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On-line optimization via off-line parametric optimization tools
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DOI：10.1016/S0098-1354(00)00510-X.png)
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In this paper, on-line optimization problems with a quadratic performance criteria and linear constraints are formulated as multi-parametric quadratic programs, where the input and state variables, corresponding to a plant, are treated as optimization variables and parameters, respectively. The solution of such problems is given by (i) a complete set of profiles of all the optimal inputs to the plant as a function of state variables, and (ii) the regions in the space of state variables where these functions remain optimal. It is shown that these profiles are linear and the corresponding regions are described by linear inequalities. An algorithm for obtaining these profiles and corresponding regions of optimality is also presented. The key feature of the proposed approach is that the on-line optimization problem is solved off-line via parametric programming techniques, hence, at each time interval (i) no optimization solver is called on-line, (ii) simple function evaluations are required for obtaining the optimal inputs to the plant for the current state of the plant. (C) 2000 Elsevier Science Ltd. All rights reserved.
Keyword:
real-time optimization
model predictive control
multi-parametric quadratic programming
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