Adaptive extended Kalman filter for parameter tracking of base-isolated structure under unknown seismic input

Polóni

2014

Shock and Vibration

This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

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Section: Laboratory Hardware and Experimental Settingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

Polóni

2014

Shock and Vibration

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“…The use of the extended Kalman filter for the estimation of vibration dynamics is, with a few exceptions, limited to offline a posteriori system identification procedures. Realtime application of EKF for diagnostics and monitoring is presented by Lourens et al [26] for disturbance force estimation and by Mu et al [27] for the monitoring of structures under seismic loads, stiffness, and damping coefficient estimation in automotive applications [28] and for the adaptive control of torsional vibration in a two-mass rotating drive system [29,30]. While Williams suggested the use of unscented EKF to assess damage and damage location based on accelerometer measurements [31], the work is limited to offline numerical studies.…”

Section: Introductionmentioning

confidence: 99%

“…(7)Approximate the damped natural frequencŷ( ) of the beam according to(26). (8)If the frequency estimatê( ) is outside the tolerance band in(27), enable the fault detection signal ( ) . (9) At the next sample restart the procedure from 1, use the estimates from Step 6.…”

mentioning

confidence: 99%

Online Structural Health Monitoring and Parameter Estimation for Vibrating Active Cantilever Beams Using Low-Priced Microcontrollers

Vachálek

2015

Shock and Vibration

This paper presents a structural health monitoring and parameter estimation system for vibrating active cantilever beams using low-cost embedded computing hardware. The actuator input and the measured position are used in an augmented nonlinear model to observe the dynamic states and parameters of the beam by the continuous-discrete extended Kalman filter (EKF). The presence of undesirable structural change is detected by variations of the first resonance estimate computed from the observed equivalent mass, stiffness, damping, and voltage-force conversion coefficients. A fault signal is generated upon its departure from a predetermined nominal tolerance band. The algorithm is implemented using automatically generated and deployed machine code on an electronics prototyping platform, featuring an economically feasible 8-bit microcontroller unit (MCU). The validation experiments demonstrate the viability of the proposed system to detect sudden or gradual mechanical changes in real-time, while the functionality on low-cost miniaturized hardware suggests a strong potential for mass-production and structural integration. The modest computing power of the microcontroller and automated code generation designates the proposed system only for very flexible structures, with a first dominant resonant frequency under 4 Hz; however, a code-optimized version certainly allows much stiffer structures or more complicated models on the same hardware.

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“…On the other side, adaptive control designs in vibration control feature self-tuning minimum variance control [Zhang et al, 2013], model reference adaptive control (MRAC) [Trajkov et al, 2008] and others. Literature research reveals that the use of EKF for vibration control is centered mainly on parameter or disturbance force identification [Lourens et al, 2012] and structural diagnostics [Mu et al, 2013], however, in the work of Szabat and Orlowska-Kowalska [2008] the role of EKF shifts from the background to serve as the means of online identification for adaptive control.…”

Section: Introductionmentioning

confidence: 99%

Adaptive predictive control of transient vibrations of cantilevers with changing weight

Polóni

IFAC Proceedings Volumes

2014