A method for the distributed optimization of dynamic nonlinear systems is presented. The method is based on partial goal-interaction operators [1]. Partial goal-interaction operators provide gradient information of no...
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ISBN:
(纸本)9781424474264
A method for the distributed optimization of dynamic nonlinear systems is presented. The method is based on partial goal-interaction operators [1]. Partial goal-interaction operators provide gradient information of non-local objective functions. Hence, these operators are used to modify the objective functions of infimal optimization problems in order to take non-local information into account and to achieve an optimum for the overall objective, i.e. the objective of the entire process. However, that optimum is achieved by a decentralized but cooperative optimization, while communication between the different infimal optimization units is limited. An important part of the method is the decentralized calculation of sensitivities. The method is applied to a nonlinear differential-algebraic simple-toy system and compared to the dual-optimization method [2] as well as to the solutions of fully centralized and fully decentralized optimizations.
Abstract Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-b...
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Abstract Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based state estimation can provide estimates of the unknown states and increase the reliability of measurements. In this paper, an integrated approach is presented for the estimation problem employing unconventional, but technically feasible sensor networks. Using the ASM1 model in the reference scenario BSM1, the estimators EKF and MHE are evaluated. Very good estimation results for the system comprising of 78 states are found.
Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based stat...
详细信息
ISBN:
(纸本)9783902661548
Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based state estimation can provide estimates of the unknown states and increase the reliability of measurements. In this paper, an integrated approach is presented for the estimation problem employing unconventional, but technically feasible sensor networks. Using the ASM1 model in the reference scenario BSM1, the estimators EKF and MHE are evaluated. Very good estimation results for the system comprising of 78 states are found.
This paper investigates the formulation of nonlinear model-predictive control problems with economic objectives on an infinite horizon. The proposed formulation guarantees nominal stability for closed-loop operation. ...
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ISBN:
(纸本)9783902661548
This paper investigates the formulation of nonlinear model-predictive control problems with economic objectives on an infinite horizon. The proposed formulation guarantees nominal stability for closed-loop operation. Furthermore, a novel solution method of the infinite horizon method through a transformation of the independent time variable is employed. The closed-loop optimization with infinite horizon is compared to a finite-horizon formulation. A small case study is presented for illustration purposes.
Abstract This paper investigates the formulation of nonlinear model-predictive control problems with economic objectives on an infinite horizon. The proposed formulation guarantees nominal stability for closed-loop op...
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Abstract This paper investigates the formulation of nonlinear model-predictive control problems with economic objectives on an infinite horizon. The proposed formulation guarantees nominal stability for closed-loop operation. Furthermore, a novel solution method of the infinite horizon method through a transformation of the independent time variable is employed. The closed-loop optimization with infinite horizon is compared to a finite-horizon formulation. A small case study is presented for illustration purposes.
We present a method for computing the solution to the infinite horizon continuous-time constrained linear quadratic regulator (CLQR). The method relies on two main features: a multi-grid method for placing a finite nu...
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ISBN:
(纸本)9783902661548
We present a method for computing the solution to the infinite horizon continuous-time constrained linear quadratic regulator (CLQR). The method relies on two main features: a multi-grid method for placing a finite number of time intervals, and a piece-wise linear parameterization of the input within the intervals. The input values at the grid points and slopes within the time intervals are computed via quadratic programs (QPs). The grids are gradually refined to efficiently improve the accuracy of the solution, and the required matrices and vectors for all QPs are computed offline and stored to improve the online efficiency. We present two examples, a single-input single-output unstable system and a three-input three-output stable system, to show the main characteristics of the proposed computation method.
Abstract We present a method for computing the solution to the infinite horizon continuous-time constrained linear quadratic regulator (CLQR). The method relies on two main features: a multi-grid method for placing a ...
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Abstract We present a method for computing the solution to the infinite horizon continuous-time constrained linear quadratic regulator (CLQR). The method relies on two main features: a multi-grid method for placing a finite number of time intervals, and a piece-wise linear parameterization of the input within the intervals. The input values at the grid points and slopes within the time intervals are computed via quadratic programs (QPs). The grids are gradually refined to efficiently improve the accuracy of the solution, and the required matrices and vectors for all QPs are computed offline and stored to improve the online *** present two examples, a single-input single-output unstable system and a three-input three-output stable system, to show the main characteristics of the proposed computation method.
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