Active tendons control of structures using block pulse functions

Ghaffarzadeh, Hosein; Younespour, Amir

doi:10.1002/stc.1656

Cited by 16 publications

(6 citation statements)

References 30 publications

(27 reference statements)

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“…Active tendon systems consist of prestressed tendons located on each floor where active control is delivered by actuators which adjust the level of tension in the tendons. Active tendon systems have been tested in small laboratory scale [10], full scale testing [11], as well as studied numerically [12]. Figure 7a shows the configuration of the 3-storey active scissor-jack system while Fig.…”

Section: Numerical Studymentioning

confidence: 99%

Active scissor-jack for seismic risk mitigation of building structures

2019

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Active vibration control systems involve sensing and actuation systems to be integrated into a structure. The actuator generates control forces based on sensed external excitation and system response and applies forces directly to the structure in order to reduce its seismic response. One major obstacle with the active vibration control technique is that very large actuator power is often required. This paper studies the effects of positioning an actuator in a scissor-jack configuration within a structural frame. Based on its geometries, the governing equation of motion is derived. A classical optimal control algorithm determines control forces. In a numerical example, a three-level multi-degree of freedom system frame equipped with scissor-jack actuators is compared to an active-tendon system with the same structural characteristics. The results indicate that peak actuator force reduces by 92%. The results indicate that by using the proposed configuration, significant reduction of control forces can be achieved, implying that a much smaller actuator can be used.

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Section: Numerical Studymentioning

confidence: 99%

Active scissor-jack for seismic risk mitigation of building structures

2019

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“…The comparison of the sliding mode controller without a chattering problem with PID was performed by Guclu [16]. The comparison of the block pulse functions with the linear quadratic regulator was proposed by Ghaffarzadeh and Younespour [17]. The comparison of a wavelet-based adaptive pole assignment with the linear quadratic regulator was proposed and the system was optimized via active tuned mass dampers via metaheuristics [18].…”

Section: Introductionmentioning

confidence: 99%

Performance of Optimum Tuned PID Controller with Different Feedback Strategies on Active-Controlled Structures

et al. 2021

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In this study, multi-story structures with different combinations (on each floor and only the first floor) of active tendon control systems driven by a proportional–integral–derivative (PID) controller were actively controlled. The PID parameters, Kp (proportional gain), Td (derivative gain), and Ti (integral gain) for each structure, were optimally tuned by using both the harmony search algorithm (HS) and flower pollination algorithm (FPA), which are metaheuristic algorithms. In two different active-controlled structures, which are formed according to the position of the PID, the structural responses under near-fault records defined in FEMA P-695 are examined to determine the appropriate feedback which was applied for displacement, velocity, acceleration, and total acceleration. The performance of the different feedback strategies on these two active-controlled structures is evaluated. As a result, the acceleration feedback is suitable for all combinations of the active control system with a PID controller. The HS algorithm outperforms the optimum results found according to the FPA.

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“…Meanwhile, vibration mitigation and performance enhancement of nonlinear systems under excitations have drawn the attention of researchers recently . The necessity of reducing vibrations with various control systems including passive, active, and semiactive has made the researchers to develop different control schemes. However, the key element in obtaining a favorable performance in systems is to select a proper control strategy.…”

Section: Introductionmentioning

confidence: 99%

Orthogonal function‐based equivalent linearization for sliding mode control of nonlinear systems

Baghaei

Ghaffarzadeh

Younespour

2019

Struct Control Health Monit

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This paper proposes the equivalent linearization (EL) and sliding mode control (SMC) methods to address nonlinearity and enhance the performance of nonlinear systems subjected to nonstationary random excitations. The EL methods are commonly used to propose approximate solutions for nonlinear systems under random excitations due to the high computational demands in the exact analyses. Considering the application of orthogonal functions in improving the accuracy and efficiency of approximate solutions, an orthogonal block pulse (BP) function is applied to the EL method in this study to approximate the nonlinear system responses under nonstationary random excitations. The SMC, as a robust control method for systems with uncertainties and external disturbances, is capable of achieving reliable and accurate tracking control. This method is applied to effectively reduce the dynamic responses predicted by the proposed EL method under nonstationary random excitations. The proposed approach is tested on single-degreeof-freedom and two-degree-of-freedom Duffing systems subjected to a seismic type excitation. The results indicate that not only the orthogonal functionbased EL method can approximate the dynamic responses more accurately, at lower computational cost, and by a high agreement with the exact solution, but also the proposed SMC can improve the performance of nonlinear systems by effectively reducing the responses compared with the linear quadratic regulator control method.KEYWORDS block pulse functions, equivalent linearization, nonlinearity, sliding mode control Nomenclature: A, plant matrix of the system; B,B u , control location matrices; B r , excitation orientation vector; C,C eq , damping matrix and its equivalent value; E[·], mathematical expectation; g, nonlinear function of displacement and velocity; h, unit impulse-response function; J, cost function; J G ,J F , convolution operational matrix; K,K eq , stiffness matrix and its equivalent value; k, linear stiffness; M, mass matrix; m, positive integer value; P, sliding surface coefficient vector; Q,R, positive semidefinite and definite weighting matrices; q, width of block pulse

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Active tendons control of structures using block pulse functions

Cited by 16 publications

References 30 publications

Active scissor-jack for seismic risk mitigation of building structures

Active scissor-jack for seismic risk mitigation of building structures

Performance of Optimum Tuned PID Controller with Different Feedback Strategies on Active-Controlled Structures

Orthogonal function‐based equivalent linearization for sliding mode control of nonlinear systems

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