Technical Report Available

[E. Tzirkel-Hancock]

The following report has been placed in the neuroprose archives at
Ohio State University:

		    STABLE CONTROL OF NONLINEAR  
	           SYSTEMS USING NEURAL NETWORKS

		Eli Tzirkel-Hancock & Frank Fallside

	        Technical Report CUED/F-INFENG/TR.81 

	             Cambridge University
		    Engineering Department 
		      Trumpington Street 
		       Cambridge CB2 1PZ 
			    England 

                            Abstract

A neural network based direct control architecture is presented, 
that achieves output tracking for a class of continuous time nonlinear 
plants, for which the nonlinearities are unknown. The controller employs 
neural networks to perform approximate input/output plant linearization. 
The network parameters are adapted according to a stability principle. 
The architecture is based on a modification of a method previously 
proposed by the authors, where the modification comprises adding a 
sliding control term to the controller. This modification serves two 
purposes: first, as suggested by Sanner and Slotine, sliding control
compensates for plant uncertainties outside the state region where the 
networks are used, thus providing global stability; second, the sliding 
control compensates for inherent network approximation errors, hence 
improving tracking performance. 

A complete stability and tracking error convergence proof is given and 
the setting of the controller parameters is discussed. It is demonstrated 
that as a result of using sliding control, better use of the network's 
approximation ability can be achieved, and the asymptotic tracking error 
can be made dependent only on inherent network approximation errors and 
the frequency range of unmodeled dynamical modes. Two simulations are 
provided to demonstrate the features of the control method. 


************************ How to obtain a copy ************************

a) via FTP:

% ftp archive.cis.ohio-state.edu
..
Name (archive.cis.ohio-state.edu): anonymous
Password: neuron
ftp> cd pub/neuroprose
ftp> binary
ftp> get tzirkel.control_tr81.ps.Z
ftp> quit
% uncompress tzirkel.control_tr81.ps.Z
% lp         tzirkel.control_tr81.ps

b) via postal mail:

Request a hardcopy from

Eli Tzirkel, et at eng.cam.ac.uk
Speech Laboratory
Cambridge University Engineering Department 
Trumpington Street, Cambridge CB2 1PZ 
England