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A Homogeneous and Self-Dual Interior-Point Linear Programming Algorithm for Economic Model Predictive Control
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DOI：10.1109/TAC.2015.2495558.png)
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Abstract
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We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that: 1) the proposed algorithm is significantly faster than several state-of-the-art IPMs based on sparse linear algebra and 2) warm-start reduces the average number of iterations by 35%-40%.
Keywords:
Energy systems
Linear programming algorithms
optimization algorithms
predictive control for linear systems
Riccati iterations
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