A simple first order compensator for brushless direct current drive based position control system

Ganesh, C.; Patnaik, S. K.

doi:10.1177/1077546313486276

Cited by 7 publications

(2 citation statements)

References 18 publications

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“…The dynamic response of the BLDC drive system was enhanced by employing a simple first-order compensator (Shanmugasundram et al, 2008; Ganesh et al, 2009; Ganesh and Patnaik, 2015). The result was found to be superior to what a PID controller would have produced.…”

Section: Introductionmentioning

confidence: 99%

An effective controller design strategy for higher order systems

Chandramouleeswaran,

Deivanayagam Pillai,

Ramasamy

et al. 2023

Journal of Vibration and Control

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The recent methods that guarantee the stability of the reduced-order models are Mihailov stability, improved Pade approximation and truncation, improved generalized pole clustering, moment matching and salp swarm optimization. Further, these methods could overcome the limitations such as non-uniqueness, pole clustering, gain adjustment and difficulty to maintain the dominant roots in the lower order system for non-minimum higher order plants. This research emphasizes the design of the proposed compensating algorithm by using an additional open loop zero for the stable reduced-order models of large-scale single-input single-output linear time-invariant continuous time systems. The results of the proposed algorithm are compared with the existing compensating methods and the design is validated and illustrated numerically.

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Section: Introductionmentioning

confidence: 99%

An effective controller design strategy for higher order systems

Chandramouleeswaran,

Deivanayagam Pillai,

Ramasamy

et al. 2023

Journal of Vibration and Control

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“…Classic control theory and linear system theory are well understood but they require extensive knowledge about control systems, motor parameters, and load torque variations to develop a welldesigned controller (Acarnley and Watson, 2006). A first order compensated BLDC drive is proposed in Gansh and Patnaik (2013) to achieve effective position control. The model reference adaptive control in Crnosija et al (2002) is based on the back stepping technique.…”

Section: Introductionmentioning

confidence: 99%

Robust flatness-based tracking control for brushless direct current motor drives

Yousef

Soliman

2014

Journal of Vibration and Control

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The trajectory tracking problem for nonlinear brushless direct current drive is solved by combined robust and flatness state feedback control. The drive's nonlinear model is shown to have the flatness property. The proposed controller consists of two parts, linear and nonlinear. Linear matrix inequalities (LMI) optimization is used to design the linear part which achieves robust stability against system uncertainties, desired swiftness, and guaranteed cost performance. System uncertainty due to changes in the drive's parameters is represented with a norm-bounded structure. The nonlinear control part solves the motion planning problem through flatness which avoids integrating the differential equations of the dynamics. The main advantages of this technique are that the LMI algorithm includes an optimal part to preclude high control efforts, and the control burden is heavily placed on the linear part to achieve flatness properties. In some systems, in which flatness cannot be achieved, adding robust linear control can overcome or alleviate this problem.

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