Multi-objective robust controller synthesis with integral quadratic constraints in discrete-time
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866908288493289472 |
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| author | Schwenkel, Lukas Köhler, Johannes Müller, Matthias A. Scherer, Carsten W. Allgöwer, Frank |
| author_facet | Schwenkel, Lukas Köhler, Johannes Müller, Matthias A. Scherer, Carsten W. Allgöwer, Frank |
| contents | This article presents a novel framework for the robust controller synthesis problem in discrete-time systems using dynamic Integral Quadratic Constraints (IQCs). We present an algorithm to minimize closed-loop performance measures such as the $\mathcal H_\infty$-norm, the energy-to-peak gain, the peak-to-peak gain, or a multi-objective mix thereof. While IQCs provide a powerful tool for modeling structured uncertainties and nonlinearities, existing synthesis methods are limited to the $\mathcal H_\infty$-norm, continuous-time systems, or special system structures. By minimizing the energy-to-peak and peak-to-peak gain, the proposed synthesis can be utilized to bound the peak of the output, which is crucial in many applications requiring robust constraint satisfaction, input-to-state stability, reachability analysis, or other pointwise-in-time bounds. Numerical examples demonstrate the robustness and performance of the controllers synthesized with the proposed algorithm. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_22429 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multi-objective robust controller synthesis with integral quadratic constraints in discrete-time Schwenkel, Lukas Köhler, Johannes Müller, Matthias A. Scherer, Carsten W. Allgöwer, Frank Systems and Control Optimization and Control This article presents a novel framework for the robust controller synthesis problem in discrete-time systems using dynamic Integral Quadratic Constraints (IQCs). We present an algorithm to minimize closed-loop performance measures such as the $\mathcal H_\infty$-norm, the energy-to-peak gain, the peak-to-peak gain, or a multi-objective mix thereof. While IQCs provide a powerful tool for modeling structured uncertainties and nonlinearities, existing synthesis methods are limited to the $\mathcal H_\infty$-norm, continuous-time systems, or special system structures. By minimizing the energy-to-peak and peak-to-peak gain, the proposed synthesis can be utilized to bound the peak of the output, which is crucial in many applications requiring robust constraint satisfaction, input-to-state stability, reachability analysis, or other pointwise-in-time bounds. Numerical examples demonstrate the robustness and performance of the controllers synthesized with the proposed algorithm. |
| title | Multi-objective robust controller synthesis with integral quadratic constraints in discrete-time |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2503.22429 |