This paper discusses energy optimal point-to-point motion control for linear time-invariant (LTI) systems using energy-optimal Model Predictive Control (EOMPC). The developed EOMPC, which is based on time-optimal MPC, aims at performing energy-optimal point-to-point motions within a required motion time. Energy optimality is achieved by setting the object function of the EOMPC optimization problem equal to the system’s energy losses. The key issue is to utilize the strategy of the prediction horizon to ensure that the motion time is exactly equal to the required motion time. Application of EOMPC on a badminton robot shows the practical applicability of the developed method. In addition, an experimental comparison with time-optimal MPC is provided.
- Dynamic Systems and Control Division
Energy Optimal Point-to-Point Motion Using Model Predictive Control
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Wang, X, Swevers, J, Stoev, J, & Pinte, G. "Energy Optimal Point-to-Point Motion Using Model Predictive Control." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 267-273. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8586
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