A new optimal sliding mode controller with adjustable gains based on Bolza-Meyer criterion for vibration control

被引:12
作者
Phu Do Xuan [1 ]
Mien Van [2 ]
Tu Phan Huu Thanh [1 ]
Nguyen Ngoc Phi [3 ]
Choi, Seung-Bok [4 ]
机构
[1] Vietnamese German Univ, Dept Mechatron & Sensor Syst Technol, Thu Dau Mot, Binh Duong, Vietnam
[2] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT7 1NN, Antrim, North Ireland
[3] Sejong Univ, Dept Aerosp Engn, Seoul, South Korea
[4] Inha Univ, Dept Mech Engn, Smart Struct & Syst Lab, Incheon 22212, South Korea
关键词
Optimal control; Optimal sliding mode control; Gain adjustability; Bolza-meyer criterion; Faster convergence; Cost function; Hamiltonian function; NEURAL-NETWORK; TRACKING; SYSTEM;
D O I
10.1016/j.jsv.2020.115542
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In this study, a new optimal control law associated with sliding mode control is developed based on basis of the Bolza-Meyer criterion. The salient characteristic of the proposed controller is to have gains adjustability, where the gain values can be larger than one. This leads to enhancing control system performances with a given cost function. It should be pointed out that conventional optimal controllers usually have constant gains of one or less than one, and hence the control system performances such as the requirement on convergence speed may not be satisfactory. After formulating the proposed optimal control law for polynomial time-varying control systems, computer simulations are carried out to validate the benefits of the proposed approach. Firstly, as an illustrative example, three crucial index values including control gain index, main input control index and the state index are investigated. Secondly, the proposed controller is applied to a vehicle seat suspension system with magneto-rheological damper to evaluate vibration control performances. In simulation studies, a comparison between the proposed approach and a state-of-the-art optimal controller is undertaken to demonstrate additional benefits such as less power and faster convergence of the proposed optimal controller. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:19
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