L. Jetto et al., ADAPTIVE DEAD-BEAT CONTROL LAW FOR TRAJECTORY TRACKING OF ROBOTIC MANIPULATORS, International journal of adaptive control and signal processing, 8(6), 1994, pp. 587-604
Citations number
37
Categorie Soggetti
Controlo Theory & Cybernetics","Robotics & Automatic Control","Engineering, Eletrical & Electronic
The purpose of this paper is to propose an adaptive dead-beat controll
er for the trajectory tracking of a robotic manipulator. The dead-beat
compensator is self-tuned to a linearized discretized model whose par
ameters are identified on-line through a Kalman-like estimator. To imp
rove the convergence of the estimator and to obtain good control perfo
rmances even in the case of time-varying parameters, the state covaria
nce matrix of the Kalman filter is adapted to the observed statistics
of the innovation process. Numerical results have been obtained in a s
imulation context and refer to various operating conditions. They show
that very good control performances in terms of maximum error are rea
lly obtainable. A comparison with minimum variance control is also rep
orted.