Direct control design in sampled-data uncertain systems

Yaniv, Oded; Chait, Yossi

doi:10.1016/0005-1098(93)90129-h

Cited by 19 publications

(23 citation statements)

References 10 publications

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“…In the last example, the computational superiority of the proposed method is shown by comparison with existing algorithms the number of floating point operations, flops, required for generating QFT bounds. Therefore, from (20), the solution set for the bivariate polynomial inequality corresponding to the edge E 1 is F = {g: g≥ 62.9952}. The solution sets for the remaining 12 bivariate polynomial inequalities corresponding to the 12 edges of the three-dimensional box B can be computed in the same manner.…”

Section: Illustrative Examplesmentioning

confidence: 99%

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Generation of Exact QFT Bounds for Plants With Affinely Dependent Uncertainties

Yang¹

2007

Asian Journal of Control

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This paper presents an efficient method for the generation of exact QFT bounds for robust sensitivity reduction and gain‐phase margin specifications for plants with affinely dependent uncertainties. It is shown that, for a plant with m affinely dependent uncertainties, the exact QFT bounds for robust sensitivity reduction and gain‐phase margin specifications at a given frequency and controller phase can be computed by solving m2m‐1 bivariate polynomial inequalities corresponding to the edges of the parameter domain box. Moreover, the solution set for each bivariate polynomial inequality can be computed by solving for the real roots of one fourth‐order and six second‐order polynomials. This avoids the unfavorable trade‐off between the computational burden and the accuracy of QFT bounds that has arisen in the application of many existing QFT bound generation algorithms. Numerical examples are given to illustrate the proposed method and its computational superiority.

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Section: Illustrative Examplesmentioning

confidence: 99%

“…However, these geometry based algorithms are inefficient. Recently, more efficient algorithms based on quadratic inequalities have been proposed [6,7,20]. These algorithms solve quadratic inequalities generated from the plant template of the plant to compute QFT bounds at a fixed frequency and controller phase.…”

Section: Introductionmentioning

confidence: 99%

Generation of Exact QFT Bounds for Plants With Affinely Dependent Uncertainties

Yang¹

2007

Asian Journal of Control

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“…For a rigorous extension of the QFT technique to sampled data systems see Yaniv and Chait (1993), whose technique includes algorithms to achieve closed loop specs on the sampled plant output, as well as on the continuous plant output.…”

Section: Notes and Referencesmentioning

confidence: 99%

Quantitative Feedback Design of Linear and Nonlinear Control Systems

Yaniv

1999

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152

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“…The plant can be unstable (see Horowitz and Sidi 1972) or non-minimum-phas e (NMP) (see Sidi 1976, Horowitz andSidi 1978) and can be embedded in a sampled feedback system (see Sidi 1977, Horowitz and Liao 1986, Yaniv and Chait 1993 (1). d…s † is the disturbance function shown in ®gure 1.…”

Section: The Qft Design Techniquementioning

confidence: 99%

A combined QFT/H ∞ design technique for TDOF uncertain feedback systems

Sidi¹

2002

International Journal of Control

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A new way of incorporating QFT principles into H 1 -control design techniques for solving the two-degrees of freedom feedback problem with highly uncertain plants is developed. The proposed practical design approach consists of two stages. In the ®rst stage, the robustness problem, due to plant uncertainties, is solved by H 1 -norm optimization. In this stage, the controller inside the loop (the ®rst degree of freedom) is designed, with the ultimate goal of minimizing the cost of feedback. Minimization of the sensor white noise ampli®cation at the input to the plant is also performed using QFT principles. In the second stage of the design, the pre®lter outside the loop (the second degree of freedom), is used to achieve the tracking speci®cations by conventional classical control theory, as practiced by the QFT design procedure. The combined QFT=H 1 design procedure for single input±single output (SISO) feedback systems is directly applicable to multi input±multi output (MIMO) feedback uncertain systems. The e ciency of the proposed technique is demonstrated with SISO and MIMO design examples for higly uncertain plants.

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Direct control design in sampled-data uncertain systems

Cited by 19 publications

References 10 publications

Generation of Exact QFT Bounds for Plants With Affinely Dependent Uncertainties

Generation of Exact QFT Bounds for Plants With Affinely Dependent Uncertainties

Quantitative Feedback Design of Linear and Nonlinear Control Systems

A combined QFT/H ∞ design technique for TDOF uncertain feedback systems

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