Linear System Analysis and Optimal Control of Natural Gas Dynamics in Pipeline Networks
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866915405179650048 |
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| author | Baker, Luke S. Shivakumar, Sachin Armbruster, Dieter Platte, Rodrigo B. Zlotnik, Anatoly |
| author_facet | Baker, Luke S. Shivakumar, Sachin Armbruster, Dieter Platte, Rodrigo B. Zlotnik, Anatoly |
| contents | We design nonlinear and adaptive linear model-predictive control (MPC) techniques to minimize operational costs of compressor-actuated dynamics in natural gas pipeline networks. We establish stability of the local linear system and derive rigorous bounds on error between the nonlinear and linear system solutions. These bounds are used to quantify conditions under which the linear MPC can substitute the nonlinear MPC without significant loss of predictive accuracy. Furthermore, we prove and numerically verify that the computational cost of the linear MPC is orders of magnitude lower than that of solving the baseline optimal control problem. Numerical simulations are performed on nontrivial networks to demonstrate that the proposed MPC can effectively adapt to varying load conditions while maintaining nearly 95% optimality. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_06658 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Linear System Analysis and Optimal Control of Natural Gas Dynamics in Pipeline Networks Baker, Luke S. Shivakumar, Sachin Armbruster, Dieter Platte, Rodrigo B. Zlotnik, Anatoly Optimization and Control Dynamical Systems 37N35 We design nonlinear and adaptive linear model-predictive control (MPC) techniques to minimize operational costs of compressor-actuated dynamics in natural gas pipeline networks. We establish stability of the local linear system and derive rigorous bounds on error between the nonlinear and linear system solutions. These bounds are used to quantify conditions under which the linear MPC can substitute the nonlinear MPC without significant loss of predictive accuracy. Furthermore, we prove and numerically verify that the computational cost of the linear MPC is orders of magnitude lower than that of solving the baseline optimal control problem. Numerical simulations are performed on nontrivial networks to demonstrate that the proposed MPC can effectively adapt to varying load conditions while maintaining nearly 95% optimality. |
| title | Linear System Analysis and Optimal Control of Natural Gas Dynamics in Pipeline Networks |
| topic | Optimization and Control Dynamical Systems 37N35 |
| url | https://arxiv.org/abs/2305.06658 |