Application of Multiple-Model Adaptive Control Strategy for Robust Damping of Interarea Oscillations in Power System

Chaudhuri, Balarko; Majumder, Ritwik; Pal, Bikash C.

doi:10.1109/tcst.2004.833409

Cited by 79 publications

(39 citation statements)

References 13 publications

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“…3. System behavior with the proposed self-tuning control (STC, in black) is almost identical to that using multi-model adaptive control (MMAC, in gray) [19] …”

Section: Real-time Simulationmentioning

confidence: 95%

Self-tuning flexible ac transmission system controllers for power oscillation damping: a case study in real time

Domahidi

Chaudhuri

Korba

et al. 2009

IET Gener. Transm. Distrib.

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“…3. System behavior with the proposed self-tuning control (STC, in black) is almost identical to that using multi-model adaptive control (MMAC, in gray) [19] …”

Section: Real-time Simulationmentioning

confidence: 95%

Self-tuning flexible ac transmission system controllers for power oscillation damping: a case study in real time

Domahidi

Chaudhuri

Korba

et al. 2009

IET Gener. Transm. Distrib.

Self Cite

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“…According to dynamic models of control valves (12), the proportional-integral-derivative (PID) controller parameters are acquired as follows: …”

Section: Augmented Plant Modelmentioning

confidence: 99%

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

Wang

Chai

et al. 2013

IEEE Trans. Contr. Syst. Technol.

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Abstract-For the forced-circulation evaporation process of alumina production, the control objectives include maintaining the liquid level and fast tracking of the product density with respect to its setpoint. However, with the strong coupling between the level control and product density control loops and the process exhibits strong nonlinearities, conventional control strategies, such as proportional-integral-derivative and other linear control design, cannot achieve satisfactory control performance and meet production demands. By augmenting the forced-circulation evaporation system model with dynamics of its operating valves, a nonlinear adaptive decoupling switching control strategy is proposed. This control strategy includes a linear adaptive decoupling controller, a neural-network-based nonlinear adaptive decoupling controller, and a switching mechanism. The linear adaptive decoupling controller is used to reduce the coupling between the two control loops. The neural-network-based nonlinear adaptive decoupling controller is employed to improve the transient performance and reduce the effects of the nonlinearities on the system, and the switching mechanism is introduced to guarantee the input-output stability of the closed-loop system. Simulation results show that the proposed method can decouple the loops effectively for the forced-circulation evaporation system and thus improve the evaporation efficiency.

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“…Remark 1: Without any reset, the time-derivative of the Lyapunov function is given by (12), such that reset makes V (t) decay faster.…”

Section: B Ideal Estimator Reset Criterionmentioning

confidence: 99%

“…Recently, MMAC ideas have been extended to nonlinear systems in [7], [8], [9], [10], [11] and [12]. The different approaches reported above are typically distinguished either by the type of adaptive controller under consideration, or the resetting strategy and criterion applied.…”

Section: Introductionmentioning

confidence: 99%

Transient performance, estimator resetting and filtering in nonlinear multiple model adaptive backstepping control

Bakkeheim

Johansen

2006

IEE Proceedings - Control Theory and Applications

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Multiple model adaptive control (MMAC) is a well established approach for implementing adaptive systems with fast transient response. This paper considers a recently developed MMAC method based on adaptive nonlinear backstepping control where the parameter estimate may be instantaneously reset based on a criterion that requires a negative jump in the associated control Lyapunov function. Particular attention is paid to transient effects due to data filtering, which must be introduced in any practical implementation of the MMAC algorithm in order to reduce the sensitivity to noise, disturbances and model uncertainty. The main contribution of this paper is insight into the robust behavior of the adaptive system resulting from the filtering, and an investigation into the trade-offs between high transient performance and robustness to uncertainty.We also suggest data filter tuning guidelines and illustrate the results using a simulation example.

show abstract

Application of Multiple-Model Adaptive Control Strategy for Robust Damping of Interarea Oscillations in Power System

Cited by 79 publications

References 13 publications

Self-tuning flexible ac transmission system controllers for power oscillation damping: a case study in real time

Self-tuning flexible ac transmission system controllers for power oscillation damping: a case study in real time

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

Transient performance, estimator resetting and filtering in nonlinear multiple model adaptive backstepping control

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