Joint Estimation of Nonlinear Dynamics and Resistance Torque for Integrated Motor-Transmission Systems via Switched ℓ<sub>∞</sub> Observers With Smoothness Guarantee

Pan, Juntao; Nguyen, Anh‐Tu; Lai, Weilong; Zhu, Xiaoyuan; Huang, Hailong

doi:10.1109/tsmc.2023.3297064

Cited by 1 publication

(1 citation statement)

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“…The peak value of the disturbance signal can be described by the L ∞ norm, which means that the L ∞ norm can be used as the performance criterion for control synthesis to minimize the upper bound of the continuously bounded disturbance when considering the control problem of a system with persistent disturbance [22]. At present, there are relevant studies on the L ∞ method [23]- [25]. In [23], the optimal L ∞ -gain of the stabilization problem for T-S fuzzy systems is acquired.…”

Section: Introductionmentioning

confidence: 99%

Tracking Control Design for Takagi-Sugeno Fuzzy Systems Based on Membership Function-Dependent L∞ Performance

Yang,

Li,

et al. 2023

IEEE Access

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The design of tracking control based on membership function-dependent L ∞ performance for the systems, which are described by the Takagi-Sugeno fuzzy models, is considered. In practice, most Takagi-Sugeno fuzzy systems have such a characteristic that they work on some local subsystems most of the time and on others less time. Taking advantage of this feature, an L ∞ performance index dependent on membership function is proposed, through which better performance may be guaranteed for those local subsystems that work most of the time. By means of the newly defined L ∞ performance index, the measurable premise variables, the estimation of immeasurable premise variables, and the estimation of nonlinear function, an observer-based tracking controller is designed in the form of linear matrix inequalities, which makes full use of the information of measurable premise variables. Finally, an example is provided to verify the effectiveness of the proposed approach. In the simulation, compared with the traditional L ∞ control method, the novel method has better robust tracking performance.INDEX TERMS L ∞ control, Membership function-dependent, Observer-based tracking controller, Takagi-Sugeno fuzzy system.

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Section: Introductionmentioning

confidence: 99%

Tracking Control Design for Takagi-Sugeno Fuzzy Systems Based on Membership Function-Dependent L∞ Performance

Yang,

Li,

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

Joint Estimation of Nonlinear Dynamics and Resistance Torque for Integrated Motor-Transmission Systems via Switched ℓ_∞ Observers With Smoothness Guarantee

Cited by 1 publication

References 38 publications

Tracking Control Design for Takagi-Sugeno Fuzzy Systems Based on Membership Function-Dependent L∞ Performance

Tracking Control Design for Takagi-Sugeno Fuzzy Systems Based on Membership Function-Dependent L∞ Performance

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Joint Estimation of Nonlinear Dynamics and Resistance Torque for Integrated Motor-Transmission Systems via Switched ℓ∞ Observers With Smoothness Guarantee

Cited by 1 publication

References 38 publications

Tracking Control Design for Takagi-Sugeno Fuzzy Systems Based on Membership Function-Dependent L∞ Performance

Tracking Control Design for Takagi-Sugeno Fuzzy Systems Based on Membership Function-Dependent L∞ Performance

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Joint Estimation of Nonlinear Dynamics and Resistance Torque for Integrated Motor-Transmission Systems via Switched ℓ_∞ Observers With Smoothness Guarantee