Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation
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. D...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2014/741765 |
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| _version_ | 1832552134404472832 |
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| author | Gergely Takács Tomáš Polóni Boris Rohal’-Ilkiv |
| author_facet | Gergely Takács Tomáš Polóni Boris Rohal’-Ilkiv |
| author_sort | Gergely Takács |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-0f4383bcdf6f437caa1a5111ace21e96 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-0f4383bcdf6f437caa1a5111ace21e962025-02-03T05:59:20ZengWileyShock and Vibration1070-96221875-92032014-01-01201410.1155/2014/741765741765Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter EstimationGergely Takács0Tomáš Polóni1Boris Rohal’-Ilkiv2Slovak University of Technology in Bratislava, Faculty of Mechanical Engineering, Institute of Automation, Measurement and Applied Informatics, Nám Slobody 17, 812 31 Bratislava 1, SlovakiaSlovak University of Technology in Bratislava, Faculty of Mechanical Engineering, Institute of Automation, Measurement and Applied Informatics, Nám Slobody 17, 812 31 Bratislava 1, SlovakiaSlovak University of Technology in Bratislava, Faculty of Mechanical Engineering, Institute of Automation, Measurement and Applied Informatics, Nám Slobody 17, 812 31 Bratislava 1, SlovakiaThis 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.http://dx.doi.org/10.1155/2014/741765 |
| spellingShingle | Gergely Takács Tomáš Polóni Boris Rohal’-Ilkiv Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation Shock and Vibration |
| title | Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation |
| title_full | Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation |
| title_fullStr | Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation |
| title_full_unstemmed | Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation |
| title_short | Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation |
| title_sort | adaptive model predictive vibration control of a cantilever beam with real time parameter estimation |
| url | http://dx.doi.org/10.1155/2014/741765 |
| work_keys_str_mv | AT gergelytakacs adaptivemodelpredictivevibrationcontrolofacantileverbeamwithrealtimeparameterestimation AT tomaspoloni adaptivemodelpredictivevibrationcontrolofacantileverbeamwithrealtimeparameterestimation AT borisrohalilkiv adaptivemodelpredictivevibrationcontrolofacantileverbeamwithrealtimeparameterestimation |