Real-time application of a constrained predictive controller based on dynamic neural networks with feedback linearizationDeng, J., Becerra, V., Stobart, R. and Zhong, S. (2011) Real-time application of a constrained predictive controller based on dynamic neural networks with feedback linearization. In: 18th IFAC World Congress, August 28 - September 2, 2011, Milano (Italy), pp. 6727-6732. Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. Abstract/SummaryThis paper describes an experimental application of constrained predictive control and feedback linearisation based on dynamic neural networks. It also verifies experimentally a method for handling input constraints, which are transformed by the feedback linearisation mappings. A performance comparison with a PID controller is also provided. The experimental system consists of a laboratory based single link manipulator arm, which is controlled in real time using MATLAB/SIMULINK together with data acquisition equipment.
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