Quadratic optimal fuzzy control
One presents a fuzzy logic approach for optimal control of discrete-time nonlinear dynamic systems with a quadratic criterion. The approach is based on Pontryagin’s Minimum Principle. Using back propagation from the final co-state error and gradient descent, a method is devised which allows for trai...
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| Other Authors: | , |
| Format: | conferenceObject |
| Language: | eng |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10198/2751 |
| Country: | Portugal |
| Oai: | oai:bibliotecadigital.ipb.pt:10198/2751 |
| Summary: | One presents a fuzzy logic approach for optimal control of discrete-time nonlinear dynamic systems with a quadratic criterion. The approach is based on Pontryagin’s Minimum Principle. Using back propagation from the final co-state error and gradient descent, a method is devised which allows for training an adaptive fuzzy inference system to estimate values for the co-state variables converging to the optimal ones. In turn this implies that the controlled variables trajectories also converge to the optimal ones. The approach allows finding a solution to the optimal control problem on-line, by training of the system, rather than by pre computing it. In particular, the use of an adaptive fuzzy inference system also will allow incorporating a priori knowledge about the optimal behavior of the co-state variable and track changes in the system. |
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