contributor author | Sardahi, Yousef | |
contributor author | Sun, Jian-Qiao | |
date accessioned | 2017-11-25T07:20:37Z | |
date available | 2017-11-25T07:20:37Z | |
date copyright | 2016/26/9 | |
date issued | 2017 | |
identifier issn | 0022-0434 | |
identifier other | ds_139_01_014501.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4236570 | |
description abstract | This 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Many-Objective Optimal Design of Sliding Mode Controls | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 1 | |
journal title | Journal of Dynamic Systems, Measurement, and Control | |
identifier doi | 10.1115/1.4034421 | |
journal fristpage | 14501 | |
journal lastpage | 014501-4 | |
tree | Journal of Dynamic Systems, Measurement, and Control:;2017:;volume( 139 ):;issue: 001 | |
contenttype | Fulltext | |