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

We study a stabilization problem for systems with quantized signals. We propose encoding strategies for three signals: the plant output, the control input, and the estimate of the plant output. A controller generates the estimate of the plant output in addition to the control input and then transmits their quantized data to a plant for control and quantization. We obtain sufficient conditions for local practical stability under bounded disturbances and noise. We first develop an encoding method for general stabilizing gains and then tailor it to deadbeat gains. Finally, we illustrate the proposed encoding methods with numerical simulations.

Observer-Based Stabilization of Systems With Quantized Inputs and Outputs

A novel dynamic model for the online prediction of rate of penetration and its industrial application to a drilling process

This article presents an improved disturbance estimation and rejection method based on equivalent input disturbance (EID) with $H_\infty$ robust performance for a time-varying uncertain system. The analysis and synthesis are conducted in the frequency domain. Different from conventional two-degree-of-freedom (2-DOF) $H_\infty$ control, some related weighting functions are introduced into a new devised structure to separate the rejection of the parameter uncertainty and disturbance from reference tracking. Compared with the existent EID-based approaches designed in the time domain of which the robust performance is not addressed, $H_\infty$ robust performance of the closed-loop system is guaranteed in this design. Treating the difference between the real plant and an ideal plant, namely, the overall effect of the parameter uncertainty and disturbance, as an EID, an EID estimation and compensation strategy is then established to cancel out the effect of the EID in system output. Furthermore, a constant scaling matrix is introduced into system design to reduce the conservativeness of a quadratic stabilization condition. Finally, a comparison with conventional 2-DOF robust $H_\infty$ control illustrates the advantages of the developed method.

Improved Equivalent-Input-Disturbance Approach Based on $H_\infty$ Control

LMI solution to singular H 2 suboptimal control problems

In this paper, a new control approach is proposed for the transient stabilization of a single-machine infinite-bus power system. The proposed method is based on an LPV (linear parameter varying) modelling of the nonlinear power system and gain-scheduled output feedback control. It is well-known that when large disturbances or a fault occurs, the nonlinearity inherent in power systems can no longer be ignored. The proposed method can handle the nonlinear model directly. First, we show that the nonlinear model can be transformed equivalently into an LPV system with the rotor angle as the scheduling parameter. Then, a gain-scheduled output feedback controller is designed based on robust pole placement and L2-gain minimization. Simulation results verify that the proposed method is better than well-tuned conventional PSS control.

Kang-Zhi Liu

Papers

Observer-Based Stabilization of Systems With Quantized Inputs and Outputs

A novel dynamic model for the online prediction of rate of penetration and its industrial application to a drilling process

Improved Equivalent-Input-Disturbance Approach Based on $H_\infty$ Control

LMI solution to singular H 2 suboptimal control problems

LPV modelling and gain-scheduled control approach for the transient stabilization of power systems