TY - GEN

T1 - Robust control system design using simulated annealing

AU - Motoda, Toshikazu

AU - Stengel, Robert F.

AU - Miyazawa, Yoshikazu

PY - 2000/12/1

Y1 - 2000/12/1

N2 - Design parameters of a flight control system are optimized by a probabilistic method. Simulated Annealing is applied for the optimization while the Downhill-Simplex method is added to generate new design vector candidates. The cost function to be minimized is chosen as the probability of violating the design criteria, and it is derived by Monte Carlo evaluation that incorporates various uncertainties. Thus, the designed system is robust against these uncertainties. The feasibility of the algorithm is demonstrated by designing a control system for a simplified model. The algorithm is compared both with the Downhill-Simplex method and the Genetic Algorithm. For the simple example, the results show that Simulated Annealing is more effective than the Downhill-Simplex method for parameter optimization, and it requires less computational time than the Genetic Algorithm. Furthermore, the algorithm is applied to the longitudinal flight control design of automatic landing system. It is demonstrated and verified that the algorithm is an efficient control design method.

AB - Design parameters of a flight control system are optimized by a probabilistic method. Simulated Annealing is applied for the optimization while the Downhill-Simplex method is added to generate new design vector candidates. The cost function to be minimized is chosen as the probability of violating the design criteria, and it is derived by Monte Carlo evaluation that incorporates various uncertainties. Thus, the designed system is robust against these uncertainties. The feasibility of the algorithm is demonstrated by designing a control system for a simplified model. The algorithm is compared both with the Downhill-Simplex method and the Genetic Algorithm. For the simple example, the results show that Simulated Annealing is more effective than the Downhill-Simplex method for parameter optimization, and it requires less computational time than the Genetic Algorithm. Furthermore, the algorithm is applied to the longitudinal flight control design of automatic landing system. It is demonstrated and verified that the algorithm is an efficient control design method.

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M3 - Conference contribution

SN - 9781563479786

T3 - AIAA Guidance, Navigation, and Control Conference and Exhibit

BT - AIAA Guidance, Navigation, and Control Conference and Exhibit

T2 - AIAA Guidance, Navigation, and Control Conference and Exhibit 2000

Y2 - 14 August 2000 through 17 August 2000

ER -