Based on the T-S fuzzy model,this paper presents a new model of non-linear network control system with stochastic transfer delay.Sufficient criterion is proposed to guarantee globally asymptotically stability of this ...Based on the T-S fuzzy model,this paper presents a new model of non-linear network control system with stochastic transfer delay.Sufficient criterion is proposed to guarantee globally asymptotically stability of this two-levels T-S fuzzy model.Also a T-S fuzzy observer of NCS is designed base on this two-levels T-S fuzzy model.All these results present a new approach for networked control system analysis and design.展开更多
This paper mainly talks about a popular approach of volatility of a GARCH-type model in R, while the disturbances are independent and have identical Student-t distribution. It uses the Metropolis-Hastings method to pe...This paper mainly talks about a popular approach of volatility of a GARCH-type model in R, while the disturbances are independent and have identical Student-t distribution. It uses the Metropolis-Hastings method to perform the computations and gives the programs in details in R.展开更多
The coordination behavior of 2,3-butanedionemonoxime Girard’s T hydrazone (L<sup>1</sup>) towards Hg<sup>2+</sup> ion has been investigated. The structure of Hg<sup>2+</sup> comple...The coordination behavior of 2,3-butanedionemonoxime Girard’s T hydrazone (L<sup>1</sup>) towards Hg<sup>2+</sup> ion has been investigated. The structure of Hg<sup>2+</sup> complex, [Hg(L<sup>1</sup>)Cl]Cl·5H<sub>2</sub>O, is elucidated using elemental analyses, spectral (IR, UV-visible, 1H-NMR and mass) and TGA measurements. IR spectrum suggests that L<sup>1</sup> behaves in a bidentate manner through the azomethine groups. The molecular modeling of L<sup>1</sup> and its Hg<sup>2+</sup> complex has been investigated. The bond lengths, bond angles, HOMO and LUMO have been calculated. The thermal behavior and kinetic parameters are determined using Coats-Redfern method. The use of L<sup>1</sup> for preconcentration and separation via flotation of Hg<sup>2+</sup> complex and determination using cold vapor atomic spectrometry (CVAAS) is described. The effects on the percentage of recovered Hg<sup>2+</sup> by pH of sample solutions, oleic acid (HOL) concentration, Hg<sup>2+</sup> and L<sup>1</sup> concentrations are studied in details. The method is applied for the determination of the total Hg<sup>2+</sup> (mg·mL<sup>-1</sup>) in natural water samples.展开更多
Ship-mounted container cranes are challenging industrial applications of nonlinear pendulum-like systems with oscillating disturbance which can cause them unstable.Since wave-induced ship motion causes the hoisted con...Ship-mounted container cranes are challenging industrial applications of nonlinear pendulum-like systems with oscillating disturbance which can cause them unstable.Since wave-induced ship motion causes the hoisted container to swing during the transfer operation,the swing motion may be dangerously large and the operation must be stopped.In order to reduce payload pendulation of ship-mounted crane,nonlinear dynamics of ship-mounted crane is derived and a control method using T-S fuzzy model is proposed.Simulation results are given to illustrate the validity of the proposed design method and pendulation of ship-mounted crane is reduced significantly.展开更多
In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) f...In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.展开更多
A constrained generalized predictive control (GPC) algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno (T-S) fuzzy model based on the fuzzy cluster algorithm and th...A constrained generalized predictive control (GPC) algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno (T-S) fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.展开更多
BACKGROUND: Neuronal loss, synapse mutilation, and increasing malnourished axons are pathologically related to Alzheimer's disease. Microtubule-associated protein 2 (MAP2) is of importance for neuronal, axonal, an...BACKGROUND: Neuronal loss, synapse mutilation, and increasing malnourished axons are pathologically related to Alzheimer's disease. Microtubule-associated protein 2 (MAP2) is of importance for neuronal, axonal, and dendritic generation, extension, and stabilization, as well as for the regulation of synaptic plasticity. OBJECTIVE: To investigate the antagonistic effects of natural-cerebrolysin-containing serum on beta amyloid protein 1-40 (Aβ1-40)-induced neurotoxicity from the standpoints of cell proliferation, synaptogenesis, and cytoskeleton formation (MAP2 expression). DESIGN, TIME AND SETTING: A paralleled, controlled, neural cell, and molecular biology experiment was performed at the Institute of Integrated Chinese and Western Medicine, Shenzhen Hospital, Southern Medical University between February 2006 and April 2008. MATERIALS: PC12 cells, derived from the rat central nervous system, were purchased from Shanghai Institute of Cell Biology, Chinese Academy of Sciences, China. A β1-40 was provided by Sigma, USA. Natural-cerebrolysin was provided by Shenzhen Institute of Integrated Chinese and Western Medicine, China. The natural-cerebrolysin was predominantly composed of Renshen (Radix Ginseng), Tianma (Rhizoma Gastrodiae), and Yixingye (Ginkgo Leaf) in a proportion of 1:2:2. Following conventional water extraction technology, an extract (1:20) was prepared. Each gram of extract equaled 20 grams of crude drug. In a total of 12 adult male New Zealand rabbits, six underwent intragastric administration of natural-cerebrolysin extract for 1 month to prepare natural-cerebrolysin-containing serum, and the remaining six rabbits received intragastric administration of physiological saline to prepare normal blank serum. METHODS: An AIzheimer's disease in vitro model was induced in PC12 cells using Aβ1-40. The cells were incubated with varying doses of natural-cerebrolysin-containing serum (2.5%, 5%, and 10%). Normal blank serum-treated PC12 cells served as a blank control group. MAIN OUTCOME MEASURES: Through the use of inverted phase contrast microscope, cell morphology and neurite growth were observed, neurite length was measured, and the percentage of neurite-positive cells was calculated. Cell proliferation rate was determined by MTT assay, and MAP 2 expression was detected by fluorescent immunocytochemistry. RESULTS: Following Aβ1-40 treatments, some PC12 cells were apoptotic/dying, and only a few short neurites were observed. Following interventions with natural-cerebrolysin-containing serum, the PC12 cells proliferated, there was an increased number of neurites, and neurite length was enhanced. After middle- and high-dose natural-cerebrolysin treatments, the percentage of neurite-positive cells, as well as the average length of neurites, was significantly greater than the normal blank serum-treated PC12 cells (P 〈 0.05 or P 〈 0.01). Compared with the blank control group, MAP2 expression in the Aβ1-40-treated PC12 cells was significantly inhibited, and the cell proliferation rate was significantly decreased (P 〈 0.01). Following incubations with natural-cerebrolysin-containing serum, MAP2 expression and cell proliferation rate in the PC12 cells were significantly increased in a dose-dependent manner, compared with treatments with blank control serum (P 〈 0.05 or P 〈 0.01 ). CONCLUSION: Natural-cerebrolysin exhibited antagonistic effects on neurotoxicity in Aβ1-40 induced Alzheimer's disease in vitro models. These effects were likely related to cell proliferation and the upregulation of intracellular MAP2 expression.展开更多
A multilayer recurrent fuzzy neural network(MRFNN)is proposed for accurate dynamic system modeling.The proposed MRFNN has six layers combined with T-S fuzzy model.The recurrent structures are formed by local feedback ...A multilayer recurrent fuzzy neural network(MRFNN)is proposed for accurate dynamic system modeling.The proposed MRFNN has six layers combined with T-S fuzzy model.The recurrent structures are formed by local feedback connections in the membership layer and the rule layer.With these feedbacks,the fuzzy sets are time-varying and the temporal problem of dynamic system can be solved well.The parameters of MRFNN are learned by chaotic search(CS)and least square estimation(LSE)simultaneously,where CS is for tuning the premise parameters and LSE is for updating the consequent coefficients accordingly.Results of simulations show the proposed approach is effective for dynamic system modeling with high accuracy.展开更多
In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive fun...In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.展开更多
The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digita...The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.展开更多
A new robust proportional-integral-derivative (PID) tracking control framework is considered for stochastic systems with non-Gaussian variable based on B-spline neural network approximation and T-S fuzzy model ident...A new robust proportional-integral-derivative (PID) tracking control framework is considered for stochastic systems with non-Gaussian variable based on B-spline neural network approximation and T-S fuzzy model identification. The tracked object is the statistical information of a given target probability density function (PDF), rather than a deterministic signal. Following B-spline approximation to the integrated performance function, the concerned problem is transferred into the tracking of given weights. Different from the previous related works, the time delay T-S fuzzy models with the exogenous disturbances are applied to identify the nonlinear weighting dynamics. Meanwhile, the generalized PID controller structure and the improved convex linear matrix inequalities (LMI) algorithms are proposed to fulfil the tracking problem. Furthermore, in order to enhance the robust performance, the peak-to-peak measure index is applied to optimize the tracking performance. Simulations are given to demonstrate the efficiency of the proposed approach.展开更多
Pressure ripples in electric power steering (EPS) systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise...Pressure ripples in electric power steering (EPS) systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno (T-S) fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation (PDC) structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality (LMI) problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.展开更多
基金National Natural Science Foundation of china(60274014,60574088)
文摘Based on the T-S fuzzy model,this paper presents a new model of non-linear network control system with stochastic transfer delay.Sufficient criterion is proposed to guarantee globally asymptotically stability of this two-levels T-S fuzzy model.Also a T-S fuzzy observer of NCS is designed base on this two-levels T-S fuzzy model.All these results present a new approach for networked control system analysis and design.
文摘This paper mainly talks about a popular approach of volatility of a GARCH-type model in R, while the disturbances are independent and have identical Student-t distribution. It uses the Metropolis-Hastings method to perform the computations and gives the programs in details in R.
文摘The coordination behavior of 2,3-butanedionemonoxime Girard’s T hydrazone (L<sup>1</sup>) towards Hg<sup>2+</sup> ion has been investigated. The structure of Hg<sup>2+</sup> complex, [Hg(L<sup>1</sup>)Cl]Cl·5H<sub>2</sub>O, is elucidated using elemental analyses, spectral (IR, UV-visible, 1H-NMR and mass) and TGA measurements. IR spectrum suggests that L<sup>1</sup> behaves in a bidentate manner through the azomethine groups. The molecular modeling of L<sup>1</sup> and its Hg<sup>2+</sup> complex has been investigated. The bond lengths, bond angles, HOMO and LUMO have been calculated. The thermal behavior and kinetic parameters are determined using Coats-Redfern method. The use of L<sup>1</sup> for preconcentration and separation via flotation of Hg<sup>2+</sup> complex and determination using cold vapor atomic spectrometry (CVAAS) is described. The effects on the percentage of recovered Hg<sup>2+</sup> by pH of sample solutions, oleic acid (HOL) concentration, Hg<sup>2+</sup> and L<sup>1</sup> concentrations are studied in details. The method is applied for the determination of the total Hg<sup>2+</sup> (mg·mL<sup>-1</sup>) in natural water samples.
基金work supported by Changwon National University in 2011-2012work partly supported by the second stage of Brain Korea 21 Projects
文摘Ship-mounted container cranes are challenging industrial applications of nonlinear pendulum-like systems with oscillating disturbance which can cause them unstable.Since wave-induced ship motion causes the hoisted container to swing during the transfer operation,the swing motion may be dangerously large and the operation must be stopped.In order to reduce payload pendulation of ship-mounted crane,nonlinear dynamics of ship-mounted crane is derived and a control method using T-S fuzzy model is proposed.Simulation results are given to illustrate the validity of the proposed design method and pendulation of ship-mounted crane is reduced significantly.
基金This work was supported by Young Scientists Fundamental Research Program of Shandong Province of China (No. 031B5147).
文摘In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.
基金This Project was supported by the National Natural Science Foundation of China (60374037 and 60574036)the Opening Project Foundation of National Lab of Industrial Control Technology (0708008).
文摘A constrained generalized predictive control (GPC) algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno (T-S) fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.
基金Supported by:Scientific and Technological Foundation of the National Administration of Traditional Chinese Medicine of China,No.02-03LP41the Scientific and Technological Key Project of Guangdong Province,No. 2006B35630007
文摘BACKGROUND: Neuronal loss, synapse mutilation, and increasing malnourished axons are pathologically related to Alzheimer's disease. Microtubule-associated protein 2 (MAP2) is of importance for neuronal, axonal, and dendritic generation, extension, and stabilization, as well as for the regulation of synaptic plasticity. OBJECTIVE: To investigate the antagonistic effects of natural-cerebrolysin-containing serum on beta amyloid protein 1-40 (Aβ1-40)-induced neurotoxicity from the standpoints of cell proliferation, synaptogenesis, and cytoskeleton formation (MAP2 expression). DESIGN, TIME AND SETTING: A paralleled, controlled, neural cell, and molecular biology experiment was performed at the Institute of Integrated Chinese and Western Medicine, Shenzhen Hospital, Southern Medical University between February 2006 and April 2008. MATERIALS: PC12 cells, derived from the rat central nervous system, were purchased from Shanghai Institute of Cell Biology, Chinese Academy of Sciences, China. A β1-40 was provided by Sigma, USA. Natural-cerebrolysin was provided by Shenzhen Institute of Integrated Chinese and Western Medicine, China. The natural-cerebrolysin was predominantly composed of Renshen (Radix Ginseng), Tianma (Rhizoma Gastrodiae), and Yixingye (Ginkgo Leaf) in a proportion of 1:2:2. Following conventional water extraction technology, an extract (1:20) was prepared. Each gram of extract equaled 20 grams of crude drug. In a total of 12 adult male New Zealand rabbits, six underwent intragastric administration of natural-cerebrolysin extract for 1 month to prepare natural-cerebrolysin-containing serum, and the remaining six rabbits received intragastric administration of physiological saline to prepare normal blank serum. METHODS: An AIzheimer's disease in vitro model was induced in PC12 cells using Aβ1-40. The cells were incubated with varying doses of natural-cerebrolysin-containing serum (2.5%, 5%, and 10%). Normal blank serum-treated PC12 cells served as a blank control group. MAIN OUTCOME MEASURES: Through the use of inverted phase contrast microscope, cell morphology and neurite growth were observed, neurite length was measured, and the percentage of neurite-positive cells was calculated. Cell proliferation rate was determined by MTT assay, and MAP 2 expression was detected by fluorescent immunocytochemistry. RESULTS: Following Aβ1-40 treatments, some PC12 cells were apoptotic/dying, and only a few short neurites were observed. Following interventions with natural-cerebrolysin-containing serum, the PC12 cells proliferated, there was an increased number of neurites, and neurite length was enhanced. After middle- and high-dose natural-cerebrolysin treatments, the percentage of neurite-positive cells, as well as the average length of neurites, was significantly greater than the normal blank serum-treated PC12 cells (P 〈 0.05 or P 〈 0.01). Compared with the blank control group, MAP2 expression in the Aβ1-40-treated PC12 cells was significantly inhibited, and the cell proliferation rate was significantly decreased (P 〈 0.01). Following incubations with natural-cerebrolysin-containing serum, MAP2 expression and cell proliferation rate in the PC12 cells were significantly increased in a dose-dependent manner, compared with treatments with blank control serum (P 〈 0.05 or P 〈 0.01 ). CONCLUSION: Natural-cerebrolysin exhibited antagonistic effects on neurotoxicity in Aβ1-40 induced Alzheimer's disease in vitro models. These effects were likely related to cell proliferation and the upregulation of intracellular MAP2 expression.
文摘A multilayer recurrent fuzzy neural network(MRFNN)is proposed for accurate dynamic system modeling.The proposed MRFNN has six layers combined with T-S fuzzy model.The recurrent structures are formed by local feedback connections in the membership layer and the rule layer.With these feedbacks,the fuzzy sets are time-varying and the temporal problem of dynamic system can be solved well.The parameters of MRFNN are learned by chaotic search(CS)and least square estimation(LSE)simultaneously,where CS is for tuning the premise parameters and LSE is for updating the consequent coefficients accordingly.Results of simulations show the proposed approach is effective for dynamic system modeling with high accuracy.
基金Project(2007AA04Z162) supported by the National High-Tech Research and Development Program of ChinaProjects(2006T089, 2009T062) supported by the University Innovation Team in the Educational Department of Liaoning Province, China
文摘In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.
基金Project(E2015203354)supported by Natural Science Foundation of Steel United Research Fund of Hebei Province,ChinaProject(ZD2016100)supported by the Science and the Technology Research Key Project of High School of Hebei Province,China+1 种基金Project(LJRC013)supported by the University Innovation Team of Hebei Province Leading Talent Cultivation,ChinaProject(16LGY015)supported by the Basic Research Special Breeding of Yanshan University,China
文摘The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.
基金supported by National Natural Science Foundationof China (No. 60472065, No. 60774013).
文摘A new robust proportional-integral-derivative (PID) tracking control framework is considered for stochastic systems with non-Gaussian variable based on B-spline neural network approximation and T-S fuzzy model identification. The tracked object is the statistical information of a given target probability density function (PDF), rather than a deterministic signal. Following B-spline approximation to the integrated performance function, the concerned problem is transferred into the tracking of given weights. Different from the previous related works, the time delay T-S fuzzy models with the exogenous disturbances are applied to identify the nonlinear weighting dynamics. Meanwhile, the generalized PID controller structure and the improved convex linear matrix inequalities (LMI) algorithms are proposed to fulfil the tracking problem. Furthermore, in order to enhance the robust performance, the peak-to-peak measure index is applied to optimize the tracking performance. Simulations are given to demonstrate the efficiency of the proposed approach.
基金supported Foundation of National Development and Reform Commission of China (No. 2040)
文摘Pressure ripples in electric power steering (EPS) systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno (T-S) fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation (PDC) structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality (LMI) problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.