Wavelet-Hybrid Feedback-Least Mean Square Algorithm for Robust Control of Structures

Adeli, Hojjat; Kim, Hong-Jin

doi:10.1061/(asce)0733-9445(2004)130:1(128)

Cited by 111 publications

(75 citation statements)

References 17 publications

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“…Because of these advantages, the proposed adaptive control algorithm can be especially effective for vibration control of large civil structures. Additional research, however, is needed (a) to investigate the effect of different parameters on the performance of the algorithm and (b) to compare it with other control algorithms such as wavelet-based vibration control algorithm of Adeli and Kim (2004) before the method can be implemented in large civil structures. …”

Section: Resultsmentioning

confidence: 99%

“…A learning algorithm based on the Lyapunov function may be used to guarantee system stability (Gao and Er, 2003;Hsu, 2007). Adeli and Kim (2004) introduced the concept of wavelet (Perez et al, 2014;Katicha et al, 2014) in structural control. They present a wavelet-hybrid feedback Least Mean Squared (LMS) algorithm for robust control of civil structures and demonstrate its effectiveness to vibration control of large irregular building structures subjected to seismic loading in an arbitrary direction (Kim and Adeli, 2005a), wind-excited motion of a 76-story building benchmark example (Kim and Adeli, 2005b), and a cable-stayed bridge subjected to seismic loading (Kim and Adeli, 2005c).…”

Section: Introductionmentioning

confidence: 99%

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Self-constructing wavelet neural network algorithm for nonlinear control of large structures

Wang

Adeli

2015

Engineering Applications of Artificial Intelligence

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Self-constructing wavelet neural network algorithm for nonlinear control of large structures

Wang

Adeli

2015

Engineering Applications of Artificial Intelligence

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“…Hybrid structures were proposed by combining the LMS method with feedback control [37,38]. The vibration isolation was improved at main frequencies and the speed of the convergence was increased, but the error over a broadband frequency range could not be managed.…”

Section: Limitationsmentioning

confidence: 99%

Enhanced Adaptive Filtering Algorithm Based on Sliding Mode Control for Active Vibration Rejection of Smart Beam Structures

Kim

Yoon

2017

Applied Sciences

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This article investigates vibration rejection for a continuous smart structure using piezoelectric bimorph patches. Such a structure has inherent nonlinearities, such as hysteresis and creep, and the whole system may experience unexpected disturbances, uncertainties, and noise from external sources. Thus, it is very important to design the active control scheme carefully with adaptive filtering systems to deal with these conditions. An advanced adaptive filtering algorithm was developed based on the conventional least mean squares (LMS) method and sliding mode control for the active vibration rejection system. The sliding mode controller is applied to the standard LMS algorithm to overcome problems with misadjustment and excess error in an optimal manner. A numerical analysis and laboratory experiment show that the technique can significantly attenuate the vibration of the smart structure at different levels and broadband frequency spectra. In addition, unidentified impedance is chosen to change the distribution of the mass, and the robustness and the adaptivity of the proposed approach are verified. The experimental results show that the method can isolate impulse-type vibrations of at least 2.8 dB, even with the adjusted mass arrangement.

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“…In the real-time implementation, the nonlinear modal control of the MDOF structure is carried out by assigning a different eigenvalue, determined by the control law given by Equations (28) and (29), to the controlled mode at every time step. In addition, if the state variables cannot be measured directly, an observer can be used for the state estimation (Spencer et al, 1994;Dyke et al, 1996;Min and Lee, 1999;Adeli and Kim, 2004;Min et al, 2003).…”

Section: Nonlinear Modal Control Algorithmmentioning

confidence: 99%

Probabilistic Approach for Nonlinear Modal Control of MDOF Structures Subjected to Multiple Excitations

Kang

Chung

Park

et al. 2005

Comp-aided Civil Eng

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A nonlinear control strategy with limited control force is applied to the modal control of the multidegree-of-freedom (MDOF) structure subjected to multiple excitations. For the modal control of the MDOF structure, a new eigenvalue assignment algorithm that modifies the dynamic characteristics of only the specific mode is proposed. For the probabilistic evaluation of the proposed nonlinear modal control, the joint probability density function (PDF) of the equivalent nonlinearly controlled single-degree-of-freedom (SDOF) system is obtained by the solution of the reduced Fokker-Planck equation for the equivalent nonlinear system. To overcome the difficulty in the application of the joint PDF to the MDOF structure controlled by the hybrid mass damper (HMD) system and subjected to multiple excitations, the equivalent damping ratio is proposed. The results of the analysis indicate that the proposed nonlinear modal control strategy is effective for the control of MDOF structures requiring a significantly smaller peak control force than the * To whom correspondence should be addressed. E-mail: kwmin@ dankook.ac.kr. linear quadratic Gaussian (LQG) controller to produce a similar control performance level.

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Wavelet-Hybrid Feedback-Least Mean Square Algorithm for Robust Control of Structures

Cited by 111 publications

References 17 publications

Self-constructing wavelet neural network algorithm for nonlinear control of large structures

Self-constructing wavelet neural network algorithm for nonlinear control of large structures

Enhanced Adaptive Filtering Algorithm Based on Sliding Mode Control for Active Vibration Rejection of Smart Beam Structures

Probabilistic Approach for Nonlinear Modal Control of MDOF Structures Subjected to Multiple Excitations

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