Robust control systems design using H-infinity optimization theory
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Engineering topics
Publications and source records attributed to Yeh, H. H..
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In this paper, step-by-step procedures of applying the H-infinity theory to robust control systems design are given. The objective of the paper is to eliminate the possible difficulties a control engineer may encounter in applying H-infinity control theory and to clear up some misconceptions about H-infinity theory like high-gain controller and numerical obstacles, etc. An efficient algorithm is used to compute the optimal H-infinity norm. The Glover and Doyle (1988) controller formulas are slightly modified and used to construct an optimal controller without any numerical difficulties.
The state-space H2/H(infinity) theory is employed to develop a design procedure that addresses the performance-robustness problem. A numerical example is used to illustrate both the advantages and limitations of the procedure and how it compares to linear-quadratic-Gaussian loop transfer recovery (LQG/LTR). A less rigorous procedure that compares favorably to the LQG/LTR is also constructed.
The two-Riccati-equation method was employed to design an H(infinity) optimal controller for a four-block problem. An iterative scheme was used to reduce gamma to a number which is very close to the optimum. However, as gamma is close to the optimum, the elements of the state-space realization of the controller will approach infinity. It is demonstrated that the numerical difficulty is caused by the restriction of the controller being strictly proper. This difficulty can easily be removed if one is allowed to have a proper controller with a direct feed-through term.
The two-Riccati-equation method solution to a standard H(infinity) control problem can be used to characterize all possible stabilizing optimal or suboptimal H(infinity) controllers if the optimal or suboptimal H(infinity) norm is available in the literature. An iterative algorithm for computing the optimal H(infinity) norm is proposed. The algorithm employs fixed-point, double secant and bisection to guarantee a super linear convergence.