Improved NN-PID control of MIMO systems with PSO-based initialisation of weights
by Tarun Varshney; Satya Sheel
International Journal of Automation and Control (IJAAC), Vol. 8, No. 2, 2014

Abstract: To train the neural networks (NNs) standard back propagation (BP) algorithm and its variations are widely used where initial weights are generated as random in nature. The convergence of these algorithms is very sensitive to the initial weights. In this paper, particle swarm optimisation (PSO) algorithm has been used to initialise the weights by optimisation. Various available algorithms and the proposed one have been tested and compared for the implementation of NN-PID control of two discrete-time non-linear coupled MIMO systems. Simulation results show that the controlled performance of BP algorithm for non-linear, coupled MIMO systems can be significantly improved, with the use of PSO algorithm to initialise the weights.

Online publication date: Wed, 30-Jul-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Automation and Control (IJAAC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com