An approximate method for solving optimal control problems
An approximate method is presented for solving optimization problems. A truncated series of exponential functions is used to approximate a desired state variable or output of a system. Integral-square error is used as the criterion to be minimized. The coefficients of the series are determined in su...
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Published in | IEEE transactions on automatic control Vol. 9; no. 4; pp. 554 - 556 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
IEEE
01.10.1964
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Subjects | |
Online Access | Get full text |
ISSN | 0018-9286 |
DOI | 10.1109/TAC.1964.1105764 |
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Abstract | An approximate method is presented for solving optimization problems. A truncated series of exponential functions is used to approximate a desired state variable or output of a system. Integral-square error is used as the criterion to be minimized. The coefficients of the series are determined in such a way that the error index is minimum, subject to the physical constraints imposed on the system. In this way, the dynamic problem is converted into a static one. The resulting problem becomes a general problem of mathematical programming which may be solved either by digital or analog computers. Once the coefficients of the approximating signal are determined, the input control signal is determined through the relationship of the process dynamics of the system. This approximate method of optimization is simple, and possesses the important advantage of requiring less computer time than exact optimization methods. |
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AbstractList | An approximate method is presented for solving optimization problems. A truncated series of exponential functions is used to approximate a desired state variable or output of a system. Integral-square error is used as the criterion to be minimized. The coefficients of the series are determined in such a way that the error index is minimum, subject to the physical constraints imposed on the system. In this way, the dynamic problem is converted into a static one. The resulting problem becomes a general problem of mathematical programming which may be solved either by digital or analog computers. Once the coefficients of the approximating signal are determined, the input control signal is determined through the relationship of the process dynamics of the system. This approximate method of optimization is simple, and possesses the important advantage of requiring less computer time than exact optimization methods. |
Author | Chang, C. DeRusso, P. |
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Cites_doi | 10.1109/TAC.1963.1105534 10.1287/opre.3.2.168 10.1287/opre.3.4.388 10.1093/qjmam/2.4.460 |
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References | brown (ref3) 1957 chang (ref7) 1963 ref4 ref6 jackson (ref5) 1956 ref2 ref1 |
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SubjectTerms | Aerodynamics Analog computers Computer errors Control system synthesis Electric variables control Nonlinear dynamical systems Optimal control Optimization methods Signal processing Variable speed drives |
Title | An approximate method for solving optimal control problems |
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