Low-Order Robust Decentralized Controller Design for a HVDC Power Link: A Combined Riccati - Genetic Algorithms Approach

Farag, A.; Werner, Herbert

doi:10.1016/s1474-6670(17)31687-7

Cited by 2 publications

(4 citation statements)

References 7 publications

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“…An approach similar to that used in [25] but with improved efficiency and applicable to a variety of design techniques was proposed in [10] and [9]. To outline the idea, we consider again the LMI condition (2), which represents a necessary and sufficient condition for the H ∞ norm of (1) to be less than γ .…”

Section: A Hybrid Evolutionary-algebraic Algorithmmentioning

confidence: 99%

“…, τ n ). Note that (9) is an LMI in P, Λ and T , thus the analysis problem of finding an upper bound on the worst case (over ∆ ∈ ) H 2 norm can be solved by solving the LMI problem min P,Λ,T trace B T 2 P + C T 1 ΛC 1 B 2 (10) subject to (9) ,…”

Section: Robust H 2 Design: Control Of a Three-mass-spring Systemmentioning

confidence: 99%

“…On the other hand, when turning to the synthesis problem of finding a controller K(s) that minimizes an upper bound on the worst-case H 2 norm, the system matrices in (9) represent the closed-loop system and depend on controller variables; the condition (9) is nonlinear in these variables and the controller parameters.…”

Section: Robust H 2 Design: Control Of a Three-mass-spring Systemmentioning

confidence: 99%

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A Hybrid Evolutionary-Algebraic Approach to Optimal and Robust Controller Design (Hybride evolutionär-algebraische Verfahren für den Entwurf optimaler und robuster Regler)

Werner¹,

Farag²

2005

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Dedicated to Prof. Dr.-Ing. Heinz Unbehauen at the occasion of his 70th birthday Modern control techniques -such as H 2 or H ∞ optimal controller design -offer powerful synthesis tools, provided the controller has the same order as the plant, and there are no constraints on the information structure of the feedback loop (e. g. decentralized control). If these assumptions do not hold -as is often the case in practical applications -the synthesis problem becomes non-convex and hard to solve. A frequently encountered situation is however that a synthesis problem is intractable, whereas the corresponding analysis problem is convex and easy to solve. In this case, it is often more efficient to use the easily available analysis results to guide a stochastic search for the solution, rather than to address the hard synthesis problem directly. In this paper, such an approach -based on a combination of algebraic tools from optimal control theory and evolutionary search techniques -is presented. Four benchmark problems representing ''hard" control problems are used to illustrate the approach and to compare its efficiency with that of previously published solutions.Moderne H 2 -und H ∞ -optimale Reglerentwurfsverfahren sind nur anwendbar wenn der Regler die gleiche dynamische Ordnung wie die Strecke hat, und wenn keine Beschränkungen der Reglerstruktur (wie etwa bei dezentraler Regelung) vorliegen. Sind diese Voraussetzungen nicht erfüllt -was in der Praxis oft vorkommt -dann liegt ein nicht-konvexes Entwurfsproblem vor. Häufig ist jedoch das Analyse-Problem, das einem nicht-konvexen Entwurfsproblem entspricht, konvex und kann mit relativ geringem Rechenaufwand gelöst werden. In solchen Fällen ist es oft effizienter, Lösungen dieser Analyse-Probleme für stochastische Suchverfahren zu verwenden, als das nicht-konvexe Entwurfsproblem direkt zu lösen. In der vorliegenden Arbeit wird ein auf dieser Idee beruhender hybrider evolutionär-algebraischer Ansatz vorgestellt, der Werkzeuge aus der Theorie der optimalen Regelung kombiniert mit evolutionären Suchstrategien. Vier Benchmark-Probleme illustrieren die Vielseitigkeit und Effizienz des vorgeschlagenen Verfahrens.

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Section: A Hybrid Evolutionary-algebraic Algorithmmentioning

confidence: 99%

Section: Robust H 2 Design: Control Of a Three-mass-spring Systemmentioning

confidence: 99%

Section: Robust H 2 Design: Control Of a Three-mass-spring Systemmentioning

confidence: 99%

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A Hybrid Evolutionary-Algebraic Approach to Optimal and Robust Controller Design (Hybride evolutionär-algebraische Verfahren für den Entwurf optimaler und robuster Regler)

Werner¹,

Farag²

2005

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“…The proposed technique is considered a valuable motivation for future research. While the Riccati equation in H1 controllers has been solved using various artificial intelligence algorithms [29,30], this is the first time that the GWO has been used for this purpose.…”

Section: Introductionmentioning

confidence: 99%

A robust optimal control by grey wolf optimizer for underwater vehicle-manipulator system

Dai,

Wang,

Shen

2023

PLoS ONE

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Underwater vehicle-manipulator system (UVMS) is a commonly used underwater operating equipment. Its control scheme has been the focus of control researchers, as it operates in the presence of lumped disturbances, including modelling uncertainties and water disturbances. To address the nonlinear control problem of the UVMS, we propose a robust optimal control approach optimized using grey wolf optimizer (GWO). In this scheme, the nonlinear dynamic model of UVMS is deduced to a linear state-space model in the case of the lumped disturbances. Then, the GWO algorithm is used to optimize the Riccati equation parameters of the H∞ controller in order to achieve the H∞ performance criterion, such as stability and disturbance rejection. The optimization is performed by evaluating the performance of the closed-loop UVMS in real-time comparison with the popular artificial intelligent algorithms, such as as ant colony algorithm (ACO), genetic algorithm (GA), and particle swarm optimization (PSO), using feedback control from the physical hardware-in-the-loop UVMS platform. This scheme can result in improved H∞ control system performance, and it is able to ensure that UVMS has strong robustness to these lumped disturbances. Last, the validity of the proposed scheme can be established, and its performance in overcoming modeling uncertainties and external disturbances can be observed and analyzed by performing the hardware-in-the-loop experiments.

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Low-Order Robust Decentralized Controller Design for a HVDC Power Link: A Combined Riccati - Genetic Algorithms Approach

Cited by 2 publications

References 7 publications

A Hybrid Evolutionary-Algebraic Approach to Optimal and Robust Controller Design (Hybride evolutionär-algebraische Verfahren für den Entwurf optimaler und robuster Regler)

A Hybrid Evolutionary-Algebraic Approach to Optimal and Robust Controller Design (Hybride evolutionär-algebraische Verfahren für den Entwurf optimaler und robuster Regler)

A robust optimal control by grey wolf optimizer for underwater vehicle-manipulator system

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