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• W3200526211 abstract "Robust design of autonomous systems under uncertainty is an important and challenging problem. In practice, state disturbances and state estimation error may cause a controller to fail to accomplish its task or even to stabilize the system. In this paper, we propose a novel tube-based robust model predictive control design based on set-membership state estimation for constrained systems with unknown but bounded state and output disturbances. With more accurate and efficient error bounding methods, the proposed controller ensures robust constraint satisfaction, guarantees recursive feasibility and stability, generates less conservative behavior than the previous work, and scales well to high-dimensional robotic applications. Our simulated experiments on three different systems (double integrator, robotic walker, and quadrotor) demonstrate that the proposed controller is robust against a larger range of disturbances and results in superior closed-loop performance than baseline methods." @default.
• W3200526211 created "2021-09-27" @default.
• W3200526211 creator A5014226370 @default.
• W3200526211 creator A5059066811 @default.
• W3200526211 creator A5080984162 @default.
• W3200526211 date "2020-08-11" @default.
• W3200526211 modified "2023-09-27" @default.
• W3200526211 title "Robust Model Predictive Control with State Estimation under Set-Membership Uncertainty" @default.
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• W3200526211 hasPublicationYear "2020" @default.
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