A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles
We present a new algorithm for model predictive control of non-linear systems with respect to multiple, con icting objectives. The idea is to provide a possibility to change the objective in real-time, e.g. as a reaction to changes in the environment or the system state itself. The algorithm utilise...
| Những tác giả chính: | , , , , , |
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| Định dạng: | Conference item |
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Elsevier
2017
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| _version_ | 1826278415609626624 |
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| author | Peitz, S Schäfer, K Ober-Blobaum, S Eckstein, J Köhler, U Dellnitz, M |
| author_facet | Peitz, S Schäfer, K Ober-Blobaum, S Eckstein, J Köhler, U Dellnitz, M |
| author_sort | Peitz, S |
| collection | OXFORD |
| description | We present a new algorithm for model predictive control of non-linear systems with respect to multiple, con icting objectives. The idea is to provide a possibility to change the objective in real-time, e.g. as a reaction to changes in the environment or the system state itself. The algorithm utilises elements from various well-established concepts, namely multiobjective optimal control, economic as well as explicit model predictive control and motion planning with motion primitives. In order to realise real-time applicability, we split the computation into an online and an offine phase and we utilise symmetries in the open-loop optimal control problem to reduce the number of multiobjective optimal control problems that need to be solved in the offine phase. The results are illustrated using the example of an electric vehicle where the longitudinal dynamics are controlled with respect to the concurrent objectives arrival time and energy consumption. |
| first_indexed | 2024-03-06T23:43:35Z |
| format | Conference item |
| id | oxford-uuid:7024e91b-f700-40e7-a949-c867c975d6e3 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T23:43:35Z |
| publishDate | 2017 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:7024e91b-f700-40e7-a949-c867c975d6e32022-03-26T19:35:16ZA Multiobjective MPC Approach for Autonomously Driven Electric VehiclesConference itemhttp://purl.org/coar/resource_type/c_5794uuid:7024e91b-f700-40e7-a949-c867c975d6e3Symplectic Elements at OxfordElsevier2017Peitz, SSchäfer, KOber-Blobaum, SEckstein, JKöhler, UDellnitz, MWe present a new algorithm for model predictive control of non-linear systems with respect to multiple, con icting objectives. The idea is to provide a possibility to change the objective in real-time, e.g. as a reaction to changes in the environment or the system state itself. The algorithm utilises elements from various well-established concepts, namely multiobjective optimal control, economic as well as explicit model predictive control and motion planning with motion primitives. In order to realise real-time applicability, we split the computation into an online and an offine phase and we utilise symmetries in the open-loop optimal control problem to reduce the number of multiobjective optimal control problems that need to be solved in the offine phase. The results are illustrated using the example of an electric vehicle where the longitudinal dynamics are controlled with respect to the concurrent objectives arrival time and energy consumption. |
| spellingShingle | Peitz, S Schäfer, K Ober-Blobaum, S Eckstein, J Köhler, U Dellnitz, M A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles |
| title | A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles |
| title_full | A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles |
| title_fullStr | A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles |
| title_full_unstemmed | A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles |
| title_short | A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles |
| title_sort | multiobjective mpc approach for autonomously driven electric vehicles |
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