Analog Solver for Embedded Model Predictive Control with Application to Quadruple Tank System
Continuous-time dynamic solvers have emerged as a viable alternative for online optimization of model predictive control (MPC). This class of solvers emulates the behavior of MPC by tracing its solution trajectories to the Karush-Kuhn-Tucker (KKT) optimality point. In this paper, we develop an analo...
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Published in | 2021 American Control Conference (ACC) pp. 4680 - 4685 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
American Automatic Control Council
25.05.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Continuous-time dynamic solvers have emerged as a viable alternative for online optimization of model predictive control (MPC). This class of solvers emulates the behavior of MPC by tracing its solution trajectories to the Karush-Kuhn-Tucker (KKT) optimality point. In this paper, we develop an analog circuit architecture for the hardware realization of such dynamic controllers. Using the gradient dynamics as a case study, we develop a prototype solver using a Field Programmable Analog Array (FPAA) and we validate its efficacy on a quadruple water tank system. |
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ISSN: | 2378-5861 |
DOI: | 10.23919/ACC50511.2021.9483438 |