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contributor authorSardahi, Yousef
contributor authorSun, Jian-Qiao
date accessioned2017-11-25T07:20:37Z
date available2017-11-25T07:20:37Z
date copyright2016/26/9
date issued2017
identifier issn0022-0434
identifier otherds_139_01_014501.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4236570
description abstractThis paper presents a many-objective optimal (MOO) control design of an adaptive and robust sliding mode control (SMC). A second-order system is used as an example to demonstrate the design method. The robustness of the closed-loop system in terms of stability and disturbance rejection are explicitly considered in the optimal design, in addition to the typical time-domain performance specifications such as the rise time, tracking error, and control effort. The genetic algorithm is used to solve for the many-objective optimization problem (MOOP). The optimal solutions known as the Pareto set and the corresponding objective functions known as the Pareto front are presented. To assist the decision-maker to choose from the solution set, we present a post-processing algorithm that operates on the Pareto front. Numerical simulations show that the proposed many-objective optimal control design and the post-processing algorithm are promising.
publisherThe American Society of Mechanical Engineers (ASME)
titleMany-Objective Optimal Design of Sliding Mode Controls
typeJournal Paper
journal volume139
journal issue1
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.4034421
journal fristpage14501
journal lastpage014501-4
treeJournal of Dynamic Systems, Measurement, and Control:;2017:;volume( 139 ):;issue: 001
contenttypeFulltext


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