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
As a typical rhythmic movement, human being's rhythmic gait movement can be generated by a central pattern generator (CPG) located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by g...As a typical rhythmic movement, human being's rhythmic gait movement can be generated by a central pattern generator (CPG) located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by gait frequency and amplitude variances. As an important property of human being's motion vision, the attention selection mechanism plays a vital part in the regulation of gait movement. In this paper, the CPG model is amended under the condition of attention selection on the theoretical basis of Matsuoka neural oscillators. Regulation of attention selection signal for the CPG model parameters and structure is studied, which consequentially causes the frequency and amplitude changes of gait movement output. Further, the control strategy of the CPG model gait movement under the condition of attention selection is discussed, showing that the attention selection model can regulate the output model of CPG gait movement in three different ways. The realization of regulation on the gait movement frequency and amplitude shows a variety of regulation on the CPG gait movement made by attention selection and enriches the controllability of CPG gait movement, which demonstrates potential influence in engineering applications.展开更多
The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied.The switching law is determined by the output predictive errors of a finite ...The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied.The switching law is determined by the output predictive errors of a finite number of subsystems.For the single subsystem and multiple subsystems cases,it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system.This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.展开更多
In this paper the definitions of generalized transfer functios of control system and itscontinuity are presented.Using generalized transfer function as a tool,a set of theorems fordeciding movement stability have been...In this paper the definitions of generalized transfer functios of control system and itscontinuity are presented.Using generalized transfer function as a tool,a set of theorems fordeciding movement stability have been constructed.Thus basing understanding of thecharacteristics of a control dynamics system on its measured procedure will simplify thedecision method of movement stability problems.展开更多
Generalized H2 (GH2) stability analysis and controller design of the uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with state delay are studied based on a switching fuzzy model and piecewise Lyapunov f...Generalized H2 (GH2) stability analysis and controller design of the uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with state delay are studied based on a switching fuzzy model and piecewise Lyapunov function. GH2 stability sufficient conditions are derived in terms of linear matrix inequalities (LMIs). The interactions among the fuzzy subsystems are considered. Therefore, the proposed conditions are less conservative than the previous results. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable. To illustrate the validity of the proposed method, a design example is provided.展开更多
A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity. The nonlinear off-line model of the controlled plant i...A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity. The nonlinear off-line model of the controlled plant is built by LS-SVM with radial basis function (RBF) kernel. In the process of system running, the off-line model is linearized at each sampling instant, and the generalized prediction control (GPC) algorithm is employed to implement the prediction control for the controlled plant. The obtained algorithm is applied to a boiler temperature control system with complicated nonlinearity and large time delay. The results of the experiment verify the effectiveness and merit of the algorithm.展开更多
Power plants are nonlinear and uncertain complex systems. Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modem power pla...Power plants are nonlinear and uncertain complex systems. Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modem power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network (NFGPC) is proposed in this paper. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant. From the experiments on the plant and the simulation of the plant, much better performance than the traditional controller is obtained,展开更多
This paper deeply analyzes the closed-loop nature ofGPCin the fram ework ofinter- nalm odelcontrol(IMC) theory. A new sort ofrelation lies in the feedback structure so that robustreason can be satisfactorily explain...This paper deeply analyzes the closed-loop nature ofGPCin the fram ework ofinter- nalm odelcontrol(IMC) theory. A new sort ofrelation lies in the feedback structure so that robustreason can be satisfactorily explained. The resultissignificantbecause the previous con- clusions are only applied to open-loop stable plant(orm odel).展开更多
The notion of generalized regularity is proposed for rectangular descriptor systems. Generalized regularizability of a rectangular descriptor system via different feedback forms is considered. Necessary and sufficient...The notion of generalized regularity is proposed for rectangular descriptor systems. Generalized regularizability of a rectangular descriptor system via different feedback forms is considered. Necessary and sufficient conditions for generalized regularizability are obtained, which are only dependent upon the open-loop coefficient matrices. It is also shown that under these necessary and sufficient conditions, all the generalized regularizing feedback controllers form a Zarisky open set. A numerical example demonstrates the proposed results.展开更多
The high-purity distillation column system is strongly nonlinear and coupled,which makes it difficult to control.Active disturbance rejection control(ADRC)has been widely used in distillation systems,but it has limita...The high-purity distillation column system is strongly nonlinear and coupled,which makes it difficult to control.Active disturbance rejection control(ADRC)has been widely used in distillation systems,but it has limitations in controlling distillation systems with large time delays since ADRC employs ESO and feedback control law to estimate the total disturbance of the system without considering the large time delays.This paper designs a proportion integral-type active disturbance rejection generalized predictive control(PI-ADRGPC)algorithm to control the distillation column system with large time delay.It replaces the PD controller in ADRC with a proportion integral-type generalized predictive control(PI-GPC),thereby improving the performance of control systems with large time delays.Since the proposed controller has many parameters and is difficult to tune,this paper proposes to use the grey wolf optimization(GWO)to tune these parameters,whose structure can also be used by other intelligent optimization algorithms.The performance of GWO tuned PI-ADRGPC is compared with the control performance of GWO tuned ADRC method,multi-verse optimizer(MVO)tuned PI-ADRGPC and MVO tuned ADRC.The simulation results show that the proposed strategy can track reference well and has a good disturbance rejection performance.展开更多
In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system...In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmodelled dynamics.展开更多
Because of the tire nonlinearity and vehicle's parameters'uncertainties,robust control methods based on the worst cases,such as H_∞,μsynthesis,have been widely used in active front steering control,however,in orde...Because of the tire nonlinearity and vehicle's parameters'uncertainties,robust control methods based on the worst cases,such as H_∞,μsynthesis,have been widely used in active front steering control,however,in order to guarantee the stability of active front steering system(AFS)controller,the robust control is at the cost of performance so that the robust controller is a little conservative and has low performance for AFS control.In this paper,a generalized internal model robust control(GIMC)that can overcome the contradiction between performance and stability is used in the AFS control.In GIMC,the Youla parameterization is used in an improved way.And GIMC controller includes two sections:a high performance controller designed for the nominal vehicle model and a robust controller compensating the vehicle parameters'uncertainties and some external disturbances.Simulations of double lane change(DLC)maneuver and that of braking on split-μroad are conducted to compare the performance and stability of the GIMC control,the nominal performance PID controller and the H_∞controller.Simulation results show that the high nominal performance PID controller will be unstable under some extreme situations because of large vehicle's parameters variations,H_∞controller is conservative so that the performance is a little low,and only the GIMC controller overcomes the contradiction between performance and robustness,which can both ensure the stability of the AFS controller and guarantee the high performance of the AFS controller.Therefore,the GIMC method proposed for AFS can overcome some disadvantages of control methods used by current AFS system,that is,can solve the instability of PID or LQP control methods and the low performance of the standard H_∞controller.展开更多
Continuous material processing operations like printing and textiles manufacturing are conducted under highly variable conditions due to changes in the environment and/or in the materials being processed.As such,the p...Continuous material processing operations like printing and textiles manufacturing are conducted under highly variable conditions due to changes in the environment and/or in the materials being processed.As such,the processing parameters require robust real-time adjustment appropriate to the conditions of a nonlinear system.This paper addresses this issue by presenting a hybrid feedforward-feedback nonlinear model predictive controller for continuous material processing operations.The adaptive feedback control strategy of the controller augments the standard feedforward control to ensure improved robustness and compensation for environmental disturbances and/or parameter uncertainties.Thus,the controller can reduce the need for manual adjustments.The controller applies nonlinear generalized predictive control to generate an adaptive control signal for attaining robust performance.A wavelet-based neural network model is adopted as the prediction model with high prediction precision and time-frequency localization characteristics.Online training is utilized to predict uncertain system dynamics by tuning the wavelet neural network parameters and the controller parameters adaptively.The performance of the controller algorithm is verified by both simulation,and in a real-time practical application involving a single-input single-output double-zone sliver drafting system used in textiles manufacturing.Both the simulation and practical results demonstrate an excellent control performance in terms of the mean thickness and coefficient of variation of output slivers,which verifies the effectiveness of this approach in improving the long-term uniformity of slivers.展开更多
A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical pro...A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical projection of a fourth-order chaotic system generated through nonsingular states transformation from a cell neural net chaotic system. In this sense, it is said that generalized synchronization is achieved in reduced-order. The synchronization discussed here expands the scope of reduced-order synchronization studied in relevant literatures. In this way, we can achieve generalized reduced-order synchronization between many famous chaotic systems such as the second-order Drifting system and the third-order Lorenz system by designing a fast slide mode controller. Simulation results are provided to verify the operation of the designed synchronization.展开更多
To develop vortex generator jet (VGJ) method for flow control, the turbulence flow in a 14° conical diffuser with and without vortex generator jets are simulated by solving Navier-Stokes equations with k-ε tur...To develop vortex generator jet (VGJ) method for flow control, the turbulence flow in a 14° conical diffuser with and without vortex generator jets are simulated by solving Navier-Stokes equations with k-ε turbulence model. The diffuser performance, based on different velocity ratio (ratio of the jet speed to the mainstream velocity), is investigated and compared with the experimental study. On the basis of the flow characteristics using computation fluid dynamics (CFD) method observed in the conical diffuser and the downstream development of the longitudinal vortices, attempt is made to correlate the pressure recovery coefficient with the behavior of vortices produced by vortex generator jets.展开更多
A GPC (generalized predictive control) law is developed to control the powerof a turbine, after transforming the nonlinear mathematical model of the power regulation systeminto a CARIMA(controlled auto-regressive inte...A GPC (generalized predictive control) law is developed to control the powerof a turbine, after transforming the nonlinear mathematical model of the power regulation systeminto a CARIMA(controlled auto-regressive integrated moving average) form. The effect of the newcontrol law is compared with a traditional PID (proportional, integral and differential) control lawby numerical simulation. The simulation results verify the effectiveness, the correctness and theadvantage of the new control scheme.展开更多
Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic...Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic control theory. However, now global convergence of GPC has not been established for algorithms in computing a least squares iteration. A generalized model of adaptive generalized predictive control is presented. The global convergebce is also given on the basis of estimating the parameters of GPC by least squares algorithm.展开更多
In order to improve the robustness and noise resistance of generalized minimum valance cothrol systems, several generalizedminimum variance control schemes are synthetically analyzed. The output variance caused by st...In order to improve the robustness and noise resistance of generalized minimum valance cothrol systems, several generalizedminimum variance control schemes are synthetically analyzed. The output variance caused by stochastic noise is decomposed to two parts. One part accords with the output variance of minboum vedance control and the other is the additional term of output variance causedby the control weighting factors. At the same time, the sensitivity function of modeling error is also deduced. A new robast design method that can minimize the sensitivity and the additional part of output variance is Presented by regulating variable parameters of contollers. The simulation results of self-tuning control show the effect of this method.展开更多
The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used propor...The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used proportion integration differentiation(PID) algorithm had been limited,a novel method was developed to precisely control the heating and cooling stages for batch dyeing process based on predictive sliding mode control(SMC) algorithm.Firstly,a special predictive sliding mode model was constructed according to the principle of generalized predictive control(GPC);secondly,an appropriate reference trajectory for SMC was designed based on the improved approaching law;finally,the predictive sliding mode model and the Diophantine equation were used to predict the output and then the optimized control law was derived using the generalized predictive law.This method combined GPC and the SMC with their respective advantages,so it could be applied to time-delay process,making the control system more robust.Simulation experiments show that this algorithm can well track the temperature variation for the batch dyeing process.展开更多
In an extraction turbine, pressure of the extracted steam and rotate speed of the rotor are two important controlled quantities. The traditional linear state feedback control method is not perfect enough to control th...In an extraction turbine, pressure of the extracted steam and rotate speed of the rotor are two important controlled quantities. The traditional linear state feedback control method is not perfect enough to control the two quantities accurately because of existence of nonlinearity and coupling. A generalized minimum variance control method is studied for an extraction turbine. Firstly, a nonlinear mathematical model of the control system about the two quantities is transformed into a linear system with two white noises. Secondly, a generalized minimum variance control law is applied to the system. A comparative simulation is done. The simulation results indicate that precision and dynamic quality of the regulating system under the new control law are both better than those under the state feedback control law.展开更多
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 the National Natural Science Foundation of China(Nos.11232005 and11472104)the Doctoral Fund of Ministry of Education of China(No.20120074110020)
文摘As a typical rhythmic movement, human being's rhythmic gait movement can be generated by a central pattern generator (CPG) located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by gait frequency and amplitude variances. As an important property of human being's motion vision, the attention selection mechanism plays a vital part in the regulation of gait movement. In this paper, the CPG model is amended under the condition of attention selection on the theoretical basis of Matsuoka neural oscillators. Regulation of attention selection signal for the CPG model parameters and structure is studied, which consequentially causes the frequency and amplitude changes of gait movement output. Further, the control strategy of the CPG model gait movement under the condition of attention selection is discussed, showing that the attention selection model can regulate the output model of CPG gait movement in three different ways. The realization of regulation on the gait movement frequency and amplitude shows a variety of regulation on the CPG gait movement made by attention selection and enriches the controllability of CPG gait movement, which demonstrates potential influence in engineering applications.
文摘The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied.The switching law is determined by the output predictive errors of a finite number of subsystems.For the single subsystem and multiple subsystems cases,it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system.This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.
文摘In this paper the definitions of generalized transfer functios of control system and itscontinuity are presented.Using generalized transfer function as a tool,a set of theorems fordeciding movement stability have been constructed.Thus basing understanding of thecharacteristics of a control dynamics system on its measured procedure will simplify thedecision method of movement stability problems.
文摘Generalized H2 (GH2) stability analysis and controller design of the uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with state delay are studied based on a switching fuzzy model and piecewise Lyapunov function. GH2 stability sufficient conditions are derived in terms of linear matrix inequalities (LMIs). The interactions among the fuzzy subsystems are considered. Therefore, the proposed conditions are less conservative than the previous results. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable. To illustrate the validity of the proposed method, a design example is provided.
基金This work has been supported by the National Outstanding Youth Science Foundation of China (No. 60025308) and the Teach and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE,China.
文摘A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity. The nonlinear off-line model of the controlled plant is built by LS-SVM with radial basis function (RBF) kernel. In the process of system running, the off-line model is linearized at each sampling instant, and the generalized prediction control (GPC) algorithm is employed to implement the prediction control for the controlled plant. The obtained algorithm is applied to a boiler temperature control system with complicated nonlinearity and large time delay. The results of the experiment verify the effectiveness and merit of the algorithm.
基金This work was supported by the Natural Science Foundation of Beijing (No. 4062030)National Natural Science Foundation of China (No. 50576022,69804003)Scientific Research Common Program of Beijing Municipal Commission of Education (KM200611232007).
文摘Power plants are nonlinear and uncertain complex systems. Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modem power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network (NFGPC) is proposed in this paper. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant. From the experiments on the plant and the simulation of the plant, much better performance than the traditional controller is obtained,
文摘This paper deeply analyzes the closed-loop nature ofGPCin the fram ework ofinter- nalm odelcontrol(IMC) theory. A new sort ofrelation lies in the feedback structure so that robustreason can be satisfactorily explained. The resultissignificantbecause the previous con- clusions are only applied to open-loop stable plant(orm odel).
基金the Chinese Outstanding Youth Foundation(No. 69925308)the Program for Changjiang Scholars and Innovative Research Team in University.
文摘The notion of generalized regularity is proposed for rectangular descriptor systems. Generalized regularizability of a rectangular descriptor system via different feedback forms is considered. Necessary and sufficient conditions for generalized regularizability are obtained, which are only dependent upon the open-loop coefficient matrices. It is also shown that under these necessary and sufficient conditions, all the generalized regularizing feedback controllers form a Zarisky open set. A numerical example demonstrates the proposed results.
基金funded by the National Natural Science Foundation of China(61973175,62073177 and 61973172)South African National Research Foundation(132797)+2 种基金South African National Research Foundation Incentive(114911)Eskom Tertiary Education Support Programme Grant of South AfricaTianjin Research Innovation Project for Postgraduate Students(2021YJSB018,2020YJSB003)。
文摘The high-purity distillation column system is strongly nonlinear and coupled,which makes it difficult to control.Active disturbance rejection control(ADRC)has been widely used in distillation systems,but it has limitations in controlling distillation systems with large time delays since ADRC employs ESO and feedback control law to estimate the total disturbance of the system without considering the large time delays.This paper designs a proportion integral-type active disturbance rejection generalized predictive control(PI-ADRGPC)algorithm to control the distillation column system with large time delay.It replaces the PD controller in ADRC with a proportion integral-type generalized predictive control(PI-GPC),thereby improving the performance of control systems with large time delays.Since the proposed controller has many parameters and is difficult to tune,this paper proposes to use the grey wolf optimization(GWO)to tune these parameters,whose structure can also be used by other intelligent optimization algorithms.The performance of GWO tuned PI-ADRGPC is compared with the control performance of GWO tuned ADRC method,multi-verse optimizer(MVO)tuned PI-ADRGPC and MVO tuned ADRC.The simulation results show that the proposed strategy can track reference well and has a good disturbance rejection performance.
文摘In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmodelled dynamics.
基金Supported by National Natural Science Foundation of China(Grant Nos.11072106,51375009)
文摘Because of the tire nonlinearity and vehicle's parameters'uncertainties,robust control methods based on the worst cases,such as H_∞,μsynthesis,have been widely used in active front steering control,however,in order to guarantee the stability of active front steering system(AFS)controller,the robust control is at the cost of performance so that the robust controller is a little conservative and has low performance for AFS control.In this paper,a generalized internal model robust control(GIMC)that can overcome the contradiction between performance and stability is used in the AFS control.In GIMC,the Youla parameterization is used in an improved way.And GIMC controller includes two sections:a high performance controller designed for the nominal vehicle model and a robust controller compensating the vehicle parameters'uncertainties and some external disturbances.Simulations of double lane change(DLC)maneuver and that of braking on split-μroad are conducted to compare the performance and stability of the GIMC control,the nominal performance PID controller and the H_∞controller.Simulation results show that the high nominal performance PID controller will be unstable under some extreme situations because of large vehicle's parameters variations,H_∞controller is conservative so that the performance is a little low,and only the GIMC controller overcomes the contradiction between performance and robustness,which can both ensure the stability of the AFS controller and guarantee the high performance of the AFS controller.Therefore,the GIMC method proposed for AFS can overcome some disadvantages of control methods used by current AFS system,that is,can solve the instability of PID or LQP control methods and the low performance of the standard H_∞controller.
文摘Continuous material processing operations like printing and textiles manufacturing are conducted under highly variable conditions due to changes in the environment and/or in the materials being processed.As such,the processing parameters require robust real-time adjustment appropriate to the conditions of a nonlinear system.This paper addresses this issue by presenting a hybrid feedforward-feedback nonlinear model predictive controller for continuous material processing operations.The adaptive feedback control strategy of the controller augments the standard feedforward control to ensure improved robustness and compensation for environmental disturbances and/or parameter uncertainties.Thus,the controller can reduce the need for manual adjustments.The controller applies nonlinear generalized predictive control to generate an adaptive control signal for attaining robust performance.A wavelet-based neural network model is adopted as the prediction model with high prediction precision and time-frequency localization characteristics.Online training is utilized to predict uncertain system dynamics by tuning the wavelet neural network parameters and the controller parameters adaptively.The performance of the controller algorithm is verified by both simulation,and in a real-time practical application involving a single-input single-output double-zone sliver drafting system used in textiles manufacturing.Both the simulation and practical results demonstrate an excellent control performance in terms of the mean thickness and coefficient of variation of output slivers,which verifies the effectiveness of this approach in improving the long-term uniformity of slivers.
基金Project supported by the National Natural Science Foundation of China (Grant No 60374037) and the National High Technology Development Program of China (Grant No 2004BA204B08-02).
文摘A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical projection of a fourth-order chaotic system generated through nonsingular states transformation from a cell neural net chaotic system. In this sense, it is said that generalized synchronization is achieved in reduced-order. The synchronization discussed here expands the scope of reduced-order synchronization studied in relevant literatures. In this way, we can achieve generalized reduced-order synchronization between many famous chaotic systems such as the second-order Drifting system and the third-order Lorenz system by designing a fast slide mode controller. Simulation results are provided to verify the operation of the designed synchronization.
基金This project is supported by Scientific Research Foundation of Ministry of Education of China for Returnee.
文摘To develop vortex generator jet (VGJ) method for flow control, the turbulence flow in a 14° conical diffuser with and without vortex generator jets are simulated by solving Navier-Stokes equations with k-ε turbulence model. The diffuser performance, based on different velocity ratio (ratio of the jet speed to the mainstream velocity), is investigated and compared with the experimental study. On the basis of the flow characteristics using computation fluid dynamics (CFD) method observed in the conical diffuser and the downstream development of the longitudinal vortices, attempt is made to correlate the pressure recovery coefficient with the behavior of vortices produced by vortex generator jets.
文摘A GPC (generalized predictive control) law is developed to control the powerof a turbine, after transforming the nonlinear mathematical model of the power regulation systeminto a CARIMA(controlled auto-regressive integrated moving average) form. The effect of the newcontrol law is compared with a traditional PID (proportional, integral and differential) control lawby numerical simulation. The simulation results verify the effectiveness, the correctness and theadvantage of the new control scheme.
基金This project was supported by the National Natural Science Foundation of China (60174021) Tianjin Advanced School Science and Technology Development Foundation (01 - 20403) .
文摘Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic control theory. However, now global convergence of GPC has not been established for algorithms in computing a least squares iteration. A generalized model of adaptive generalized predictive control is presented. The global convergebce is also given on the basis of estimating the parameters of GPC by least squares algorithm.
文摘In order to improve the robustness and noise resistance of generalized minimum valance cothrol systems, several generalizedminimum variance control schemes are synthetically analyzed. The output variance caused by stochastic noise is decomposed to two parts. One part accords with the output variance of minboum vedance control and the other is the additional term of output variance causedby the control weighting factors. At the same time, the sensitivity function of modeling error is also deduced. A new robast design method that can minimize the sensitivity and the additional part of output variance is Presented by regulating variable parameters of contollers. The simulation results of self-tuning control show the effect of this method.
基金National Natural Science Foundation of China(No.61074154)
文摘The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used proportion integration differentiation(PID) algorithm had been limited,a novel method was developed to precisely control the heating and cooling stages for batch dyeing process based on predictive sliding mode control(SMC) algorithm.Firstly,a special predictive sliding mode model was constructed according to the principle of generalized predictive control(GPC);secondly,an appropriate reference trajectory for SMC was designed based on the improved approaching law;finally,the predictive sliding mode model and the Diophantine equation were used to predict the output and then the optimized control law was derived using the generalized predictive law.This method combined GPC and the SMC with their respective advantages,so it could be applied to time-delay process,making the control system more robust.Simulation experiments show that this algorithm can well track the temperature variation for the batch dyeing process.
文摘In an extraction turbine, pressure of the extracted steam and rotate speed of the rotor are two important controlled quantities. The traditional linear state feedback control method is not perfect enough to control the two quantities accurately because of existence of nonlinearity and coupling. A generalized minimum variance control method is studied for an extraction turbine. Firstly, a nonlinear mathematical model of the control system about the two quantities is transformed into a linear system with two white noises. Secondly, a generalized minimum variance control law is applied to the system. A comparative simulation is done. The simulation results indicate that precision and dynamic quality of the regulating system under the new control law are both better than those under the state feedback control law.