Parametric identification of a servo-hydraulic actuator for real-time hybrid simulation

Qian, Yili; Ou, Ge; Maghareh, Amin; Dyke, Shirley J.

doi:10.1016/j.ymssp.2014.03.001

Cited by 43 publications

(32 citation statements)

References 13 publications

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“…The equations describing the fluid flow rate q in an actuator can be linearized about the origin to obtain the following equations: where F a , , V, A a , K q , i, K c , x, and x 1 indicate actuator force, bulk modulus of the fluid, half the volume of the actuator, piston area, valve flow gain, valve input, leakage coefficient, and actuator displacement and velocity, respectively. 2,4,[11][12][13][14][15] By combining Equations (1) and (2), and solving for . F a , the following expression is obtained:…”

Section: Nonlinear Dynamics Of the Control Plantmentioning

confidence: 99%

A Self‐tuning Robust Control System for nonlinear real‐time hybrid simulation

Maghareh

Dyke

Silva

2020

Earthq Engng Struct Dyn

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In a real-time hybrid simulation, a transfer system is used to enforce the interface interaction between computational and physical substructures. A model-based, multilayer nonlinear control system is developed to accommodate extensive performance variations and uncertainties in a physical substructure. The aim of this work is to extend the application of real-time hybrid simulation to investigating failure, nonlinearity, and nonstationary behavior. This Self-tuning Robust Control System (SRCSys) consists of two layers: robustness and adaptation. The robustness layer synthesizes a nonlinear control law such that the closed-loop dynamics perform as intended under a broad range of parametric and nonparametric uncertainties. Sliding mode control is employed as the control scheme in this layer. Then, the adaptation layer reduces uncertainties at run time through slow and controlled learning of the control plant. The tracking performance of the SRCSys is evaluated in two experiments that have highly uncertain physical specimens.

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Section: Nonlinear Dynamics Of the Control Plantmentioning

confidence: 99%

A Self‐tuning Robust Control System for nonlinear real‐time hybrid simulation

Maghareh

Dyke

Silva

2020

Earthq Engng Struct Dyn

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“…In particular, r(u, v, s) is the nonlinear restoring force vector while g(u, v, s) is a nonlinear function that describes the evolution of the additional state variable s; m is the mass matrix, and f(t) is the external time varying load while I and 0 are identity and zero matrices, respectively. When (10) and (11) refer to a linear system, no additional state variable s enters the state vector Y, and the restoring force is defined as,…”

Section: Time Integration Algorithmmentioning

confidence: 99%

A model‐order reduction framework for hybrid simulation based on component‐mode synthesis

Miraglia

Petrović

Abbiati

et al. 2020

Earthq Engng Struct Dyn

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Testing of stiff physical substructures (PSs) still poses major technical issues that prevent from adopting hybrid simulation (HS) as a standard structural testing method. Firstly, elastic deformation of reaction frames, as well as the limited resolution of displacement transducers, deteriorate displacement control accuracy. Secondly, as a consequence of control errors, small perturbations of actuator displacements entail large restoring force oscillations that spuriously excite the higher eigenmodes of the hybrid model. For this reason, in the current practice, force-controlled hydraulic jacks handle vertical degrees of freedom, which are typically associated with stiff axially loaded members and excluded from the time integration loop. Vertical forces are either kept constant or adjusted during the experiment based on simplified redistribution rules. Besides deterioration of displacement control accuracy, stiff PSs naturally increase the frequency bandwidth of the hybrid model, whose higher eigenfrequencies (divided by the testing time scale) may fall outside the frequency bandwidth of the actuation system, thus destabilizing the HS. This is a collateral issue to which, in the authors' knowledge, no sufficient attention as been dedicated yet, and this paper tries to address it. From this standpoint, we propose component-mode synthesis as a rigorous approach for deriving reduced-order physical and numerical substructure mass and stiffness matrices that minimize the frequency bandwidth of the hybrid model. The proposed methodology allowed for performing HSs of a load-bearing unreinforced masonry structure including both horizontal and vertical degrees of freedom with a standard three-actuator setup used for cyclic testing.

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“…For the servo‐hydraulic actuator system, many linear and nonlinear models have been proposed to the date . MTS Systems Corporation has developed a detailed Simulink model to be used for MTS manufactured servo‐hydraulic actuators and is available in OpenFresco's source code for different static and dynamic actuators.…”

Section: Vrths Frameworkmentioning

confidence: 99%

“…An all computational hybrid simulation, in which all the components are modeled numerically, is called virtual hybrid simulation . Virtual hybrid simulation often involves numerical modeling of dynamic test system to realistically predict potential issues and challenges that may appear in an actual hybrid test and is critical before the implementation of hybrid experiments. In this paper, virtual real‐time hybrid simulation (vRTHS) of the previously mentioned benchmark building, which combines a numerical model of the MR damper and dynamic test system in Matlab/Simulink with an OpenSees model of the rest of the structure, using OpenFresco as a middleware, is chosen as the simulation methodology.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive nonlinear seismic performance assessment of MR damper controlled systems using virtual real‐time hybrid simulation

Ghaffary

Mohammadi

2019

Structural Design Tall Build

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Summary Magnetorheological (MR) dampers have gained significant attention in seismic mitigation of structural systems due to their distinguished characteristics such as inherent stability and minimum power requirements. Their performance in control of nonlinear structural response, however, has not been widely investigated. This paper provides comprehensive nonlinear seismic performance assessment of a three‐story benchmark structure equipped with a large‐scale MR damper using virtual real‐time hybrid simulation to efficiently capture the nonlinear behavior of the damper. The framework is first verified by means of available experimental results of an actual RTHS on the same structural system. A set of 12 earthquake ground motions, each one scaled to have 12 different intensities are then utilized to perform nonlinear dynamic analyses. An energy‐based adaptive passive‐on control strategy is proposed, and its performance is compared with passive‐on, passive‐off, and uncontrolled response of the structure in terms of interstory drifts shown by fragility curves, residual drifts, MR damper control force, and the ability to maintain a uniform interstory drift along the height of the structure.

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Parametric identification of a servo-hydraulic actuator for real-time hybrid simulation

Cited by 43 publications

References 13 publications

A Self‐tuning Robust Control System for nonlinear real‐time hybrid simulation

A Self‐tuning Robust Control System for nonlinear real‐time hybrid simulation

A model‐order reduction framework for hybrid simulation based on component‐mode synthesis

Comprehensive nonlinear seismic performance assessment of MR damper controlled systems using virtual real‐time hybrid simulation

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