CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities
Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system paramete...
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| Autor*in: |
Shafik, Amro [verfasserIn] Abdelhameed, Magdy [verfasserIn] Kassem, Ahmed [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Umfang: |
1 Online-Ressource |
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| Übergeordnetes Werk: |
Enthalten in: International journal of manufacturing, materials, and mechanical engineering - Hershey, Pa : IGI Global, 2011, 4(2014), 2, Seite 47-72 |
|---|---|
| Übergeordnetes Werk: |
volume:4 ; year:2014 ; number:2 ; pages:47-72 |
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| DOI / URN: |
10.4018/ijmmme.2014040104 |
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NLEJ251821617 |
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| 520 | |a Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals | ||
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| 700 | 1 | |a Abdelhameed, Magdy |e verfasserin |4 aut | |
| 700 | 1 | |a Kassem, Ahmed |e verfasserin |4 aut | |
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10.4018/ijmmme.2014040104 doi (DE-627)NLEJ251821617 (VZGNL)10.4018/ijmmme.2014040104 DE-627 ger DE-627 rakwb eng Shafik, Amro verfasserin aut CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities 2014 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals CMAC Electrohydraulic Hybrid Control Nonlinearities PV Abdelhameed, Magdy verfasserin aut Kassem, Ahmed verfasserin aut Enthalten in International journal of manufacturing, materials, and mechanical engineering Hershey, Pa : IGI Global, 2011 4(2014), 2, Seite 47-72 Online-Ressource (DE-627)NLEJ244419337 (DE-600)2703520-7 2156-1672 nnns volume:4 year:2014 number:2 pages:47-72 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 4 2014 2 47-72 |
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10.4018/ijmmme.2014040104 doi (DE-627)NLEJ251821617 (VZGNL)10.4018/ijmmme.2014040104 DE-627 ger DE-627 rakwb eng Shafik, Amro verfasserin aut CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities 2014 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals CMAC Electrohydraulic Hybrid Control Nonlinearities PV Abdelhameed, Magdy verfasserin aut Kassem, Ahmed verfasserin aut Enthalten in International journal of manufacturing, materials, and mechanical engineering Hershey, Pa : IGI Global, 2011 4(2014), 2, Seite 47-72 Online-Ressource (DE-627)NLEJ244419337 (DE-600)2703520-7 2156-1672 nnns volume:4 year:2014 number:2 pages:47-72 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 4 2014 2 47-72 |
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10.4018/ijmmme.2014040104 doi (DE-627)NLEJ251821617 (VZGNL)10.4018/ijmmme.2014040104 DE-627 ger DE-627 rakwb eng Shafik, Amro verfasserin aut CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities 2014 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals CMAC Electrohydraulic Hybrid Control Nonlinearities PV Abdelhameed, Magdy verfasserin aut Kassem, Ahmed verfasserin aut Enthalten in International journal of manufacturing, materials, and mechanical engineering Hershey, Pa : IGI Global, 2011 4(2014), 2, Seite 47-72 Online-Ressource (DE-627)NLEJ244419337 (DE-600)2703520-7 2156-1672 nnns volume:4 year:2014 number:2 pages:47-72 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 4 2014 2 47-72 |
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10.4018/ijmmme.2014040104 doi (DE-627)NLEJ251821617 (VZGNL)10.4018/ijmmme.2014040104 DE-627 ger DE-627 rakwb eng Shafik, Amro verfasserin aut CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities 2014 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals CMAC Electrohydraulic Hybrid Control Nonlinearities PV Abdelhameed, Magdy verfasserin aut Kassem, Ahmed verfasserin aut Enthalten in International journal of manufacturing, materials, and mechanical engineering Hershey, Pa : IGI Global, 2011 4(2014), 2, Seite 47-72 Online-Ressource (DE-627)NLEJ244419337 (DE-600)2703520-7 2156-1672 nnns volume:4 year:2014 number:2 pages:47-72 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 4 2014 2 47-72 |
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10.4018/ijmmme.2014040104 doi (DE-627)NLEJ251821617 (VZGNL)10.4018/ijmmme.2014040104 DE-627 ger DE-627 rakwb eng Shafik, Amro verfasserin aut CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities 2014 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals CMAC Electrohydraulic Hybrid Control Nonlinearities PV Abdelhameed, Magdy verfasserin aut Kassem, Ahmed verfasserin aut Enthalten in International journal of manufacturing, materials, and mechanical engineering Hershey, Pa : IGI Global, 2011 4(2014), 2, Seite 47-72 Online-Ressource (DE-627)NLEJ244419337 (DE-600)2703520-7 2156-1672 nnns volume:4 year:2014 number:2 pages:47-72 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijmmme.2014040104&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 4 2014 2 47-72 |
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Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals |
| abstractGer |
Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals |
| abstract_unstemmed |
Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals |
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CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities |
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Abdelhameed, Magdy Kassem, Ahmed |
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