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확률 모델예측제어 알고리즘을 이용한 작동기 수가 부족한 무인잠수정 운동 제어
이찬규(Chan-gyu Lee),장준우(Jun-woo Jang),김진환(Jin-whan Kim) 제어로봇시스템학회 2020 제어·로봇·시스템학회 논문지 Vol.26 No.5
Most dynamic system operate under uncertainties such as external disturbances, measurement noise and modeling uncertainties. Failure to account for these uncertainties in the controller design may lead to performance degradation in real-world applications. As a result, SMPC (Stochastic Model Predictive Control), which provides a probabilistic framework for the nonlinear model predictive control of systems with stochastic uncertainty, has attracted much attention. The main challenge of SMPC is the efficient propagation of probabilistic uncertainty through system dynamics. In this paper, unscented transformation was used to efficiently estimate the distribution of states under uncertainties, and it is applied to trajectory tracking and obstacle avoidance of an unmanned underwater vehicle. The performance of the proposed algorithm was demonstrated through numerical simulations.