A Robust Controller Based on Fractional Structure for Mimo Plant With Multiple Delays

Sedraoui, Moussa; Gherbi, Sofiane; Abdelmalek, Salem

doi:10.2316/journal.201.2012.2.201-2216

Cited by 9 publications

(13 citation statements)

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“…2, two sensitivity functions can be determined when the robustified GPC controller is used. We get:(a) Sensitivity function [19,20]:…”

Section: Youla Parameterizationmentioning

confidence: 99%

“…In robust control theory, the optimal trade-off robustness can be formulated as the following weighted-mixed-sensitivity problem [19,20]:…”

Section: Youla Parameterizationmentioning

confidence: 99%

“…performance level, W 1 and W 3 denote, respectively, the weighting functions that penalize the control error eðtÞ and the process output yðtÞ [19,20]. Practical considerations such as rate saturation, pure time delays and unmodeled dynamics can be included in those above weighting functions.…”

Section: Youla Parameterizationmentioning

confidence: 99%

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Robustified GPC controller based on H ∞ robust control for an hydraulic actuator

Aidoud¹,

Sedraoui

Lachouri³

et al. 2015

J Braz. Soc. Mech. Sci. Eng.

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This paper proposes the robustification method of primary generalized predictive control GPC for a hydraulic actuator, which is previously modeled by an uncertain plant. Three-step procedures should be followed for robustification: First, the primary GPC controller based on nominal plant is designed to ensure a better tracking dynamic of the closed-loop system. Second, the Q-parameter transfer function is determined from solving the weighted-mixed sensitivity problem using the two Riccati equations where the uncertainty plant and neglected dynamics are taken into account. Finally, the Youla parameterization combines the primary GPC controller and Q-parameter to design the robustified GPC controller which enhances the trade-off robustness of primary GPC controller without changing its better tracking dynamic. To validate the effectiveness of the proposed robustification, the hydraulic actuator, which presents a realistic process, is controlled by both primary and robustified GPC controllers where their simulation results are compared in time and frequency domains by those given by the H ? controller.

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“…2, two sensitivity functions can be determined when the robustified GPC controller is used. We get:(a) Sensitivity function [19,20]:…”

Section: Youla Parameterizationmentioning

confidence: 99%

“…In robust control theory, the optimal trade-off robustness can be formulated as the following weighted-mixed-sensitivity problem [19,20]:…”

Section: Youla Parameterizationmentioning

confidence: 99%

See 1 more Smart Citation

Robustified GPC controller based on H ∞ robust control for an hydraulic actuator

Aidoud¹,

Sedraoui

Lachouri³

et al. 2015

J Braz. Soc. Mech. Sci. Eng.

Self Cite

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show abstract

“…Furthermore, conventional controller-based PI controllers are only able to guarantee robustness with respect to small parameters variations. Consequently, the wind energy systems require a robust controller (Belfedal et al, 2010; Sedraoui et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Secondly, the optimal solution is not guaranteed due to the higher number of the specifications to be fulfilled. Finally, local minima or the global optimal are not ensured due to the ill-initializing solution, which must be previously fixed by the user after several trails (Sedraoui et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Robustified fractional-order controller based on adjustable fractional weights for a doubly fed induction generator

Sedraoui

Amieur

Bouiadjra

et al. 2016

Transactions of the Institute of Measurement and Control

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In this paper, a robustification method of the primary fractional controller is proposed. This novel method uses the adjustable fractional weights on the H∞ mixed-sensitivity problem. It can achieve an enhancement in both nominal performance and robust stability margins for the uncertain plants while respecting the frequency-domain constraints, such as the tracking of the set-point references, load disturbance attenuation and measurement noise suppression. The proposed robustification holds two steps; in the first step, a primary fractional controller is designed from solving the H∞ mixed-sensitivity problem that uses fixed-integer weights. In the second step, the robustified fractional controller with adjustable fractional weights is designed in order to guarantee a good compromise between the nominal performance and the robust stability not only for the nominal plant, but also for all set of the neighbouring plants. The proposed robustified fractional controller is used to control the doubly fed induction generator. Its dynamic is modelled by the unstructured output-multiplicative uncertain plant. Simulation results given by both primary and robustified fractional controllers are compared in time and frequency domains with those given by the conventional integer H∞ controller in order to validate the effectiveness of the proposed method.

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Synthesis of fixed-structure robust controllers using a constrained particle swarm optimizer with cyclic neighborhood topology

Maruta

Kim

Song

et al. 2013

Expert Systems with Applications

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A Robust Controller Based on Fractional Structure for Mimo Plant With Multiple Delays

Cited by 9 publications

References 0 publications

Robustified GPC controller based on H ∞ robust control for an hydraulic actuator

Robustified GPC controller based on H ∞ robust control for an hydraulic actuator

Robustified fractional-order controller based on adjustable fractional weights for a doubly fed induction generator

Synthesis of fixed-structure robust controllers using a constrained particle swarm optimizer with cyclic neighborhood topology

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