Robust Performance in Parametric Control System Design With Application to Power Systems

2021 ◽  
Vol 68 (3) ◽  
pp. 2400-2407
Author(s):  
Majid Firouzbahrami ◽  
Amin Nobakhti
1994 ◽  
Vol 6 (4) ◽  
pp. 304-311
Author(s):  
Kenzo Nonami ◽  
◽  
Qi-fu Fan ◽  

The <I>H</I>∞ control theory is currently the most powerful method for robust control theory, and is useful as well as practical because a great amount of software related to computer-aided control system design is available. However, it has some disadvantages in that the <I>H</I>∞ control system is a conservative one and cannot deal with robust performance. This is due to maximum singular values. Doyle proposed a structured singular value instead of a maximum singular value. This is called ∞ synthesis theory and actively deals with robust performance using D-K iteration. This paper is concerned with computeraided design of active vibration control systems based on the μ synthesis theory. First, the paradigm of the μ synthesis theory is described concerning μ, robust performance, and D-K iteration. Next, the relationships between the μ controller, robust performance, nominal performance, and robust stability are discussed for vibration control systems.


Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 567
Author(s):  
Adrian Gambier

advanced control system design for large wind turbines is becoming increasingly complex, and high-level optimization techniques are receiving particular attention as an instrument to fulfil this significant degree of design requirements. Multiobjective optimal (MOO) control, in particular, is today a popular methodology for achieving a control system that conciliates multiple design objectives that may typically be incompatible. Multiobjective optimization was a matter of theoretical study for a long time, particularly in the areas of game theory and operations research. Nevertheless, the discipline experienced remarkable progress and multiple advances over the last two decades. Thus, many high-complexity optimization algorithms are currently accessible to address current control problems in systems engineering. On the other hand, utilizing such methods is not straightforward and requires a long period of trying and searching for, among other aspects, start parameters, adequate objective functions, and the best optimization algorithm for the problem. Hence, the primary intention of this work is to investigate old and new MOO methods from the application perspective for the purpose of control system design, offering practical experience, some open topics, and design hints. A very challenging problem in the system engineering application of power systems is to dominate the dynamic behavior of very large wind turbines. For this reason, it is used as a numeric case study to complete the presentation of the paper.


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