A New Development of Adaptive Model Predictive Control
| Authors: | Yu D. L., Liverpool John Moores University, United Kingdom
Yu D.W., Northeast University at Qinhuangdao, China
Gomm J.B., Liverpool John Moores University, United Kingdom
Page G.W., Liverpool John Moores University, United Kingdom |
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| Topic: | 1.2 Adaptive and Learning Systems |
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| Session: | Optimal and Adaptive Control |
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| Keywords: | Adaptive RBF network, NMPC, adaptive control, ROLS algorithm |
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Abstract
An adaptive radial basis function (RBF) neural network model is developed in this paper for nonlinear systems using the recursive orthogonal least squares (ROLS) algorithm. The model is used in a nonlinear model predictive control (NMPC). The developed adaptive NMPC is applied to a chemical reactor rig. On-line control performance is presented and it demonstrates superiority over the fixed parameter PID control.
