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Jaberi S.M.,Iranian Institute of Advance Science and Technology IRAN SSP | Piltan F.,Iranian Institute of Advance Science and Technology IRAN SSP | Sahamijoo A.,Iranian Institute of Advance Science and Technology IRAN SSP | Sulaiman N.B.,University Putra Malaysia
International Journal of Bio-Science and Bio-Technology | Year: 2015

Smog hanging over cities is the most familiar and obvious form of air pollution. The effects of inhaling particulate matter have been studied in humans and animals and include asthma, lung cancer, cardiovascular issues, and premature death. There are, however, some additional products of the combustion process that include nitrogen oxides and sulfur and some un-combusted hydrocarbons, depending on the operating conditions and the fuel-air ratio. Tuning the fuel to air ratio caused to control the lung cancer. Lung cancers are tumors arising from cells lining the airways of the respiratory system. Design of a robust nonlinear controller for automotive engine can be a challenging work. This research paper focuses on the design and analysis of a high performance PID like fuzzy controller for automotive engine, in certain and uncertain condition. The proposed approach effectively combines of design methods from linear Proportional-Integral-Derivative (PID) controller and fuzzy logic theory to improve the performance, stability and robustness of the automotive engine. To solve system’s dynamic nonlinearity, the PID fuzzy logic controller is used as a PID like fuzzy logic controller. The PID like fuzzy logic controller is updated based on gain updating factor. In this methodology, fuzzy logic controller is used to estimate the dynamic uncertainties. In this methodology, PID like fuzzy logic controller is evaluated. PID like fuzzy logic controller has three inputs, Proportional (P), Derivative (D), and Integrator (I), if each inputs have N linguistic variables to defined the dynamic behavior, it has N×N×N linguistic variables. To solve this challenge, parallel structure of a PD-like fuzzy controller and PI-like fuzzy controller is evaluated. In the next step, the challenge of design PI and PD fuzzy rule tables are supposed to be solved. To solve this challenge PID like fuzzy controller is replaced by PD-like fuzzy controller with the integral term in output. This method is caused to design only PD type rule table for PD like fuzzy controller and PI like fuzzy controller. © 2015 SERSC. Source


Vosoogh M.,Iranian Institute of Advance Science and Technology IRAN SSP | Piltan F.,Iranian Institute of Advance Science and Technology IRAN SSP | Siahbazi A.,Iranian Institute of Advance Science and Technology IRAN SSP | Mirshekaran A.M.,Iranian Institute of Advance Science and Technology IRAN SSP | And 3 more authors.
International Journal of Bio-Science and Bio-Technology | Year: 2015

In this paper, a PID model-based adaptive robust control method is proposed in order to design a high performance robust controller in the presence of structured (parametric) uncertainties and unstructured uncertainties. The approach improves performance by using the advantages of sliding mode control, adaptive control, and PID controller, while the disadvantages attributed to these methods are remedied by each other. This is achieved without increasing the complexities of the overall design and analysis of the control system (controller). The proposed controller attenuates the effect of model uncertainties from both structured uncertainties and unstructured uncertainties. Thus, transient performance and final tracking accuracy is guaranteed by proper design of the controller. Therefore, asymptotic tracking (or zero final tracking error) can be achieved without using high-gain feedback. The design is conceptually simple and is reliable in applications because of its high performance and strong robustness. © 2015 SERSC. Source


Mirshekaran M.,Iranian Institute of Advance Science and Technology IRAN SSP | Piltan F.,Iranian Institute of Advance Science and Technology IRAN SSP | Sulaiman N.,Iranian Institute of Advance Science and Technology IRAN SSP | Sulaiman N.,University Putra Malaysia | And 3 more authors.
International Journal of Bio-Science and Bio-Technology | Year: 2015

Computed torque controller (CTC) is one of the types of feedback linearization nonlinear controller. This controller works very well in certain positions. However this controller has many advantages in certain conditions but it has challenges in uncertainty. The main challenge in CTC is fluctuations in uncertainties. In this research low pass filter is used to reduce the fluctuations in CTC. To improve the result of this controller intelligent CTC is recommended based on fuzzy logic engineering. In this research fuzzy logic theory is used to tune the new low pass filter CTC coefficients. The process of setting of integral intelligent Computed Torque Controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. This research is used to reduce or eliminate the computed torque controller problem based on low pass filter and fuzzy logic theory to control of flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator. © 2015 SERSC. Source


Beheshti M.,Iranian Institute of Advance Science and Technology IRAN SSP | Rahbar S.,Iranian Institute of Advance Science and Technology IRAN SSP | Davarpanah H.,Iranian Institute of Advance Science and Technology IRAN SSP | Jowkar S.,Iranian Institute of Advance Science and Technology IRAN SSP | Farzin P.,Iranian Institute of Advance Science and Technology IRAN SSP
International Journal of Bio-Science and Bio-Technology | Year: 2015

Recent development of robot technology is revolutionizing the medical field. The concept of using robot assistance in medical surgery has been receiving more and more recognition throughout the world. Robot-assisted surgery has the advantage of reducing surgeons' hand tremor, decreasing post-operative complications, reducing patients' pains, and increasing operation dexterity inside the patients' body. Robotic assistants have been broadly used in many medical fields such as orthopedics, neurology, urology and cardiology, and robot assisted surgery is keeping expanding its influences in more general medical field. Refer to this research, auxiliary sliding variable sliding mode controller is proposed for multi DOF joint with application in surgical robot manipulator. The main problem in this research is design robust chattering free sliding mode controller. The chattering phenomenon problem is reduced in certain/uncertain system by using auxiliary sliding variable. The simulation results exhibit that the sliding mode controller with auxiliary sliding variable works well in certain and uncertain condition. © 2015 SERSC. Source


Piltan F.,Iranian Institute of Advance Science and Technology IRAN SSP | Hivand Z.,Iranian Institute of Advance Science and Technology IRAN SSP | Emamzadeh S.,Iranian Institute of Advance Science and Technology IRAN SSP | Mirzaie M.,Iranian Institute of Advance Science and Technology IRAN SSP | Yarmahmoudi M.H.,Iranian Institute of Advance Science and Technology IRAN SSP
International Journal of u- and e- Service, Science and Technology | Year: 2014

This paper examines secure uncertain robot which performance is improved secure by artificial intelligence based on-line tuning method. Computed like torque (CLT) methodology is selected as a framework to construct the control law and address the better performance and reduce the error in presence of uncertainty in any trajectory. The main goal in security in any industrial factory is to guarantee acceptable trajectories tracking between the robot arm actual output and the desired input in presence of uncertainty and external disturbance. The proposed approach effectively combines the design technique from computed torque methodology is based on nonlinear stable system and fuzzy estimator to estimate the nonlinearity of undefined system dynamic in uncertain robot. The input represents the function between error and the rate of error. The outputs represent actual trajectory to improve the security, respectively. The fuzzy partly sliding switching methodology is on-line tune the computed torque like method based on adaptive methodology. The performance of the computed torque like method which controller coefficient is on-line tuned by fuzzy partly sliding switching algorithm (ACTLM) is validated the security through comparison with computed torque like methodology (CTLM). Simulation results signify good performance of trajectory in presence of uncertainty and external disturbance; it is used to show guarantee the security. © 2014 SERSC. Source

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