.…”
Section: Tuning Techniques Based On the Multi-objective Optimization mentioning
confidence: 99%
“…Then, several tuning methods use a closed-loop simulation to calculate the output trajectories and evaluate the tuning objectives. Examples of these objectives are the overshoot, the rise time, and settling time of the closed-loop response (Abbas & Sawyer, 1995;Han, Zhao & Qian,, 2006;Reynoso-Meza et al, 2013;Suzuki et al, 2012;van der Lee, Svrcek & Young, 2008). The tuning objective can also be the IAE or the ISE between the output trajectory and an output constraint envelope with variable height (Ali & Zafiriou, 1993b;Al-Ghazzawi et al, 2001).…”
Section: Introductionmentioning
confidence: 99%