Pub Date : 2011-12-01DOI: 10.1109/ICCIAUTOM.2011.6356815
K. Salahshoor, M. Hajisalehi, M. H. Sefat
In recent years, carbon capture and storage (CCS) has been recognized as a promising technology to achieve a considerable reduction of greenhouse gas emissions from large local industries. Among different methods of CCS, carbon dioxide (CO2) sequestration in underground saline aquifers has gained much attention due to its long-term storage and low cost benefits. This type of sequestration, however, poses over-pressurization as a potential risk. This paper aims at effective monitoring of critical parameters which directly impact the CO2 sequestration performance due to over-pressurization and cap rock failure. A synthetic reservoir model is simulated in reservoir simulator (ECLIPSE-100) environment and an online fuzzy model is identified using an evolving Takagi Sugeno (eTS) algorithm. The approach recursively develops an evolving fuzzy rule-base model structure with linear rule antecedent parts using Recursive Least-Squares (RLS) parameter estimation to track reservoir dynamic changes during the CO2 sequestration. Suitability of the presented adaptive identification approach in modeling CO2 sequestration dynamic performance in an underground saline aquifer is verified via various test studies.
{"title":"Online identification of evolved Takagi Sugeno fuzzy model for CO2 sequestration process","authors":"K. Salahshoor, M. Hajisalehi, M. H. Sefat","doi":"10.1109/ICCIAUTOM.2011.6356815","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356815","url":null,"abstract":"In recent years, carbon capture and storage (CCS) has been recognized as a promising technology to achieve a considerable reduction of greenhouse gas emissions from large local industries. Among different methods of CCS, carbon dioxide (CO2) sequestration in underground saline aquifers has gained much attention due to its long-term storage and low cost benefits. This type of sequestration, however, poses over-pressurization as a potential risk. This paper aims at effective monitoring of critical parameters which directly impact the CO2 sequestration performance due to over-pressurization and cap rock failure. A synthetic reservoir model is simulated in reservoir simulator (ECLIPSE-100) environment and an online fuzzy model is identified using an evolving Takagi Sugeno (eTS) algorithm. The approach recursively develops an evolving fuzzy rule-base model structure with linear rule antecedent parts using Recursive Least-Squares (RLS) parameter estimation to track reservoir dynamic changes during the CO2 sequestration. Suitability of the presented adaptive identification approach in modeling CO2 sequestration dynamic performance in an underground saline aquifer is verified via various test studies.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"79 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":"116344866","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.2011.6356632
H. S. Ousaloo
The present paper deals with the multi-axis attitude maneuver of a small satellite with variable inertia matrix, using fuzzy logic strategy. The controller has been realized by means of a Multi Input Multi Output (MIMO) fuzzy controller with a knowledge base composed by 75 logic rules (25 logic rules for per axis). The input-domains are partitioned with 5 membership functions, resulting in 25 fuzzy rules for each rule-base. The output-domains are partitioned with 7 membership functions. The Mamdani controllers use a standard max-min inference process and a fast center of area method to calculate the crisp control signals. The satellite control is obtained autonomously by the fuzzy controller generating commands to the hybrid actuators. The actuator set combined from magnetorquers and reaction wheel to facilitate three axes maneuver. Using hybrid actuators solve the singularity problem that often occurs in active magnetic control methods. IGRF2000 was used as earth magnetic field simulation. Effects of the environmental disturbances during Attitude maneuver of the SC have been considered by developing a disturbance torques simulator module. The main features of the proposed control strategy are: simplicity in spacecraft control system design and development, increased robustness for automatic control reconfiguration and model uncertainty, reduction in development and production cost for flight control systems, autonomous on-board control features. Numerical simulations show the capabilities of the proposed approaches compared to the other classical methods (PD) such as quaternion feedback and Euler Angles feedback control laws.
{"title":"Attitude control of a small satellite with uncertainly dynamic model using fuzzy logic strategy","authors":"H. S. Ousaloo","doi":"10.1109/ICCIAUTOM.2011.6356632","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356632","url":null,"abstract":"The present paper deals with the multi-axis attitude maneuver of a small satellite with variable inertia matrix, using fuzzy logic strategy. The controller has been realized by means of a Multi Input Multi Output (MIMO) fuzzy controller with a knowledge base composed by 75 logic rules (25 logic rules for per axis). The input-domains are partitioned with 5 membership functions, resulting in 25 fuzzy rules for each rule-base. The output-domains are partitioned with 7 membership functions. The Mamdani controllers use a standard max-min inference process and a fast center of area method to calculate the crisp control signals. The satellite control is obtained autonomously by the fuzzy controller generating commands to the hybrid actuators. The actuator set combined from magnetorquers and reaction wheel to facilitate three axes maneuver. Using hybrid actuators solve the singularity problem that often occurs in active magnetic control methods. IGRF2000 was used as earth magnetic field simulation. Effects of the environmental disturbances during Attitude maneuver of the SC have been considered by developing a disturbance torques simulator module. The main features of the proposed control strategy are: simplicity in spacecraft control system design and development, increased robustness for automatic control reconfiguration and model uncertainty, reduction in development and production cost for flight control systems, autonomous on-board control features. Numerical simulations show the capabilities of the proposed approaches compared to the other classical methods (PD) such as quaternion feedback and Euler Angles feedback control laws.","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":"122132711","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.2011.6356746
S. Alavi, A. Akbarzadeh, A. Farughian
This paper presents an Auto-tuning Smith-Predictive Proportional + Integral + Derivative (PID) controller based on Model Reference Adaptive System (MRAS). The Model Reference Adaptive Control employs the MIT rule to set the PID controller parameters on line. Smith-Predictive Control (SPC) is implied to predict the behavior of the system for presented time-delay system. Combination of the adaptive techniques and smith-predictive PID controller results, compared with classical smith-predictive PID which is tuned via Ziegler-Nichols (Z-N) method.
{"title":"Auto-tuning Smith-Predictive control of three-tanks system based on model Reference Adaptive System","authors":"S. Alavi, A. Akbarzadeh, A. Farughian","doi":"10.1109/ICCIAUTOM.2011.6356746","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356746","url":null,"abstract":"This paper presents an Auto-tuning Smith-Predictive Proportional + Integral + Derivative (PID) controller based on Model Reference Adaptive System (MRAS). The Model Reference Adaptive Control employs the MIT rule to set the PID controller parameters on line. Smith-Predictive Control (SPC) is implied to predict the behavior of the system for presented time-delay system. Combination of the adaptive techniques and smith-predictive PID controller results, compared with classical smith-predictive PID which is tuned via Ziegler-Nichols (Z-N) method.","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":"117231060","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.2011.6356631
H. Hosseini, B. Tusi, Navid Razmjooy, M. Khalilpoor
Progressing of the demand for electrical energy leads to loading the transmission system close to their limits which may leads to LFO happening. Low frequency oscillations (LFO) in power system usuallyhappen because of lack of damping torque to overcome disturbances in power system such as changes in mechanical power. Due to the existence of the low frequency oscillation (LFO), the transmission power of AC lines is limited and the system angle stability is affected. In this paper the Parameters of the classic PSS and SVC internal AC and DC voltage controllers are designed in order to damp the Low Frequency Oscillations (LFO). The design of PSS and SVC parameters is considered as an optimization problem and Hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for searching optimized parameters. The results of the simulation show that the SVC with PID controllers is more effective in damping LFO compared to PSS with PID controllers.
{"title":"Optimum design of PSS and SVC controller for damping low frequency oscillation (LFO)","authors":"H. Hosseini, B. Tusi, Navid Razmjooy, M. Khalilpoor","doi":"10.1109/ICCIAUTOM.2011.6356631","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356631","url":null,"abstract":"Progressing of the demand for electrical energy leads to loading the transmission system close to their limits which may leads to LFO happening. Low frequency oscillations (LFO) in power system usuallyhappen because of lack of damping torque to overcome disturbances in power system such as changes in mechanical power. Due to the existence of the low frequency oscillation (LFO), the transmission power of AC lines is limited and the system angle stability is affected. In this paper the Parameters of the classic PSS and SVC internal AC and DC voltage controllers are designed in order to damp the Low Frequency Oscillations (LFO). The design of PSS and SVC parameters is considered as an optimization problem and Hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for searching optimized parameters. The results of the simulation show that the SVC with PID controllers is more effective in damping LFO compared to PSS with PID controllers.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"34 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":"125888584","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.2011.6356831
Hamid Behzad, H. T. Shandiz, A. Noori, T. Abrishami
This paper is concerned with fractional identification of state space model of continuous time MIMO systems. The methodology used in this paper involves a continuous-time fractional operator allowing to find fractional derivatives of the stochastic input - output data which are treated in time domain and identifying the state space matrices of the system using QR factorization. There are many advantages in describing a physical system using fractional CT models in that the dynamic behavior of the system is, in actuality, inherently fractional. The efficacy of the approach is examined by comparing with other approaches using integer identification.
{"title":"Robot identification using fractional subspace method","authors":"Hamid Behzad, H. T. Shandiz, A. Noori, T. Abrishami","doi":"10.1109/ICCIAUTOM.2011.6356831","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356831","url":null,"abstract":"This paper is concerned with fractional identification of state space model of continuous time MIMO systems. The methodology used in this paper involves a continuous-time fractional operator allowing to find fractional derivatives of the stochastic input - output data which are treated in time domain and identifying the state space matrices of the system using QR factorization. There are many advantages in describing a physical system using fractional CT models in that the dynamic behavior of the system is, in actuality, inherently fractional. The efficacy of the approach is examined by comparing with other approaches using integer identification.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"54 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":"126898767","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.2011.6356690
M. Bahrami, A. Imani, A. Ghanbari, B. Ebrahimi
In this Paper, in order to improve the performance of sliding mode controller, a fuzzy logic sliding mode controller is proposed. The slope of sliding surface is changed based on error and its derivative by a fuzzy logic and reached to the predetermined slope. This decreases reaching phase and speeds up system's response, and with increasing the slope of the sliding surface, final tracking error decreases. For eliminating the chattering phenomenon, instead of using saturation function, a fuzzy logic algorithm based on surface function is designed. So chattering problem as a result of uncertainty and disturbance is eliminated. In both fuzzy logics, Mamdani-type fuzzy inference is used. Proposed controller is applied to control of a nonlinear MEMS optical switch which is subjected to disturbance. The performance of this controller is compared to sliding mode controller which has same parameters and simulation results indicate the superior performance of the proposed controller.
{"title":"Robust control of a MEMS optical switch using fuzzy sliding mode","authors":"M. Bahrami, A. Imani, A. Ghanbari, B. Ebrahimi","doi":"10.1109/ICCIAUTOM.2011.6356690","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356690","url":null,"abstract":"In this Paper, in order to improve the performance of sliding mode controller, a fuzzy logic sliding mode controller is proposed. The slope of sliding surface is changed based on error and its derivative by a fuzzy logic and reached to the predetermined slope. This decreases reaching phase and speeds up system's response, and with increasing the slope of the sliding surface, final tracking error decreases. For eliminating the chattering phenomenon, instead of using saturation function, a fuzzy logic algorithm based on surface function is designed. So chattering problem as a result of uncertainty and disturbance is eliminated. In both fuzzy logics, Mamdani-type fuzzy inference is used. Proposed controller is applied to control of a nonlinear MEMS optical switch which is subjected to disturbance. The performance of this controller is compared to sliding mode controller which has same parameters and simulation results indicate the superior performance of the proposed controller.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"572 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":"123159682","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.2011.6356836
M. Toosi, A. Maleki, A. Fallah
This paper describes the use of a feed-forward neural network for estimating and anticipating elbow joint angle. The method is based on mapping between six different combinations of muscles electromyographic signals (EMG) along with kinematics of the shoulder joint and the flexion/extension angle of elbow joint in four planar movements. Mean square error and cross correlation were used as quantitative criteria to reflect the performance of the method. We succeed to anticipate the future elbow angle up to 150 ms which is doing for the first time. For the most complete input combination which had also the best results, the cross correlation criterion between desired and anticipated splines for four movements respectively was %99.87, %99.90, %98.10 and %99.95.
{"title":"Estimation and anticipation of elbow joint angle from shoulder data during planar movements","authors":"M. Toosi, A. Maleki, A. Fallah","doi":"10.1109/ICCIAUTOM.2011.6356836","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356836","url":null,"abstract":"This paper describes the use of a feed-forward neural network for estimating and anticipating elbow joint angle. The method is based on mapping between six different combinations of muscles electromyographic signals (EMG) along with kinematics of the shoulder joint and the flexion/extension angle of elbow joint in four planar movements. Mean square error and cross correlation were used as quantitative criteria to reflect the performance of the method. We succeed to anticipate the future elbow angle up to 150 ms which is doing for the first time. For the most complete input combination which had also the best results, the cross correlation criterion between desired and anticipated splines for four movements respectively was %99.87, %99.90, %98.10 and %99.95.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"25 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":"123185541","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.2011.6356735
H. Shirinabadi, H. Talebi
In this paper, stability analysis for Partial Differential Equation systems is investigated using lyapunov stability theorem. Both parabolic and hyperbolic PDEs as representatives of heat and wave equations will be considered, respectively. we also consider Ginzburg-Landau equation a kind of complex valued PDE. The condition for asymptotic stability will be obtained using the presented analysis.
{"title":"Lyapunov stability analysis of special class of PDE systems","authors":"H. Shirinabadi, H. Talebi","doi":"10.1109/ICCIAUTOM.2011.6356735","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356735","url":null,"abstract":"In this paper, stability analysis for Partial Differential Equation systems is investigated using lyapunov stability theorem. Both parabolic and hyperbolic PDEs as representatives of heat and wave equations will be considered, respectively. we also consider Ginzburg-Landau equation a kind of complex valued PDE. The condition for asymptotic stability will be obtained using the presented analysis.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"30 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":"126539267","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.2011.6356761
M. Kia, K. R. Rezayieh, R. Taherkhani
Applications of BLDC (Brushless Direct Current) motors are increasing each day. Air conditioners, electric pumps, fans, printers, robots, electric bikes, doors, windows, sun roofs, seats, mixers, food processors, blenders, vacuum cleaners, toothbrushes, razors, coffee grinders, etc. BLDC motors are most commonly used in easy to drive, high speed and long life applications. They have become widespread and are available in all shapes and sizes from large-scale industrial models to small motors for light applications (such as 12 V BLDC motors). In some cases it is needed to have a feedback of the motor's rotational speed in order to control it. Common speed meters use hall-effect sensors to measure the exact speed of the motor; and some kinds of BLDC motors include these sensors inside to give to the controller board. Nevertheless in some places it is hard or even impossible to locate these sensors around motor. Here we present a simple method for measuring the speed of a BLDC motor using simple electronic elements and a low cost microcontroller unit for measuring and transferring data. The main idea is to measure the frequency of the voltage between two phases of the motor; as we know the rotational speed of a BLDC motor is proportional to the phase signal frequency generated by the driver.
{"title":"A novel method for measuring rotational speed of BLDC motors using voltage feedback","authors":"M. Kia, K. R. Rezayieh, R. Taherkhani","doi":"10.1109/ICCIAUTOM.2011.6356761","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356761","url":null,"abstract":"Applications of BLDC (Brushless Direct Current) motors are increasing each day. Air conditioners, electric pumps, fans, printers, robots, electric bikes, doors, windows, sun roofs, seats, mixers, food processors, blenders, vacuum cleaners, toothbrushes, razors, coffee grinders, etc. BLDC motors are most commonly used in easy to drive, high speed and long life applications. They have become widespread and are available in all shapes and sizes from large-scale industrial models to small motors for light applications (such as 12 V BLDC motors). In some cases it is needed to have a feedback of the motor's rotational speed in order to control it. Common speed meters use hall-effect sensors to measure the exact speed of the motor; and some kinds of BLDC motors include these sensors inside to give to the controller board. Nevertheless in some places it is hard or even impossible to locate these sensors around motor. Here we present a simple method for measuring the speed of a BLDC motor using simple electronic elements and a low cost microcontroller unit for measuring and transferring data. The main idea is to measure the frequency of the voltage between two phases of the motor; as we know the rotational speed of a BLDC motor is proportional to the phase signal frequency generated by the driver.","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":"121405024","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.2011.6356688
M. Azimi, M. Beheshti, A. Badpa, H. S. Nejad
This paper concerns the tracking control problem for a class of nonlinear networked control systems (NCSs) with external disturbances. A Takagi-Sugeno fuzzy model is employed to represent the nonlinear controlled plant in the NCSs. Both network-induced delay and packet dropout are addressed. The control scheme is based on a parallel distributed compensation (PDC) structure, a fuzzy observer and a H∞ performance to attenuate the external disturbances. The stability of the whole closed-loop model is investigated using a general Lyapunov-Krasovskii functional. The key point of the proposed approaches is to achieve conditions under a linear matrix inequalities (LMI) formulation in the case of a disturbed T-S fuzzy model. This formulation facilitates obtaining solutions through interior point optimization methods for some nonlinear NCSs tracking problems. A numerical example is used to illustrate the validity of the design methodology.
{"title":"A new T-S fuzzy observer based controller for nonlinear NCSs","authors":"M. Azimi, M. Beheshti, A. Badpa, H. S. Nejad","doi":"10.1109/ICCIAUTOM.2011.6356688","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356688","url":null,"abstract":"This paper concerns the tracking control problem for a class of nonlinear networked control systems (NCSs) with external disturbances. A Takagi-Sugeno fuzzy model is employed to represent the nonlinear controlled plant in the NCSs. Both network-induced delay and packet dropout are addressed. The control scheme is based on a parallel distributed compensation (PDC) structure, a fuzzy observer and a H∞ performance to attenuate the external disturbances. The stability of the whole closed-loop model is investigated using a general Lyapunov-Krasovskii functional. The key point of the proposed approaches is to achieve conditions under a linear matrix inequalities (LMI) formulation in the case of a disturbed T-S fuzzy model. This formulation facilitates obtaining solutions through interior point optimization methods for some nonlinear NCSs tracking problems. A numerical example is used to illustrate the validity of the design methodology.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"212 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":"123022887","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}
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