Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356625
A. Ahmad, A. Abdelqader
Small-signal stability is a key element in the studies of dynamic performance of electric power systems. One of the main considerations in stability analysis is the low-frequency oscillations of rotor due to disturbances of which the power system is susceptible to. These oscillations may sustain and grow in magnitude to cause system separation if adequate damping is not provided, especially during using an AVR in the system. To enhance system damping, the generating unit is equipped with a power system stabilizer (PSS). Conventional PSS controllers are widely utilized in industry to damp the low-frequency inertial oscillations experienced due to disturbances. The design of such stabilizer encompasses finding the best settings of PSS parameters which yield the attainable damping response. Several design approaches and techniques have been proposed (i.e. sequential PSS design, Ha>; optimization technique, etc.) over the years. A novel genetic-algorithm (GA) based optimization approach to design a robust PSS is presented in this paper. This proposed approach employs optimization of damping factor (σ) and damping ratio () in parallel with speed deviation based performance index (IAE) optimization, to obtain the best possible time-domain results (minimum settling time, sserror, etc.). The well-known single-machine infinite bus system is used here. Simulation of the linearized system is presented. The system speed response is investigated with and without PSS. Their results are compared and show that the response of the system with PSS sustains its stability during system upsets, which means that the proposed method gives encouraging results compared with traditional methods.
{"title":"Power system stabilizer design using real-coded genetic algorithm","authors":"A. Ahmad, A. Abdelqader","doi":"10.1109/ICCIAUTOM.2011.6356625","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356625","url":null,"abstract":"Small-signal stability is a key element in the studies of dynamic performance of electric power systems. One of the main considerations in stability analysis is the low-frequency oscillations of rotor due to disturbances of which the power system is susceptible to. These oscillations may sustain and grow in magnitude to cause system separation if adequate damping is not provided, especially during using an AVR in the system. To enhance system damping, the generating unit is equipped with a power system stabilizer (PSS). Conventional PSS controllers are widely utilized in industry to damp the low-frequency inertial oscillations experienced due to disturbances. The design of such stabilizer encompasses finding the best settings of PSS parameters which yield the attainable damping response. Several design approaches and techniques have been proposed (i.e. sequential PSS design, Ha>; optimization technique, etc.) over the years. A novel genetic-algorithm (GA) based optimization approach to design a robust PSS is presented in this paper. This proposed approach employs optimization of damping factor (σ) and damping ratio () in parallel with speed deviation based performance index (IAE) optimization, to obtain the best possible time-domain results (minimum settling time, sserror, etc.). The well-known single-machine infinite bus system is used here. Simulation of the linearized system is presented. The system speed response is investigated with and without PSS. Their results are compared and show that the response of the system with PSS sustains its stability during system upsets, which means that the proposed method gives encouraging results compared with traditional methods.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120961333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356762
M. Salehi, E. Abiri, M. Jowkar
Using a MEMS pressure sensor installed at the bottom of fuel reservoirs, one can easily find the pressure of the liquid inside the reservoir and, consequently, its height. However, due to a high SI thermal coefficient, the sensor displays different voltages at its output at different temperatures and under fixed pressure. This Article examines a digital electronic system including a MEMS pressure sensor, a temperature sensor, a microcontroller and using it to remove the effect of temperature on measuring the height of the liquid inside the reservoirs. The main advantage of using the microcontroller system is the straightforward and precise use of mathematical formulas for correction of linear and even non-linear characteristics of the sensor.
{"title":"Microcontroller optimization of thermal characteristic in pezoresistive MEMS pressure sensors in height measurement in fuel reservoirs","authors":"M. Salehi, E. Abiri, M. Jowkar","doi":"10.1109/ICCIAUTOM.2011.6356762","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356762","url":null,"abstract":"Using a MEMS pressure sensor installed at the bottom of fuel reservoirs, one can easily find the pressure of the liquid inside the reservoir and, consequently, its height. However, due to a high SI thermal coefficient, the sensor displays different voltages at its output at different temperatures and under fixed pressure. This Article examines a digital electronic system including a MEMS pressure sensor, a temperature sensor, a microcontroller and using it to remove the effect of temperature on measuring the height of the liquid inside the reservoirs. The main advantage of using the microcontroller system is the straightforward and precise use of mathematical formulas for correction of linear and even non-linear characteristics of the sensor.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116593040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356814
D. Mohammed, M. Abdelkrim, K. Mokhtar, O. Abdelaziz
In a recent paper, a new discrete-time Bayesian filter, named the cubature Kalman filter (CKF), was derived. To reduce the complexity of the filter, we propose in this paper to combine the CKF with the linear Kalman filter, when either the process equation or the measurement equation is linear. The resulting filter is referred to as the Reduced CKF (RCKF). It is here applied to the problem of tracking in Cartesian coordinates a moving object whose state can be modeled by a linear dynamic equation, but whose measurement equation is non linear, due to the fact that the measurements represent position measurements in polar coordinates. The simulations results show that, in terms of root Mean Square Error (RMSE), the RCKF and CKF have the same performance, but the processing time of the RCKF is lower than that of the CKF.
{"title":"Reduced cubature Kalman filtering applied to target tracking","authors":"D. Mohammed, M. Abdelkrim, K. Mokhtar, O. Abdelaziz","doi":"10.1109/ICCIAUTOM.2011.6356814","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356814","url":null,"abstract":"In a recent paper, a new discrete-time Bayesian filter, named the cubature Kalman filter (CKF), was derived. To reduce the complexity of the filter, we propose in this paper to combine the CKF with the linear Kalman filter, when either the process equation or the measurement equation is linear. The resulting filter is referred to as the Reduced CKF (RCKF). It is here applied to the problem of tracking in Cartesian coordinates a moving object whose state can be modeled by a linear dynamic equation, but whose measurement equation is non linear, due to the fact that the measurements represent position measurements in polar coordinates. The simulations results show that, in terms of root Mean Square Error (RMSE), the RCKF and CKF have the same performance, but the processing time of the RCKF is lower than that of the CKF.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123825643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356678
A. Al-Araji, M. Abbod, H. Al-Raweshidy
This paper proposes an adaptive neural predictive controller to guide a nonholonomic wheeled mobile robot during continuous and non-continuous gradients trajectory tracking. The structure of the controller consists of two models that describe the kinematics and dynamics of the mobile robot system and a feedforward neural controller. The models are modified Elman neural network and feedforward multi-layer perceptron respectively. The trained Elman neural model acts as the position and orientation identifier. The feedforward neural controller is trained off-line and adaptive weights are adapted on-line to find the reference torques, which controls the steady-state outputs of the mobile robot system. The feedback neural controller is based on the posture neural identifier and quadratic performance index optimisation algorithm to find the optimal torque action in the transient state for N-step-ahead prediction. General back propagation algorithm is used to learn the feedforward neural controller and the posture neural identifier. Simulation results show the effectiveness of the proposed adaptive neural predictive control algorithm; this is demonstrated by the minimised tracking error and the smoothness of the torque control signal obtained with bounded external disturbances.
{"title":"Neural autopilot predictive controller for nonholonomic wheeled mobile robot based on a pre-assigned posture identifier in the presence of disturbances","authors":"A. Al-Araji, M. Abbod, H. Al-Raweshidy","doi":"10.1109/ICCIAUTOM.2011.6356678","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356678","url":null,"abstract":"This paper proposes an adaptive neural predictive controller to guide a nonholonomic wheeled mobile robot during continuous and non-continuous gradients trajectory tracking. The structure of the controller consists of two models that describe the kinematics and dynamics of the mobile robot system and a feedforward neural controller. The models are modified Elman neural network and feedforward multi-layer perceptron respectively. The trained Elman neural model acts as the position and orientation identifier. The feedforward neural controller is trained off-line and adaptive weights are adapted on-line to find the reference torques, which controls the steady-state outputs of the mobile robot system. The feedback neural controller is based on the posture neural identifier and quadratic performance index optimisation algorithm to find the optimal torque action in the transient state for N-step-ahead prediction. General back propagation algorithm is used to learn the feedforward neural controller and the posture neural identifier. Simulation results show the effectiveness of the proposed adaptive neural predictive control algorithm; this is demonstrated by the minimised tracking error and the smoothness of the torque control signal obtained with bounded external disturbances.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125261386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356654
S. Minagar, Reza Ghaderi, A. R. Noey
In this paper, a constrained model predictive controller with guaranteed stability is proposed for a PEM fuel cell. The aim is to prevent oxygen starvation by controlling the air supply system, when the control system is affected by required stack current as a measurable disturbance. The compressor voltage is controlled to regulate the oxygen excess ratio towards a desired equilibrium to avoid oxygen starvation. A dual-mode controller is utilized to guarantee input-to-state stability. In a neighborhood of the target state, the control action is generated by a local state feedback controller and outside this neighborhood model predictive control is employed. Linear Matrix Inequalities is used to obtain a terminal cost and a local state-feedback control law to satisfy MPC input-to-state stabilization conditions. A nonlinear dynamical model of PEM fuel cell is used as a simulator. Simulation results indicate that the proposed controller leads to improved stability and much less computations with respect to conventional GPC controllers.
{"title":"Constrained model predictive control of PEM fuel cell with guaranteed stability","authors":"S. Minagar, Reza Ghaderi, A. R. Noey","doi":"10.1109/ICCIAUTOM.2011.6356654","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356654","url":null,"abstract":"In this paper, a constrained model predictive controller with guaranteed stability is proposed for a PEM fuel cell. The aim is to prevent oxygen starvation by controlling the air supply system, when the control system is affected by required stack current as a measurable disturbance. The compressor voltage is controlled to regulate the oxygen excess ratio towards a desired equilibrium to avoid oxygen starvation. A dual-mode controller is utilized to guarantee input-to-state stability. In a neighborhood of the target state, the control action is generated by a local state feedback controller and outside this neighborhood model predictive control is employed. Linear Matrix Inequalities is used to obtain a terminal cost and a local state-feedback control law to satisfy MPC input-to-state stabilization conditions. A nonlinear dynamical model of PEM fuel cell is used as a simulator. Simulation results indicate that the proposed controller leads to improved stability and much less computations with respect to conventional GPC controllers.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113981679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356788
S. Kalantari, A. A. Farahani, A. Doustmohammadi, M. Menhaj, A. Suratgar, H. Talebi
In this paper, the hybrid modeling and predictive control of capsule robot (capsubot) systems are presented. First, the corresponding nonlinear state space equations are obtained from capsubot dynamics. Then, these state space equations are converted to a Piece-Wise Affine (PWA) system which is a class of hybrid systems. Next, this system is transformed to a Mixed Logical Dynamical (MLD) framework by defining binary variables representing the switching rules. At last, a Model Predictive Control (MPC) scheme is designed for this framework using a quadratic cost function resulting in a Mixed-Integer Quadratic Programming (MIQP). MPC approach excels other approaches due to its superiority in control of multivariable systems, unstable systems, non-minimum phase (NMP) systems, and systems with long delay. The main reason motivating us to use MPC for capsubot dynamics is its capability of handling constraints while reaching a desired performance. Simulation results illustrate the effectiveness of the proposed control approach.
{"title":"Hybrid model predictive control of legless piezo capsubot","authors":"S. Kalantari, A. A. Farahani, A. Doustmohammadi, M. Menhaj, A. Suratgar, H. Talebi","doi":"10.1109/ICCIAUTOM.2011.6356788","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356788","url":null,"abstract":"In this paper, the hybrid modeling and predictive control of capsule robot (capsubot) systems are presented. First, the corresponding nonlinear state space equations are obtained from capsubot dynamics. Then, these state space equations are converted to a Piece-Wise Affine (PWA) system which is a class of hybrid systems. Next, this system is transformed to a Mixed Logical Dynamical (MLD) framework by defining binary variables representing the switching rules. At last, a Model Predictive Control (MPC) scheme is designed for this framework using a quadratic cost function resulting in a Mixed-Integer Quadratic Programming (MIQP). MPC approach excels other approaches due to its superiority in control of multivariable systems, unstable systems, non-minimum phase (NMP) systems, and systems with long delay. The main reason motivating us to use MPC for capsubot dynamics is its capability of handling constraints while reaching a desired performance. Simulation results illustrate the effectiveness of the proposed control approach.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130321112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356641
S. Hosseinnia, I. Tejado, B. Vinagre, V. Milanés, J. Villagrá
Highly non-linear vehicle dynamics plays an important role in autonomous driving systems, especially in congested traffic situations at very low speeds. Due to this fact, accurate controllers are needed in order to ensure safety during navigation. In this paper, based on a previous fractional order speed control, an improved fractional order control is presented to control a commercial Citroën C3 prototype - which has automatic driving capabilities - at low speeds, which considers a hybrid model of the vehicle. Specifically, two different fractional order PIα controllers are designed to act over the throttle and brake pedals, respectively. Concerning to the uncertain dynamics of the system during the brake action parameters are tuned to design a robust controller. In addition, the system is modeled as hybrid fractional order differential inclusions. Experimental and simulation results, obtained in a real circuit, are given to demonstrate the effectiveness of the proposed strategies for cruise control at low speeds.
{"title":"Low speed control of an autonomous vehicle using a hybrid fractional order controller","authors":"S. Hosseinnia, I. Tejado, B. Vinagre, V. Milanés, J. Villagrá","doi":"10.1109/ICCIAUTOM.2011.6356641","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356641","url":null,"abstract":"Highly non-linear vehicle dynamics plays an important role in autonomous driving systems, especially in congested traffic situations at very low speeds. Due to this fact, accurate controllers are needed in order to ensure safety during navigation. In this paper, based on a previous fractional order speed control, an improved fractional order control is presented to control a commercial Citroën C3 prototype - which has automatic driving capabilities - at low speeds, which considers a hybrid model of the vehicle. Specifically, two different fractional order PIα controllers are designed to act over the throttle and brake pedals, respectively. Concerning to the uncertain dynamics of the system during the brake action parameters are tuned to design a robust controller. In addition, the system is modeled as hybrid fractional order differential inclusions. Experimental and simulation results, obtained in a real circuit, are given to demonstrate the effectiveness of the proposed strategies for cruise control at low speeds.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115390828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356809
A. Nazari, S. Moosavian, A. Hasani
In this paper, kinematics analysis and dynamic modeling of a novel spatial parallel robot is elaborated. The proposed mechanism is to be exploited in a compounded serial-parallel mobile robotic system to accomplish stabilized heavy object manipulation by a serial manipulator mounted on the parallel mechanism. In fact, this parallel mechanism has been designed to acquire a suitable maneuverability and fulfill the tipover avoidance of the aforementioned robotic system after grasping heavy objects. The proposed mechanism is made of three legs while each leg has one active degree of freedom (DOF) and consequently, the mechanism would be 3-DOF. In order to investigate this novel CRRR parallel robot, inverse kinematics of the mechanism is discussed. Next, the dynamic model of the mechanism is developed. Then, the verification of the obtained dynamic model is guaranteed utilizing two various rational maneuvers. Finally, the obtained results and remarks are concluded and the future research is expressed.
{"title":"Kinematics analysis, dynamic modeling and verification of a CRRR 3-DOF spatial parallel robot","authors":"A. Nazari, S. Moosavian, A. Hasani","doi":"10.1109/ICCIAUTOM.2011.6356809","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356809","url":null,"abstract":"In this paper, kinematics analysis and dynamic modeling of a novel spatial parallel robot is elaborated. The proposed mechanism is to be exploited in a compounded serial-parallel mobile robotic system to accomplish stabilized heavy object manipulation by a serial manipulator mounted on the parallel mechanism. In fact, this parallel mechanism has been designed to acquire a suitable maneuverability and fulfill the tipover avoidance of the aforementioned robotic system after grasping heavy objects. The proposed mechanism is made of three legs while each leg has one active degree of freedom (DOF) and consequently, the mechanism would be 3-DOF. In order to investigate this novel CRRR parallel robot, inverse kinematics of the mechanism is discussed. Next, the dynamic model of the mechanism is developed. Then, the verification of the obtained dynamic model is guaranteed utilizing two various rational maneuvers. Finally, the obtained results and remarks are concluded and the future research is expressed.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115658671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356718
B. Moaveni, H. Abdollahzadeh, M. Mazoochi
Zeta converters are the fourth-order DC-DC converters capable of operating in both step-up and step-down modes and do not suffer from the polarity reversal problem. There are many applications which require a variable output voltage commanded by an external reference signal. So, the Zeta converters can be particularly useful for such applications. To achieve a Zeta converter with adjustable output voltage capable of following an external reference signal smoothly and accurately, there will be a need for a suitable control system. Since the Zeta converter model that is used in this paper is nonlinear, we propose a combination scheme of model reference adaptive control (MRAC) with neural networks (NN). In this paper, we propose and design a neural network adaptive model reference controller to control the output voltage of Zeta converter. Simulation results show the effectiveness of the proposed scheme for the Zeta converters with adjustable output voltage.
{"title":"Adjustable output voltage Zeta converter using neural network adaptive model reference control","authors":"B. Moaveni, H. Abdollahzadeh, M. Mazoochi","doi":"10.1109/ICCIAUTOM.2011.6356718","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356718","url":null,"abstract":"Zeta converters are the fourth-order DC-DC converters capable of operating in both step-up and step-down modes and do not suffer from the polarity reversal problem. There are many applications which require a variable output voltage commanded by an external reference signal. So, the Zeta converters can be particularly useful for such applications. To achieve a Zeta converter with adjustable output voltage capable of following an external reference signal smoothly and accurately, there will be a need for a suitable control system. Since the Zeta converter model that is used in this paper is nonlinear, we propose a combination scheme of model reference adaptive control (MRAC) with neural networks (NN). In this paper, we propose and design a neural network adaptive model reference controller to control the output voltage of Zeta converter. Simulation results show the effectiveness of the proposed scheme for the Zeta converters with adjustable output voltage.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114288607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356797
H. Khorasgani, N. E. Ghiasi, A. Farshad, H. Talebi
This paper presents a methodology for trajectory control of single-link lightweight flexible manipulators. The objective is to control the trajectory of the tip position of the flexible-link manipulator in the presence of joint friction and output disturbances. Robust nonlinear approach is applied to guarantee system stability and to alleviate the degrading effects of uncertainties and nonlinearities presented in the dynamics of the system. Output redefinition is used to cancel the effects of the internal instability of the zero dynamic of the flexible-link. A drawback of this method, however, is that the controller is designed to track a new output trajectory. In fact, the difference between the tip position and new defined output could be significant and affects the tracking performance. To overcome this problem, a fuzzy compensator is employed. Simulation study and experimental results are presented to illustrate the performance of the proposed composite control strategy.
{"title":"Nonlinear robust control of flexible-link manipulator with fuzzy compensator: Experimental results","authors":"H. Khorasgani, N. E. Ghiasi, A. Farshad, H. Talebi","doi":"10.1109/ICCIAUTOM.2011.6356797","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356797","url":null,"abstract":"This paper presents a methodology for trajectory control of single-link lightweight flexible manipulators. The objective is to control the trajectory of the tip position of the flexible-link manipulator in the presence of joint friction and output disturbances. Robust nonlinear approach is applied to guarantee system stability and to alleviate the degrading effects of uncertainties and nonlinearities presented in the dynamics of the system. Output redefinition is used to cancel the effects of the internal instability of the zero dynamic of the flexible-link. A drawback of this method, however, is that the controller is designed to track a new output trajectory. In fact, the difference between the tip position and new defined output could be significant and affects the tracking performance. To overcome this problem, a fuzzy compensator is employed. Simulation study and experimental results are presented to illustrate the performance of the proposed composite control strategy.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115821546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：