Move blocked model predictive control with guaranteed stability and improved optimality using linear interpolation of base sequences
2020 · International Journal of Control
저자
Sang Hwan Son, Byung Jun Park, Tae Hoon Oh, Jong Woo Kim, 이종민 (Jong Min Lee)
연구주제
Advanced Control Systems Optimization
NTIS 과학기술표준분류
배정 근거: 지원 과제·키워드 근거가 없어 AI가 논문 제목·초록을 읽고 고른 분류(정책 연계 맵과 같은 방법).
AI 연구 키워드·방법
모델 예측 제어(MPC) move blocking model predictive control recursive feasibility
키워드 (OpenAlex)
model predictive control linear interpolation base sequence linear quadratic regulator recursive feasibility closed-loop stability computational efficiency online optimization
초록
To mitigate the online computational load of model predictive control, move blocking, which parameterises either the input sequence or offset from the base sequence by fixing the decision variables over arbitrary time intervals, is commonly used. However, existing move blocking schemes use a fixed base sequence only and do not fully exploit the valuable properties from various base sequences. Thus, we propose the interpolated solution-based move blocking strategy which parameterises the offset from the convex combination of two complementary base sequences – infinite-horizon linear quadratic regulator solution and shifted previous solution – and optimises the interpolation parameter as an additional decision variable in the optimal control problem. This allows the controller to exploit the valuable properties from both solutions by choosing the optimal interpolation parameter and blocked…
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교수 1
연구주제 1
Advanced Control Systems Optimization