A fuzzy Lyapunov-based control strategy for a macro-micro manipulator

Mannani, A.; Talebi, Heidar Ali

doi:10.1109/cca.2003.1223413

Cited by 5 publications

(7 citation statements)

References 12 publications

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“…7 shows the tracking response of output in (23) using the main fuzzy term where both elements of Fig. 8, these results are significantly improved by adding the fuzzy correction terms and (18). Tables V and VI indicate that the vibration amplitude and actuators' energy consumptions are reduced by 12% and 60%, respectively, with the cost of having a slightly slower response.…”

Section: Resultsmentioning

confidence: 81%

“…Numerical simulations [18] show that for this output, the smallest eigenvalue of the matrix in (4) remains positive against the changes in . This observation together with Proposition 2, demonstrate that the main controller (9) can keep in (8) negative for a wide range of micro angles and macro deflections.…”

Section: B Definitions Of Reference Trajectory and Outputmentioning

confidence: 92%

“…tip deflection is SMALL-T Then is (18) where LARGE-T and SMALL-T are fuzzy labels measuring the tip deflection qualitatively and affects the th element of the diagonal matrix in (9) and would maintain its positive semi-definiteness. The cost we pay for less vibration is, however, a slower response.…”

Section: If Tip Deflection Is Large-t Then Is Ifmentioning

confidence: 99%

“…The usefulness of each of the previous methods depends on (usually) local information available from the plant or the environment. The parameters of the membership functions are selected based on control goals [e.g., the compromise between precision and sensitivity in defining LARGE-T in (18)] and also considering the role of each parameter in reflecting its associated physical quantity (e.g., defining and in (17) on the grounds of the available knowledge about structural damping of the flexible link). Adaptation mechanisms, which are beyond the scope of this work, may be used in each case for further refinements.…”

Section: If Tip Deflection Is Large-t Then Is Ifmentioning

confidence: 99%

“…Response of the output in (23) to the polynomial trajectory in(20) using controllers u + u +(18), all together.…”

mentioning

confidence: 99%

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A Fuzzy Lyapunov-Based Control Strategy for a Macro–Micro Manipulator: Experimental Results

Mannani

Talebi

2007

IEEE Trans. Contr. Syst. Technol.

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A class of model-free fuzzy controllers based on the Lyapunov-function reasoning is presented for a Macro-Micro Manipulator (M3) system. The control strategy uses the structural properties of the system model and assumes no other a priori knowledge about the system dynamics. Although, in general, the control structure can be regarded as a fuzzy controller, it may also be interpreted as a nonlinear multi-input multi-output (MIMO) proportional-integral-differential (PID) controller. An experimental setup consisting of a three-link M3 is considered as a practical case study. The test-bed is a nonlinear nonminimum phase MIMO system with a complex model and considerable joint frictions. Experimental results are presented to illustrate the improved performance of the proposed control strategy over a joint PD controller.

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Section: Resultsmentioning

confidence: 81%

Section: B Definitions Of Reference Trajectory and Outputmentioning

confidence: 92%

Section: If Tip Deflection Is Large-t Then Is Ifmentioning

confidence: 99%

Section: If Tip Deflection Is Large-t Then Is Ifmentioning

confidence: 99%

“…Response of the output in (23) to the polynomial trajectory in(20) using controllers u + u +(18), all together.…”

mentioning

confidence: 99%