Description: A method is presented for augmenting an extended
Kalman filter with an adaptive element. The resulting estimator
provides robustness to parameter uncertainty and unmodeled
dynamics.-A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics . Platform: |
Size: 339059 |
Author:rifer |
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Description: A method is presented for augmenting an extended
Kalman filter with an adaptive element. The resulting estimator
provides robustness to parameter uncertainty and unmodeled
dynamics.-A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics . Platform: |
Size: 338944 |
Author:rifer |
Hits:
Description: This paper presents two kinds of adaptive control schemes for robot manipulator which has the parametric uncertainties. In order to compensate these uncertainties, we use the FLS (fuzzy logic system) that has the capability to approximate any nonlinear function over the compact input space. In the proposed control schemes, we need not derive the linear formulation of robot dynamic equation and tune the parameters. We also suggest the robust adaptive control laws in all proposed schemes for decreasing the effect of approximation error. To reduce the number of fuzzy rules of the FLS, we consider the properties of robot dynamics and the decomposition of the uncertainty function. The proposed controllers are robust not only to the structured uncertainty such as payload parameter, but also to the unstructured one such as friction model and disturbance. The validity of the control scheme is shown by computer simulations of a two-link planar robot manipulator. Platform: |
Size: 641024 |
Author:Diamant |
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Search - adaptive parameter uncertainty