Design of robust optimal Linear Parameter Varying (LPV) controller for DC servo system

Aydın, Yücel

doi:10.1109/icelmach.2010.5607850

Cited by 3 publications

(4 citation statements)

References 17 publications

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“…A possible example for the considered problem can be the position/velocity control of DC servo motors as popular devices that are used in aeronautics, robotics, automated manufacturing, and electric vehicles. DC servo motors can be modeled as linear systems whose parameters vary under variable load conditions or due to the change of system parameters from their initial value (for instance, the change of the armature resistance due to the change of temperature) [31], [32]. Furthermore, a pre-amplifier and a servo amplifier are used to transfer the control signal from the controller to the DC motor.…”

Section: Problem Statementmentioning

confidence: 99%

Data-Driven Fault-Tolerant Tracking Control for Linear Parameter-Varying Systems

et al. 2022

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This article proposes a data-driven passive fault-tolerant tracking controller for single-input single-output (SISO) discrete-time linear systems with slowly-varying unknown parameters in the presence of actuator faults. Initially, a parameterized controller is considered. Using the internal model principle, the controller structure is determined such that the passive-fault-tolerance and tracking objectives are achieved. The obtained fixed-structure controller is utilized for both normal and faulty conditions without using any feedback from the fault information. Thus, the controller is simple to implement and responds fast to the effects of faults. Then, using a data-driven technique and based on the input/output (I/O) data, the controller parameters are adjusted online to tackle the problem of parameter variation. A data-based constraint on the controller parameters is proposed for ensuring the stability of the closed-loop system. The proposed technique is extended to multi-input multi-output (MIMO) systems using the sequential loop closing concept and the relay auto-tuning method. Simulation results of applying the proposed controller to a direct current (DC) servo motor and a three-tank system demonstrate its effectiveness.INDEX TERMS Data-driven control, fault-tolerant control, internal model principle, linear parametervarying systems, tracking control.

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Section: Problem Statementmentioning

confidence: 99%

Data-Driven Fault-Tolerant Tracking Control for Linear Parameter-Varying Systems

et al. 2022

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“…During the last two decades, lots of results have been proposed to take account of robust problem of time‐varying systems. Referring to References 17‐27, the time‐varying system was described by LPV model. According to the convex combination, the LPV systems can be described by several polynomial systems and a time‐varying function.…”

Section: Introductionmentioning

confidence: 99%

“…According to the convex combination, the LPV systems can be described by several polynomial systems and a time‐varying function. Based on the LPV system, some control schemes have been proposed to solve stability issues of practical systems, such as mechanics 20,21 and aerospace 22,23 . In the literature, 24‐27 the Lyapunov function depended on parameters was employed to develop some criteria for designing the gain‐scheduled (GS) controller.…”

Section: Introductionmentioning

confidence: 99%

Delay‐dependentrobust control of stochastic systems with convex polynomial uncertainty

Chang

Hsu

et al. 2020

Optim Control Appl Methods

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Summary This article addresses a robust control problem of time‐varying stochastic systems with time‐delays. Through Linear Parameter Varying (LPV) modeling approach, the time‐varying parameters can be described via the convex combination. Therefore, the LPV stochastic system is interpreted by a weighting function and multiplicative noised linear systems. Furthermore, stabilization problem for the systems is investigated via Gain‐Scheduled (GS) technique to increase robustness. For the problem, some sufficient conditions are derived by Integral Lyapunov‐Krasovskii Function (ILKF) such that the conservatism caused by derivative of weighting function is ignored. Besides, an Iterative Linear Matrix Inequality algorithm is used to determine the auxiliary variable such that the problem can be solved via the convex calculation. Finally, some simulations are provided to demonstrate effectiveness and applicability of this article.

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“…Reference [6] presents the design of a robust optimal control system for a DC servo motor. The design procedure is done via a linear convex combination of all A neuro -fuzzy controller of the DC servo motor is designed in [7].The designed controller does not produce the overshoot such as PID controller, does not produce steady state error of fuzzy logic controller, and shortened about 10% of settling time.…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Experimental Investigation of Dc Servo-Motor

Elsayed

Dessouky

Attia

2014

Port-Said Engineering Research Journal

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In this paper the proportional integral derivative (PID) controller is designed and used to control the DC servo motor. The PID parameters are optimized by the trial and error method. The controller is verified on the loaded DC servo motor by SIMULINK program. The controller SIMULINK model is verified experimentally. Acceptable agreement is obtained between theoretical and experimental results. Simulation and experimental results verify the effectiveness of the PID controller of the DC servo motor.

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Design of robust optimal Linear Parameter Varying (LPV) controller for DC servo system

Cited by 3 publications

References 17 publications

Data-Driven Fault-Tolerant Tracking Control for Linear Parameter-Varying Systems

Data-Driven Fault-Tolerant Tracking Control for Linear Parameter-Varying Systems

Delay‐dependentrobust control of stochastic systems with convex polynomial uncertainty

Theoretical and Experimental Investigation of Dc Servo-Motor

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