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2 Journal of Applied Computer Science

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Adaptive control of a pressure tank system with saturation nonlinearities

Ma Z., Jutan A., Bajic V. B.

Journal of Applied Computer Science

2001

Vol. 9, nr 1

61-83

The paper presents the design of a new nonlinear real-time adaptive control algorithm which is suitable the systems with saturation nonlinearity at the input. The linear part of the system can be non-minimum phase and/or unstable. The control algorithm is of the self-tuning type. The algorithm utilizes an auxiliary control parameter that can be chosen online to keep the controller output in the linear zone of the saturation nonlinearity. Stability of the algorithm is discussed. Several simulation experiments are performed to demonstrate effectiveness of the algorithm. Finally, the algorithm is applied to the real time pressure tank process control system successfully.

Adaptive control of nonlinear pressure tanks using grey box modeling with neural networks

Ma Z., Jutan A.

Journal of Applied Computer Science

2000

Vol. 8, nr 2

45-63

In this work, a nonlinear process is modeled in a so called 'grey box' format. This format divides the model into a known linear part and an unknown nonlinear part. The linear part is modeled using simple linear discrete dynamics whereas the nonlinear pan is modeled using a neural network with some weights. An adaptive controller is designed to incorporate the unknown nonlinear dynamics into the overall process dynamics. A smaller number of neural network weights can be used in this format so that the controller can be used adoptively for on-line control. The effectiveness of this approach is demonstrated using simulation and finally is used for real time control of a pressure tank process with excellent results.