On QFT tuning of multivariable μ controllers

Lee, J. W.; Chait, Yossi; Steinbuch, M Maarten

doi:10.1016/s0005-1098(00)00076-5

Cited by 13 publications

(3 citation statements)

References 5 publications

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“…Reference [12] utilized the genetic algorithm to optimize the QFT controller. Reference [14] combined QFT with the μ method to handle the constraint of robustness and achieved favorable performance. Reference [15] proposed a new QFT/H ∞ designed technology for the nonlinear feedback system in order to optimize the design process.…”

Section: Introductionmentioning

confidence: 99%

Quantitative feedback theory and zero phase error tracking control combined robust control for radar truck leveling simulator

Zhu

et al. 2009

J. Shanghai Univ.(Engl. Ed.)

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Radar leveling system is the key equipment for improving the radar mobility and survival capability. A combined quantitative feedback theory (QFT) controller is designed for the radar truck leveling simulator in this paper, which suffers from strong nonlinearities and system parameter uncertainties. QFT can reduce the plant uncertainties and stabilize the system, but it fails to obtain high-precision tracking. This drawback can be solved by a robust QFT control scheme based on zero phase error tracking control (ZPETC) compensation. The combined controller not only possesses high robustness, but greatly improves the system performance. To verify the effectiveness and the potential of the proposed controller, a series of experiments have been carried out. Experimental results have demonstrated its robustness against a large range of parameters variation and high tracking precision performance, as well as its capability of restraining the load coupling among channels. The combined QFT controller can drive the radar truck leveling platform accurately, quickly and stably.

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Section: Introductionmentioning

confidence: 99%

Quantitative feedback theory and zero phase error tracking control combined robust control for radar truck leveling simulator

Zhu

et al. 2009

J. Shanghai Univ.(Engl. Ed.)

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“…QFT was first developed by Isaac Horowitz, (Horowitz 1982) and publications with QFT control techniques for flight control can be found in (Philips et al, 1997), (Lee et al, 2000), (Keating, et al, 1997), (Patcher et al, 1997), (Rasmussen S.J., Houpis C.H., 1997) and (Lin C, Ying C., 1998). In this paper, a QFT controller will be designed for the complete Research Civil Aircraft Model (RCAM) benchmark problem described by (Lambrechts, et al, 1997), which is a multivariable nonlinear plant that has been used to compare different design approaches.…”

Section: Introductionmentioning

confidence: 99%

QFT for the Design of an Aircraft Flight Control

Santander¹,

Almansa

2005

IFAC Proceedings Volumes

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“…Hence, further fine tuning during experiments is not possible, yet preferred by industrial control engineers. One line of research is to combine model-based and classical loopshaping ideas such as QFT [9] into one design paradigm as described in [12] and used in [5].…”

Section: Introductionmentioning

confidence: 99%

Frequency response based multivariable control design for motion systems

Boerlage

Steinbuch

Angelis

Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005.

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In this paper, we discuss the design of multivariable motion controllers exploiting crosscouplings in the controller for open loop decoupling, disturbance rejection and feedforward decoupling. Using specific properties of motion systems, we illustrate that frequency response design methods can be extended to handle several multivariable control problems. Application to high performance motion systems shows significant improvement.

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On QFT tuning of multivariable μ controllers

Cited by 13 publications

References 5 publications

Quantitative feedback theory and zero phase error tracking control combined robust control for radar truck leveling simulator

Quantitative feedback theory and zero phase error tracking control combined robust control for radar truck leveling simulator

QFT for the Design of an Aircraft Flight Control

Frequency response based multivariable control design for motion systems

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