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  • In Jour Smart Sensing And Intelligent Systems

 

Research Article | 01-June-2017

OUTPUT BASED INPUT SHAPING FOR OPTIMAL CONTROL OF SINGLE LINK FLEXIBLE MANIPULATOR

quadratic regulator (LQR) and PID separately for position and residual vibration control. The Robustness of these control algorithms are tested by changing the payloads from 0g to30g, 50g and 70g in each case. Based on MATLAB simulation results and time response analysis, LQR-OBF outperformed the PID-OBF in both tracking and vibration reduction.

Nura Musa Tahir, Sabo Miya Hassan, Zaharuddin Mohamed, Ahmed Garba Ibrahim

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 2, 367–386

Article | 06-November-2017

MODELING AND CONTROL OF BALL AND BEAM SYSTEM USING MODEL BASED AND NON-MODEL BASED CONTROL APPROACHES

the noise of the sensor in the experimental setup, a state observer is designed to observe the velocity of the ball. In order to compare the performance of the LQR and study the effect of simplifying assumptions, two control strategies are designed and implemented: Proportional Derivative Integral (PID) as non-model based control strategy, hybrid PID and Linear Quadratic Regulator (LQR) as combination of model based and non-model based control strategies. The experimental results of this research

Mohammad Keshmiri, Ali Fellah Jahromi, Abolfazl Mohebbi, Mohammad Hadi Amoozgar, Wen-Fang Xie

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 1, 14–35

Research paper | 01-September-2011

PERFECT TRACKING CONTROL WITH DISCRETE-TIME LQR FOR A NON-MINIMUM PHASE ELECTRO-HYDRAULIC ACTUATOR SYSTEM

This paper presents a perfect tracking control for discrete-time nonminimum phase of electro-hydraulic servo (EHS) system by adopting a combination of feedback and feedforward controller. A linear-quadratic-regulator (LQR) is firstly design as a feedback controller and a feedforward controller is then proposed to eliminate the phase error emerge by the LQR controller during the tracking control. The feedforward controller is develop by implementing the zero phase error tracking control (ZPETC

R. Ghazali, Y. M. Sam, M.F. Rahmat, Zulfatman, A. W. I. M. Hashim

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 3, 424–439

Article | 01-September-2012

MODELING AND CONTROLLER DESIGN OF PNEUMATIC ACTUATOR SYSTEM WITH CONTROL VALVE

mathematical model of pneumatic actuator system and for controller design. Data collection of input and output signal of the system has been performed from experiment procedure. This data is used for estimate the model by selecting Auto-Regressive Exogenous (ARX) model as a model structure. The accepted model is based validation test namely as residual correlation, Akaike Final Prediction Error and best fit percentage. Different control schemes such as PID and LQR (Linear Quadratic Regulator) have been

W.K. Lai, M.F. Rahmat, N. Abdul Wahab

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 3, 624–644

Research Article | 20-February-2013

FEED FORWARD LINEAR QUADRATIC CONTROLLER DESIGN FOR AN INDUSTRIAL ELECTRO HYDRAULIC ACTUATOR SYSTEM WITH SERVO VALVE

for model estimation and Auto Regressive with eXogeneous input (ARX) model is chosen as model structure of the system. Based on the input and output data of the system, best fit criterion and correlation analysis of the residual is analyzed to determine the adequate model to represent the EHA system. Once the model is obtained, discrete PID and feed forward plus Linear Quadratic Regulator (LQR) controller is developed to improve the performance and position tracking performance of EHA system. In

J. Micheal, M.F. Rahmat, N. Abdul Wahab, W.K. Lai

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 1, 155–170

Article | 16-December-2013

RESEARCH ON LONGITUDINAL CONTROL ALGORITHM FOR FLYING WING UAV BASED ON LQR TECHNOLOGY

Linear Quadratic Regulator (LQR) is widely used in many practical engineering fields due to good stability margin and strong robustness. But there is little literature reports the technology that has been used to control the flying wing unmanned aerial vehicles (UAV). In this paper, aiming at the longitudinal static and dynamic characteristics of the flying wing UAV, LQR technology will be introduced to the flying wing UAV flight control. The longitudinal stability augmentation control law and

Yibo Li, Chao Chen, Wei Chen

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 5, 2155–2181

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