A Digital H∞ Controller for a Flexible Transmission System

Jones, N. W.; Limebeer, D.J.N.

doi:10.1016/s0947-3580(95)70016-4

Cited by 13 publications

(4 citation statements)

References 7 publications

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“…Some of them are published in the special issue dedicated to the benchmark and the others ulteriorly with new progress in robust control approaches. At present, the following solutions can be found in the literature: four H ∞ solutions (Jones and Limebeer 1995; Kwakernaak 1995; Walker 1995; Ferreres and Fromion 1999), two controllers based on quantitative feedback theory (QFT) (Kidron and Yaniv 1995; Nordin and Gutman 1995), three controllers using pole placement with sensitivity shaping (Landau et al 1995a; Landau and Karimi 1998; Langer and Constantinescu 1999), one generalized predictive controller (GPC) (Decker et al 1995), one fractional order controller by CRONE control (Oustaloup et al 1995) and one model-free approach based on iterative feedback tuning (IFT) (Hjalmarsson et al 1995). Although all of the controllers stabilize the system and achieve good performance, only two controllers meet all of the required specifications for all loadings with relatively high-order controllers.…”

Section: Introductionmentioning

confidence: 99%

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A solution to the flexible transmission benchmark by convex optimization

Galdos

Karimi

2011

Journal of Vibration and Control

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The flexible transmission benchmark was proposed in the European Journal of Control to evaluate some robust digital control approaches in 1995. With progress in convex optimization algorithms new methods for robust controller design are developed. A recently proposed fixed-order robust controller design method is applied to this benchmark problem and the results are compared with the existing results. The proposed method is based on open-loop shaping with frequency-domain constraints on the closed-loop sensitivity functions in the Nyquist diagram. The method needs only the frequency response of the model and can consider the multimodel uncertainty. A controller is designed by a convex optimization algorithm that meets all the required performance specifications for the benchmark with the lowest controller complexity.

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Section: Introductionmentioning

confidence: 99%

“…98.61 14 (Kidron and Yaniv, 1995) 97.71 9 (Hjalmarsson et al, 1995) 97.48 9 (Landau et al, 1995a) 97.12 12 (Jones and Limebeer, 1995) 94.38 35 (Decker et al, 1995) 91.82 16 (Walker, 1995) 72.35 15…”

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confidence: 99%

A solution to the flexible transmission benchmark by convex optimization

Galdos

Karimi

2011

Journal of Vibration and Control

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“…This system has been the subject of a benchmark on robust digital control at the European Control Conference in Rome 1995 [1]. Several robust control design methods have been considered and examined on the real system, including control [2]- [4], QFT [5], [6], CRONE [7], GPC [8], pole placement with sensitivity function shaping [9], [10] and direct minimization of a performance with a model free approach [11]. The robust stability of the system has been assured by all of the robust controller proposed, but a very high-performance fixed parameter controller for all of the loadings could not be achieved.…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive control of a flexible transmission system using multiple models

Karimi

Landau

2000

IEEE Trans. Contr. Syst. Technol.

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Abstract-An application of the multiple models adaptive control based on switching and tuning to a flexible transmission system will be presented. This approach has been considered in order to assure high control performance in the presence of large load variation on the system. The advantages of the multiple models adaptive control system with respect to the classical adaptive control will be illustrated via the experimental results. It will also be shown that the robustness of the adaptive control system can be improved with the appropriate shaping of a sensitivity function. The use of a recently developed parameter estimation algorithm based on the minimization of the closed-loop output error in the multiple models scheme will also improve the performance of the system in the tuning phase and will make the adaptation algorithm insensitive to unmodeled output disturbances.

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“…Although loopshaping H, techniques have been especially applied to the benchmark problem [5], [15], classical H , control has not been applied to it. Loopshaping H, techniques are used to shape the open-loop system according to classical loopshaping rules [2], and then to apply a robust stabilization procedure to the shaped system [12].…”

Section: Introductionmentioning

confidence: 99%

H. control of a flexible transmission system

Amirifar

Sadati

Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of The

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An application of a continuous-time H , control to a flexible transmission system is presented. This approach has been proposed in order to assure high control performance in the presence of large load variation on the system. In this approach, the loading variations are considered as the multiplicative perturbation of the nominal plant. The desired specifications are enforced in the H , problem as the constraints on weighting functions. After an initial design procedure, the parameters of weighting functions, in order to obtain the desired performances, are tuned and then the final weighting functions are derived. The simulation results for three different loadings are given and compared.

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A Digital H∞ Controller for a Flexible Transmission System

Cited by 13 publications

References 7 publications

A solution to the flexible transmission benchmark by convex optimization

A solution to the flexible transmission benchmark by convex optimization

Robust adaptive control of a flexible transmission system using multiple models

H. control of a flexible transmission system

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