EKF Based Generalized Predictive Control of Nonlinear Systems
In this paper, Autoregressive with exogenous input (ARX) and dynamic neural network (DNN) based generalized predictive control (GPC) methods are designed to control of nonlinear systems. ARX and DNN models adaptively approximate the plant dynamics and predict the future behavior of the nonlinear system. While control process goes on, the poles of the ARX and DNN models are constrained in a stable region using a projection operator for structural stability. Simulation results are given to compare the tracking performances of the methods. ARX-GPC and DNN-GPC both yield good tracking performances while keeping the changes in control signal as low as possible. The simulation results show that even though ARX is a linear model, it provides acceptable tracking results as well as DNN model.
Keywords:
Generalized predictive control, ARX, dynamic neural network Kalman filter and extended Kalman filter, nonlinear systems and adaptive learning rate,
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- ISSN: 2147-8228
- Yayın Aralığı: Yılda 4 Sayı
- Başlangıç: 2013
- Yayıncı: Selçuk Üniversitesi