Weight selection in mixed sensitivity robust control for improving the sinusoidal tracking performance

Oloomi, Hossein M.; Shafai, B.

doi:10.1109/cdc.2003.1272577

Cited by 33 publications

(28 citation statements)

References 8 publications

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“…However, large values of m and n will affect the stability margins and unnecessarily increase the controller order. Thus, m and n should be kept as low as possible [21].…”

Section: Design Methodology Of the Weighting Functionsmentioning

confidence: 99%

“…This way, the H ∞ optimization problem can be expressed in the standard formulation [21], as shown in Figure 4. Figure 4 can be described as follows:…”

Section: H ∞ Mixed-sensitivity Problemmentioning

confidence: 99%

“…Many alternative methods can be used to obtain the generalized plant P(s) in the S/KS/T mixed-sensitivity problem [21,22]. Figure 3 shows the configuration of the generalized plant.…”

Section: H ∞ Mixed-sensitivity Problemmentioning

confidence: 99%

“…An optimal H∞ control method [19][20], where the weighting function selection is expressed as an optimization problem [21,22], is proposed to mitigate tie-line power fluctuations. And the mixed-sensitivity approach is used to deal with the interference suppression [23][24][25].…”

Section: Open Accessmentioning

confidence: 99%

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Application of Coordinated SOFC and SMES Robust Control for Stabilizing Tie-Line Power

Zhang

et al. 2013

Energies

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Wind power causes fluctuations in power systems and introduces issues concerning system stability and power quality because of the lack of controllability of its discontinuous and intermittent resources. This paper presents a coordinated control strategy for solid oxide fuel cells (SOFCs) and superconducting magnetic energy storage (SMES) to match the intermittent wind power generation and compensate for the rapid load changes. An optimal H∞ control method, where the weighting function selection is expressed as an optimization problem, is proposed to mitigate tie-line power fluctuations and the mixed-sensitivity approach is used to deal with the interference suppression. Simulation results show that the proposed method significantly improves the smoothing effect of wind power fluctuations. Compared with the conventional control method, the proposed method has better anti-interference performance in various operating situations.

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“…However, large values of m and n will affect the stability margins and unnecessarily increase the controller order. Thus, m and n should be kept as low as possible [21].…”

Section: Design Methodology Of the Weighting Functionsmentioning

confidence: 99%

“…This way, the H ∞ optimization problem can be expressed in the standard formulation [21], as shown in Figure 4. Figure 4 can be described as follows:…”

Section: H ∞ Mixed-sensitivity Problemmentioning

confidence: 99%

“…Many alternative methods can be used to obtain the generalized plant P(s) in the S/KS/T mixed-sensitivity problem [21,22]. Figure 3 shows the configuration of the generalized plant.…”

Section: H ∞ Mixed-sensitivity Problemmentioning

confidence: 99%

Section: Open Accessmentioning

confidence: 99%

See 2 more Smart Citations

Application of Coordinated SOFC and SMES Robust Control for Stabilizing Tie-Line Power

Zhang

et al. 2013

Energies

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show abstract

“…However, the question of the suitability of the weights and the complexity of the algorithm employed are yet to be judged. As an alternative, a new set of simple guidelines have been developed recently that can greatly facilitate the selection of appropriate weights (Oloomi & Shafai, 2003). These guidelines are derived using elementary arguments based on phasors and straight-line approximation of the magnitude response, and in the same spirit as what is usually done in the classical control theory.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Tracking Performance in Robust Control Systems

Oloomi¹,

Shafai²

2011

Recent Advances in Robust Control - Theory and Applications in Robotics and Electromechanics

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Robust State‐and‐Disturbance Observer Design for Linear Non‐minimum‐phase Systems

Chen¹,

Lin²,

Tseng³

et al. 2015

Asian Journal of Control

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When there are external disturbances acting on the system, the conventional Luenberger observer design for state estimation usually results in a biased state estimate. This paper presents a robust state and disturbance observer design that gives both accurate state and disturbance estimates in the face of large disturbances. The proposed robust observer is structurally different from the conventional one in the sense that a disturbance estimation term is included in the observer equation. With this disturbance estimation term, the robust observer design problem is skillfully transformed into a disturbance rejection control problem. We then can utilize the standard H ∞ control design tools to optimize the robust observer between the disturbance rejection ability and noise immune ability. An important advantage of the proposed robust observer is that it applies to both minimum-phase systems and non-minimum phase systems.

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Weight selection in mixed sensitivity robust control for improving the sinusoidal tracking performance

Cited by 33 publications

References 8 publications

Application of Coordinated SOFC and SMES Robust Control for Stabilizing Tie-Line Power

Application of Coordinated SOFC and SMES Robust Control for Stabilizing Tie-Line Power

Optimizing the Tracking Performance in Robust Control Systems

Robust State‐and‐Disturbance Observer Design for Linear Non‐minimum‐phase Systems

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