The Experts below are selected from a list of 12669 Experts worldwide ranked by ideXlab platform
Moritz Diehl - One of the best experts on this subject based on the ideXlab platform.
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high speed moving horizon estimation based on Automatic Code Generation
Conference on Decision and Control, 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
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CDC - High-speed moving horizon estimation based on Automatic Code Generation
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
Hans Joachim Ferreau - One of the best experts on this subject based on the ideXlab platform.
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high speed moving horizon estimation based on Automatic Code Generation
Conference on Decision and Control, 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
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CDC - High-speed moving horizon estimation based on Automatic Code Generation
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
Milan Vukov - One of the best experts on this subject based on the ideXlab platform.
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high speed moving horizon estimation based on Automatic Code Generation
Conference on Decision and Control, 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
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CDC - High-speed moving horizon estimation based on Automatic Code Generation
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
Tom Kraus - One of the best experts on this subject based on the ideXlab platform.
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high speed moving horizon estimation based on Automatic Code Generation
Conference on Decision and Control, 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
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CDC - High-speed moving horizon estimation based on Automatic Code Generation
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
Wouter Saeys - One of the best experts on this subject based on the ideXlab platform.
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high speed moving horizon estimation based on Automatic Code Generation
Conference on Decision and Control, 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
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CDC - High-speed moving horizon estimation based on Automatic Code Generation
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012Co-Authors: Hans Joachim Ferreau, Milan Vukov, Tom Kraus, Wouter Saeys, Moritz DiehlAbstract:Recent theoretical and algorithmic advances have led to efficient algorithms that allow for real-time optimisation of processes with fast nonlinear dynamics. This paper addresses the efficient implementation of algorithms for moving horizon estimation (MHE) for obtaining real-time estimates of process states or parameters that are not measured directly. To this end, we propose to combine the previously proposed concepts of real-time iteration schemes and Automatic Code Generation to obtain highly efficient source Code of MHE algorithms. This has led to major extensions of the ACADO Code Generation tool that Automatically generates customised plain C Code for both model predictive control (MPC) and MHE applications. As a proof of concept, we present numerical results of controlling a nonlinear ODE model by means of combined exported MHE and MPC algorithms in a closed-loop manner. These exported algorithms turn out to be significantly faster than their generically implemented counterparts.
