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Tham khảo tài liệu 'robust control theory and applications part 3', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Part 2 H-infinity Control 4 Robust H PID Controller Design Via LMI Solution of Dissipative Integral Backstepping with State Feedback Synthesis Endra Joelianto Bandung Institute of Technology Indonesia 1. Introduction PID controller has been extensively used in industries since 1940s and still the most often implemented controller today. The PID controller can be found in many application areas petroleum processing steam generation polymer processing chemical industries robotics unmanned aerial vehicles UAVs and many more. The algorithm of PID controller is a simple single equation relating proportional integral and derivative parameters. Nonetheless these provide good control performance for many different processes. This flexibility is achieved through three adjustable parameters of which values can be selected to modify the behaviour of the closed loop system. A convenient feature of the PID controller is its compatibility with enhancement that provides higher capabilities with the same basic algorithm. Therefore the performance of a basic PID controller can be improved through judicious selection of these three values. Many tuning methods are available in the literature among with the most popular method the Ziegler-Nichols Z-N method proposed in 1942 Ziegler Nichols 1942 . A drawback of many of those tuning rules is that such rules do not consider load disturbance model uncertainty measurement noise and set-point response simultaneously. In general a tuning for high performance control is always accompanied by low robustness Shinskey 1996 . Difficulties arise when the plant dynamics are complex and poorly modeled or specifications are particularly stringent. Even if a solution is eventually found the process is likely to be expensive in terms of design time. Varieties of new methods have been proposed to improve the PID controller design such as analytical tuning Boyd Barrat 1991 Hwang Chang 1987 optimization based Wong Seborg 1988 Boyd Barrat 1991 Astrom .
