Variable-order stochastic adaptive control of robotic manipulators with a flexible forearm

An application of a recursive covariance lattice filter to the adaptive estimation and stochastic control of a robotic manipulator with one flexible link is presented. Not only the effective order, but also the corresponding parameters of an autoregression moving average with a bias (ARMAB) predicti...

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Bibliographic Details
Published in[Proceedings 1992] The First IEEE Conference on Control Applications pp. 168 - 173 vol.1
Main Authors Yang, Y.-P., Chu, Y.-C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1992
Subjects
Adaptive control
Adaptive estimation
Adaptive filters
Cost function
Lattices
Manipulator dynamics
Optimal control
Predictive models
Robot control
Stochastic processes
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Summary:An application of a recursive covariance lattice filter to the adaptive estimation and stochastic control of a robotic manipulator with one flexible link is presented. Not only the effective order, but also the corresponding parameters of an autoregression moving average with a bias (ARMAB) prediction model of the manipulator, are updated by a set of pure order-recursive lattice algorithms. The reduced-order prediction model that represents significant dynamics of the plant is used to generate optimal control sequences by minimizing the expectation of a weighted cost functional. In the simulations, the manipulator is modeled by the finite element method and Lagrange's equations. The performance and robustness of the variable-order stochastic adaptive controller are demonstrated by numerical results.< >
ISBN:9780780300477
0780300475
DOI:10.1109/CCA.1992.269881