Towards Dynamic Optimization with Partially Updated Sensitivities * *NvD is fellow of the TEMPO Initial Training Network. The work is supported by the EU via ERC-HIGHWIND (259 166), ITN-TEMPO (607 957), and ITN-AWESCO (642 682). The support from Flanders Make, DFG via the project 'Numerische Methoden zur optimierungsbasierten Regelung zyklischer Prozesse, the KU Leuven-BOF PFV/10/002 Centre of Excellence: Optimization in Engineering (OPTEC), and project G0A6917N of the Research Foundation -Flanders (FWO-Flanders), is gratefully acknowledged
| Autor: | Niels van Duijkeren, Jan Swevers, Goele Pipeleers, Moritz Diehl |
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| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Computer science Computation 02 engineering and technology Optimal control Task (project management) Reduction (complexity) Nonlinear system Model predictive control 020901 industrial engineering & automation Quadratic equation 020401 chemical engineering Control and Systems Engineering 0204 chemical engineering |
| Zdroj: | IFAC-PapersOnLine. 50:8680-8685 |
| ISSN: | 2405-8963 |
| Popis: | In nonlinear model predictive control (NMPC), a control task is approached by repeatedly solving an optimal control problem (OCP) over a receding horizon. Popularly, the OCP is approximated with a finite-dimensional nonlinear program (NLP). Since computing the solution of an NLP can be a complex and time-consuming task, tailored optimization algorithms have emerged to (approximately) solve the NLPs. Most methods rely on repeatedly solving a quadratic approximation of the NLP. Since computing this approximation is generally computationally demanding, it can form a bottelenck in obtaining a real-time applicable control law. This paper proposes DOPUS, a novel update scheme for the quadratic approximation of the NLP. DOPUS exploits the structure of the NLP and the repeated nature at which it is solved, to reduce the number of computations at the price of a small reduction of the convergence speed. Foreseen application areas include (economic) NMPC for fast-changing control tasks and fast time-varying systems. The convergence properties of DOPUS are studied and the performance is illustrated in a numerical case study considering a control task for a planar robot arm. |
| Databáze: | OpenAIRE |
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