Adaptive on-line steady-state optimization of slow dynamic processes
Automatica (Journal of IFAC)
A computational approach to the combined problem of optimization and parameter identification
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
The paper is concerned with the determination of optimum steady-state operation of industrial plant where the optimisation is performed using a mathematical model with parameters whose values are estimated by comparing model and real plant measurements. The two associated problems of system optimisation and model parameter estimation are discussed and an algorithm is examined whose purpose is to accomplish the correct steady-state optimum operating condition on the real plant in spite of inaccuracies in the structure of the mathematical model. The aim of the paper is to investigate the performance of the algorithm which is accomplished through a theoretical analysis of its application to a linear process, where the optimisation is performed using a quadratic performance index and a mathematical model of incorrect structure. Particular emphasis is given to the stability and convergence properties of the algorithm and to the effect of real process measurement errors. Simulation results are also presented illustrating the effectiveness of the technique when applied to nonlinear optimisation problems including a study concerned with determining optimum controller set points to maximise the net rate of return from a chemical reactor plant.