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RISS 인기검색어
- 검색키워드
- 저자 : Atefeh Chahkoutahi,Mohammad Reza MoradiPour,Mohammad Gholami,Sirous Ashja,Mohammad Hossein Rahimi (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Design High Precision Intelligent Nonlinear-Based Controller
Atefeh Chahkoutahi,Mohammad Reza MoradiPour,Mohammad Gholami,Sirous Ashja,Mohammad Hossein Rahimi 보안공학연구지원센터(IJUNESST) 2015 International Journal of u- and e- Service, Scienc Vol.8 No.1
Computed torque controller (CTC) is a significant nonlinear controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for robot manipulators, because this controller is a robust and stable. Conversely, computed torque controller is used in many applications; it has an important drawback namely; nonlinear equivalent dynamic formulation in uncertain dynamic parameter. The nonlinear equivalent dynamic formulation problem in uncertain system can be solved by using artificial intelligence theorem. However fuzzy logic controller is used to control complicated nonlinear dynamic systems, but it cannot guarantee stability and robustness. In this research parallel fuzzy logic theory is used to compensate the system dynamic uncertainty in computed torque controller.
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Intelligent Time Variation Nonlinear Fuzzy-Flatness Technique
Atefeh Chahkoutahi,Mohammad Reza MoradiPour,Mohammad Gholami,Sirous Ashja,Mohammad Hossein Rahimi 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.1
The focus of this paper is on the development and high precision robust control of an electro-mechanical robot manipulator that serves as a sensing and motion system for hybrid testing. The originality of the design is inspired from the Stewart Platform mechanism for a parallel axis configuration and a two-degree-of-freedom (2-DoF) moving platform. This design resulted in strongly non-linear and coupled dynamics as well as an inertial moving platform that attracted model-based control strategies. A novel non-linear control technique based on differential-geometric flatness was selected to meet the multiple simultaneous specification control of linearization, decoupling and asymptotic tracking. Pole placement was used to achieve a stable tracking, while the fuzzy-logic added intelligence to the control system through an automatic tuning of the pole placement coefficients. Simulation results demonstrated the validity of the fuzzy-flatness control with asymptotic and stable tracking at different frequency inputs. For the experimental implementation, the real-time constraint was further imposed and the actuators time-delay was compensated for using a forward prediction algorithm based on a fourth-order polynomial extrapolation. This compensation demonstrated a well synchronized control signal at different excitation conditions. Moreover, the non-linear flatness control was systematically assessed for the experimental validation and its implementation was made accessible for future validation and perspectives. This current research has contributed to the rapprochement of three important autonomous domains, namely: Parallel Manipulators, Hybrid Testing and Automatic Control. In addition, it has inspired many research perspectives for robust non-linear control and multi-frequency substructuring.
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Novel Adaptive Fuzzy Inference Controller for Highly Nonlinear System
Atefeh Chahkoutahi,Mohammad Hossein Rahimi,Sirous Ashja,Mohammad Gholami,Mohammad Reza Moradipour 보안공학연구지원센터 2014 International Journal of Hybrid Information Techno Vol.7 No.6
Robot manipulators are multi inputs-multi outputs, nonlinear and time variant system, therefore control of this system is the main challenge in robotic science. Control robot arm according to linear methodology are often having lots of problems because robotic systems are always highly nonlinear. Design accurate controller for robot manipulator is difficult because some dynamic parameters such as compliance and friction are not well understood and some robot parameters such as inertia are difficult to measure accurately and caused to variation in dynamic response. Fuzzy logic controllers have been applied in many applications. One of the important methods to solve above challenge is design adaptive controller based on fuzzy logic. In this paper, intelligent control of robot arm using Proportional-Integral-Derivative (PID) Adaptive Fuzzy Gain scheduling (PID-AFGS) is design for two degrees of robot arm.
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