Conference Record of the 1990 IEEE Industry Applications Society Annual Meeting
DOI: 10.1109/ias.1990.152222
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Robustness enhancement of DC drives with a smooth optimal sliding mode control

Abstract: Although sliding mode control systems are qualitatively well known for possessing robust performance, the robustness of an electrical drive system against external disturbances of a system designed in this way, especially a step load application, may vary due to certain factors such as an integral control action and smooth control algorithms which are often incorporated in a practical system. A quantitative analysis of the robustness of a dc drive control system is attempted in this paper. The time domain expr… Show more

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Cited by 8 publications
(8 citation statements)
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“…Conventional control techniques are fixed to construction and parameter of system [4,5]. The optimization and tuning of this controller is difficult, especially due to parameter changes abnormal operation conditions under and varying load conditions.…”
Section: Introductionmentioning
confidence: 99%
“…Conventional control techniques are fixed to construction and parameter of system [4,5]. The optimization and tuning of this controller is difficult, especially due to parameter changes abnormal operation conditions under and varying load conditions.…”
Section: Introductionmentioning
confidence: 99%
“…Conventional control strategies are fixed structure and fixed parameter design [ 4,5]. Hence the tuning and optimization of these controllers are a challenging, particularly under varying load conditions, parameter changes, and abnormal modes of operation.…”
Section: Introductionmentioning
confidence: 99%
“…The dynamics of such a platform are highly nonlinear, and the difficulty of the problem is compounded by the need to operate at different gyroscope flywheel speeds and under different payload conditions. For control of such systems, traditional techniques which are commonly used include optimal control (Zhang and Barton 1991), conventional variable-structure control (Hashimoto 1987) and linear adaptive control (Sepe and Lang 1991). However, most of these lose effectiveness when the servomechanisms have fairly severe nonlinear dynamics and, more recently, there has been increasing research and development work to address this problem with the design of control systems, incorporating neural networks.…”
Section: Introductionmentioning
confidence: 99%