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Non-linear predictive control for manufacturing and robotic applications

M.J. Grimble, Andrzej Ordys

Year
2001
Citations
13
Access
Open access

Abstract

The paper discusses predictive control algorithms in the context of applications to robotics and manufacturing systems. Special features of such systems, as compared to traditional process control applications, require that the algorithms are capable of dealing with faster dynamics, more significant unstabilities and more significant contribution of non-linearities to the system performance. The paper presents the general framework for state-space design of predictive algorithms. Linear algorithms are introduced first, then, the attention moves to non-linear systems. Methods of predictive control are presented which are based on the state-dependent state space system description. Those are illustrated on examples of rather difficult mechanical systems.

Keywords

Model predictive controlComputer scienceContext (archaeology)Control engineeringState spaceState (computer science)Process (computing)RoboticsLinear systemProcess control

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