1. Introduction. 2. Linear Algebra. 3. Linear Systems. 4. H2 and Ha Spaces. 5. Internal Stability. 6. Performance Specifications and Limitations. 7. Balanced Model Reduction. 8. Uncertainty and Robustness. 9. Linear Fractional Transformation. 10. m and m- Synthesis. 11. Controller Parameterization. 12. Algebraic Riccati Equations. 13. H2 Optimal Control. 14. Ha Control. 15. Controller Reduction. 16. Ha Loop Shaping. 17. Gap Metric and ...u- Gap Metric. 18. Miscellaneous Topics. Bibliography. Index.

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Essentials of Robust Control

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

Linear Robust Control

This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

A lifting technique for linear periodic systems with applications to sampled-data control

In the robust performance design, the celebrated $\mu$ -synthesis provides a reputed tool for systems with norm-bounded uncertainty. However, such small-gain methods inevitably limit the achievable robust performance when the dynamic uncertainty is not characterized by its gain bound. To achieve a high robust performance for systems with positive real (PR) uncertainty, an output strict passivity (OSP) approach is proposed recently which makes use of the positive realness and the maximum gain information of the uncertainty. Aiming at an even higher robust performance, this article proposes a novel model for PR uncertainties which captures the frequency-dependent gain bound, and establishes the corresponding design theory to actively utilize both gain and phase bounds of the uncertainty in the robust performance design. A case study reveals that the new uncertainty model alone yields a substantial improvement over the OSP method in performance even under the same design setup. Moreover, the best tuned controller outperforms the OSP controller.

Improved Robust Performance Design for Passive Uncertain Systems—Active Use of the Uncertainty Phase and Gain

Smart grid is a brand new power system that allows the installation of a high percentage of powers from renewable energy sources. In its operation, how to utilize the smoothing effect of renewable energy output plays a vital role in ensuring the power quality. This paper proposes a new operation method for smart grid which assures both the power quality and the economy of the operation. Firstly, we derive a criterion for the frequency maintenance which relates the allowable bound of frequency with that of the prediction error of renewable energy output. Secondly, we show how to employ the statistics of renewable energy to determine the uncertainty bounds. Thirdly, we propose two peak-cut methods to improve the frequency performance when the frequency bound is not assured. Finally, the proposed methods are evaluated via numerical examples.

http://ieeexplore.ieee.org/iel7/7364573/7386954/07387116.pdf

Economic operation of smart grid based on the statistics of renewable energy

Neo Robust Control Theory–Beyond The Small-Gain and Passivity Paradigms–

This paper proposes a novel nonlinear decentralized control method for a class of multi‐machine power systems The aim is to construct a suitable decentralized feedback control law so as t

Nonlinear decentralized load frequency control of multi‐machine power systems with exponential stability and low L2 gain against load disturbance

DC-DC converters by nature present hybrid behavior, which is described by a set of discrete modes associated with continuous dynamics. The control objective is accomplished by switching among the d...

Kang-Zhi Liu

Papers

Improved Robust Performance Design for Passive Uncertain Systems—Active Use of the Uncertainty Phase and Gain

Economic operation of smart grid based on the statistics of renewable energy

Neo Robust Control Theory–Beyond The Small-Gain and Passivity Paradigms–

Nonlinear decentralized load frequency control of multi‐machine power systems with exponential stability and low L2 gain against load disturbance

A New Model Predictive Control Approach to DC-DC Converter Based on Combinatory Optimization