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Computer Aided Design of Optimal Control Systems

出版	University of California, Irvine, 1973
URL	http://books.google.com.hk/books?id=sIh7NAEACAAJ&hl=&source=gbs_api

註釋The paper documents an investigation of the use of mathematical programming methods for the solution of the pole placement problem of optimal control systems synthesis. More specifically, the work presents two algorithms (Generalized Polynomial Programming and Adaptive Random Search) for the solution of constrained nonlinear optimization problems. A technique is presented for both formulating and solving multi-input/multi-output linear time-invariant optimal control synthesis problems with stationary noise inputs, without solving an algebraic matrix Riccati equation. This method, formulated in the time domain, is equivalent to the analytic methods of Newton, Gould, and Kaiser (1957), or the numerical methods of Weston and Bongiorno (1972), but it allows for constraints on system parameters and performance in both the frequency and time domains. Since it does not depend on spectral factorization, it is much easier to extend to the multi-input/multi-output case. (Author Modified Abstract).