A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a ...A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.展开更多
Dear Editor,This letter deals with the controller synthesis problem of networked Takagi-Sugeno(T-S)fuzzy systems.Due to the introduction of network communications,the same premise is no longer shared by fuzzy plants a...Dear Editor,This letter deals with the controller synthesis problem of networked Takagi-Sugeno(T-S)fuzzy systems.Due to the introduction of network communications,the same premise is no longer shared by fuzzy plants and fuzzy controllers.This makes the classic parallel distribution compensation(PDC)control infeasible.To overcome this situation,a novel method for reconstructing the membership functions'grades is proposed,which synchronizes the time scales.Then,the membership function dependent method is adopted to introduce asynchronous errors and detailed membership function information.For the event-triggered control strategy,a series of robust H∞stable conditions in LMI form are derived.Finally,a simulation of a practical system is used to demonstrate the method proposed in this letter can reduce conservatism.展开更多
The synthetic fuzzy assessing method is usually applied to sensory evaluation. The method has simple and reliable virtue, and it is consistent with objective evaluation results. Using this method, system status of pla...The synthetic fuzzy assessing method is usually applied to sensory evaluation. The method has simple and reliable virtue, and it is consistent with objective evaluation results. Using this method, system status of plating solution evaporator is evaluated, and the result is applied to compensate a fuzzy controller. Experimental results have shown the correctness and the validity of the proposed approach.展开更多
Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous...Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.展开更多
A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip ...A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.展开更多
To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output err...To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.展开更多
Filament winding has emerged as the main process for carbon fiber reinforced plastic(CFRP) fabrication, and tension control plays a key role in enhancing the quality of the winding products. With the continuous improv...Filament winding has emerged as the main process for carbon fiber reinforced plastic(CFRP) fabrication, and tension control plays a key role in enhancing the quality of the winding products. With the continuous improvement of prod?uct quality and e ciency, the precision of the tension control system is constantly improving. In this paper, a novel tension control method is proposed, which can regulate the fiber tension and transport speed of the winding process by governing the outputs of three di erent driven rollers(the torque of the unwind roll, the torque of the magnetic powder brake roller, and the speed of the master speed roller) in three levels. The mechanical structures and dynamic models of the driven rollers and idle rollers are established by considering the time?varying features of the roller radius and inertia. Moreover, the influence of parameters and speed variation on fiber tension is investigated using the increment model. Subsequently, the control method is proposed by applying fiber tension in three levels accord?ing to the features of the three driven rollers. An adaptive fuzzy controller is designed for tuning the PID parameters online to control the speed of the master speed roller. Simulation is conducted for verifying the performance and sta?bility of the proposed tension control method by comparing with those of the conventional PID control method. The result reveals that the proposed method outperforms the conventional method. Finally, an experimental platform is constructed, and the proposed system is applied to a winding machine. The performance and stability of the tension control system are demonstrated via a series of experiments using carbon fiber under di erent reference speeds and tensions. This paper proposes a novel tension control method to regulate the fiber tension and transport speed.展开更多
A bionic flexible manipulator driven by pneumatic muscle actuator(PMA)can better reflect the flexibility of the mechanism.Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic ma...A bionic flexible manipulator driven by pneumatic muscle actuator(PMA)can better reflect the flexibility of the mechanism.Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic manipulator system.Compared with traditional electro-hydraulic actuators,the structure of PMA is simple but possesses strong nonlinearity and flexibility,which leads to the difficulty in improving the control accuracy.In this paper,the configuration design of a bionic flexible manipulator is performed by human physiological map,the kinematic model of the mechanism is established,and the dynamics is analyzed by Lagrange method.A fuzzy torque control algorithm is designed based on the computed torque method,where the fuzzy control theory is applied.The hardware experimental system is established.Through the co-simulation contrast test on MATLAB and ADAMS,it is found that the fuzzy torque control algorithm has better tracking performance and higher tracking accuracy than the computed torque method,and is applied to the entity control test.The experimental results show that the fuzzy torque algorithm can better control the trajectory tracking movement of the bionic flexible manipulator.This research proposes a fuzzy torque control algorithm which can compensate the error more effectively,and possesses the preferred trajectory tracking performance.展开更多
Firstly, a multi-field coupling finite element formulation of composited beam laminated with the photostrictive actuators is developed in this paper. Moreover, an optimal fuzzy active control algorithm is also propose...Firstly, a multi-field coupling finite element formulation of composited beam laminated with the photostrictive actuators is developed in this paper. Moreover, an optimal fuzzy active control algorithm is also proposed on the basis of the combination of optimal control and fuzzy one.This method opens a new avenue to resolve the contradiction between the linear system control method and nonlinear actuating characteristics of photostrictive actuators. The desired control for suppressing multi-modal vibration of photoelectric laminated beam is firstly obtained through optimal control and then the fuzzy control is used to approach the desired mechanical strain induced by photostrictive actuators. Thus, the multi-mode vibration control of beam is realized.In the design process of optimal fuzzy controller, the design of fuzzy control is independent of optimal control. The simulation results demonstrate that the proposed control method can effectively realize multi-modal vibration control of photoelectric laminated beams, and the control effect of optimal fuzzy control is better than that of optimal state feedback control.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
This paper focuses on the stability analysis of nonlinear networked control system with integral quadratic constraints(IQC) performance, dynamic quantization, variable sampling intervals, and communication delays. By ...This paper focuses on the stability analysis of nonlinear networked control system with integral quadratic constraints(IQC) performance, dynamic quantization, variable sampling intervals, and communication delays. By using input-delay and parallel distributed compensation(PDC) techniques, we establish the Takagi-Sugeno(T-S) fuzzy model for the system, in which the sampling period of the sampler and signal transmission delay are transformed to the refreshing interval of a zero-order holder(ZOH). By the appropriate Lyapunov-Krasovskii-based methods, a delay-dependent criterion is derived to ensure the asymptotic stability for the system with IQC performance via the H∞ state feedback control. The efficiency of the method is illustrated on a simulation exampler.展开更多
This paper presents an analysis of the KM （Karnik-Mendel） algorithms performance under real time implementation using 3 types： the non-iterative, the iterative and the enhanced, and their feasibility for real-time ...This paper presents an analysis of the KM （Karnik-Mendel） algorithms performance under real time implementation using 3 types： the non-iterative, the iterative and the enhanced, and their feasibility for real-time interval type 2 fuzzy logic control system applications. The results are also compared against NT （Nie-Tan） method that is one of the fastest and simplest defuzzification methods. Because the DC （direct current） servo-motor is one of the most used motors in different industrial applications and the model of the motor is nonlinear, this motor was selected for validating the implementation in real time hardware. This DC motor is a perfect option for studying the real time performance of KM algorithms in order to show up its limits and possibilities for real-time control system applications. These methodologies are implemented in National Instruments LabVIEW FPGA （field programmable gate array） module hardware which is one of the most used platforms in the industry. The results show that the E-KM （enhanced KM） algorithm and the NT method present good results for implementing real-time control applications in real time hardware. Although fuzzy logic type 2 is a good option for working with nonlinear and noise from the sensors, the defuzzification method has to react in a short period of time in order to allow good control response. Hence, a complete study of defuzzification is needed for improving the real time implementations of fuzzy type 2.展开更多
A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is perform...A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.展开更多
Double-column bridge piers are prone to local damage during earthquakes,leading to the destruction of bridges.To improve the earthquake resistance of double-column bridge piers,a novel swing column device(SCD),consist...Double-column bridge piers are prone to local damage during earthquakes,leading to the destruction of bridges.To improve the earthquake resistance of double-column bridge piers,a novel swing column device(SCD),consisting of a magnetorheological(MR)damper,a current controller,and a swing column,was designed for the present work.To verify the seismic energy dissipation ability of the SCD,a lumped mass model for a double-column bridge pier with the SCD was established according to the low-order modeling method proposed by Steo.Furthermore,the motion equation of the double-column bridge pier with the SCD was established based on the D′Alembert principle and solved with the use of computational programming.It was found that the displacement response of the double-column bridge pier was effectively controlled by the SCD.However,due to rough current selection and a time delay,there is a significant overshoot of the bridge acceleration using SCD.Hence,to solve the overshoot phenomenon,a current controller was designed based on fuzzy logic theory.It was found that the SCD design based on fuzzy control provided an ideal shock absorption effect,while reducing the displacement and acceleration of the bridge pier by 36.43%‒40.63%and 30.06%‒33.6%,respectively.展开更多
This paper uses a methodology based in Fuzzy Sets Theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae)—the soybean aphid, and its predator, Orius insidiosus (Hemiptera: ...This paper uses a methodology based in Fuzzy Sets Theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae)—the soybean aphid, and its predator, Orius insidiosus (Hemiptera: Anthocoridae) and to propose a biological control to soybean aphid. Economic thresholds were already developed for this pest. The model includes biotic (predator) and abiotic (temperature) factors, which affect the soybean aphid population dynamics. The dynamic model results in a fuzzy model that preserves the biological meaning and nature of the predator-prey model. The paper also includes a comparison between the fuzzy model and real data reported in the literature. Subsequently, we propose a biological control to soybean aphid by another fuzzy rule-based system. This model has allowed to predict timing and releasing number of predators for soybean aphid biological control. On the one hand, the soybean aphid has still not found in Brazil. Therefore, before any eventual invasion, a predictive model to enhance biological control program is desirable. On the other hand, the soybean aphid has become the most devastating insect pest of soybeans in the United States. Brazil is the second largest exporter of soybean at present, after the USA and before Argentina. According to the Bureau of Agriculture of the USA, it has been estimated that Brazil will be the largest soybean exporter in 2023.展开更多
Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an effic...Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an efficient way to examine and analyze the accuracy of linear and nonlinear problems.The main aim of this work is to explore the approximate solutions of fuzzy Volterra integral equations(both linear and nonlinear)with a separable kernel via HAM.This method provides a reliable way to ensure the convergence of the approximation series.A new general form of HAM is presented and analyzed in the fuzzy domain.A qualitative convergence analysis based on the graphical method of a fuzzy HAM is discussed.The solutions sought by the proposed method show that the HAM is easy to implement and computationally quite attractive.Some solutions of fuzzy second kind Volterra integral equations are solved as numerical examples to show the potential of the method.The results also show that HAM provides an easy way to control and modify the convergence area in order to obtain accurate solutions.展开更多
Sliding mode control(SMC)is a widely adopted control technology known for its robustness and simplicity.The essence of SMC is to use discontinuous control to drive a system into a pre-defined motion,called the sliding...Sliding mode control(SMC)is a widely adopted control technology known for its robustness and simplicity.The essence of SMC is to use discontinuous control to drive a system into a pre-defined motion,called the sliding mode,which is designed with desirable dynamical properties.In the sliding mode,the controlled system is insensitive to the matched uncertainties and disturbances.Most SMC theory and methods have been developed based on the dynamical systems in the continuous-time domain,where switching functions play a critical role.Ideal switching is supposed to be instantaneous,activating as soon as the switching condition is met.However,in practice,switching mechanisms are affected by imperfections such as time delays,unmodeled dynamics,defects,digitization effects,and actuation limitations,which can degrade the salient properties of SMC.Understanding these effects and developing mitigation strategies are essential for industrial applications.Furthermore,the advent of networked control environments presents new challenges like limited communication bandwidth,latency and cyberattack,which have seen the emergence of the event-triggered SMC recently.Despite these significant advances,there is a lack of comprehensive studies which examine the commonalities and distinctions of utilizing switching in SMC across the continuous-time and discrete-time domains and beyond.This paper investigates the role of switching in SMC from a spatio-temporal perspective,considering both state-space and time aspects.The aim is to facilitate better understanding of its effects and misbehaviors,and to unlock its full potential for future applications.The interplay between SMC methods in the continuous-time and discrete-time domains is analyzed,and their shared principles and unique challenges are identified.Furthermore,important technical issues relating to switching across these time domains are explored,and several myths and pitfalls in their theory and applications are depicted.The relationships of SMC with other switching-based control systems such as switched control systems,fuzzy control systems,and event-triggered control systems are discussed.The impact of networked control environments on SMC in the continuous-time and discrete-time domains is also examined.Finally,key challenges and opportunities are outlined for future work in SMC and beyond.展开更多
To effectively select risk control schemes in uncertain environments,this paper has proposed an analysis and evaluation method based on the fuzzy comprehensive evaluation method.Firstly,enterprises have adopted the br...To effectively select risk control schemes in uncertain environments,this paper has proposed an analysis and evaluation method based on the fuzzy comprehensive evaluation method.Firstly,enterprises have adopted the brainstorming method and the Delphi method to identify risks in engineering projects,and organized the identified risks in the form of checklists to facilitate further analysis.Secondly,the fuzzy comprehensive evaluation theory was introduced to determine the comparison matrix of each risk factor and its weight.Furthermore,the top five risk factors in terms of weight ranking were taken as the evaluation factors for the selection of risk control plans.The plans were scored through the weighted scoring method,and the optimal risk control plan was determined based on the score.Finally,the feasibility of the proposed selection technology was verified through A research example of the risk control plan assessment for the construction project of Enterprise A.展开更多
基金This project was supported by the National Natural Science Foundation of China (90405011).
文摘A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.
基金supported by the National Natural Science Foundation of China(62173218,61833011)International International Cooperation Project of Shanghai Science and Technology Commission(21190780300).
文摘Dear Editor,This letter deals with the controller synthesis problem of networked Takagi-Sugeno(T-S)fuzzy systems.Due to the introduction of network communications,the same premise is no longer shared by fuzzy plants and fuzzy controllers.This makes the classic parallel distribution compensation(PDC)control infeasible.To overcome this situation,a novel method for reconstructing the membership functions'grades is proposed,which synchronizes the time scales.Then,the membership function dependent method is adopted to introduce asynchronous errors and detailed membership function information.For the event-triggered control strategy,a series of robust H∞stable conditions in LMI form are derived.Finally,a simulation of a practical system is used to demonstrate the method proposed in this letter can reduce conservatism.
文摘The synthetic fuzzy assessing method is usually applied to sensory evaluation. The method has simple and reliable virtue, and it is consistent with objective evaluation results. Using this method, system status of plating solution evaporator is evaluated, and the result is applied to compensate a fuzzy controller. Experimental results have shown the correctness and the validity of the proposed approach.
基金supported by the Deanship of Research at the King Fahd University of Petroleum&Minerals,Dhahran,31261,Saudi Arabia,under Project No.EC241001.
文摘Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.
文摘A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.
文摘To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.
基金Supported by National Natural Science Foundation of China(Grant No.51575018)
文摘Filament winding has emerged as the main process for carbon fiber reinforced plastic(CFRP) fabrication, and tension control plays a key role in enhancing the quality of the winding products. With the continuous improvement of prod?uct quality and e ciency, the precision of the tension control system is constantly improving. In this paper, a novel tension control method is proposed, which can regulate the fiber tension and transport speed of the winding process by governing the outputs of three di erent driven rollers(the torque of the unwind roll, the torque of the magnetic powder brake roller, and the speed of the master speed roller) in three levels. The mechanical structures and dynamic models of the driven rollers and idle rollers are established by considering the time?varying features of the roller radius and inertia. Moreover, the influence of parameters and speed variation on fiber tension is investigated using the increment model. Subsequently, the control method is proposed by applying fiber tension in three levels accord?ing to the features of the three driven rollers. An adaptive fuzzy controller is designed for tuning the PID parameters online to control the speed of the master speed roller. Simulation is conducted for verifying the performance and sta?bility of the proposed tension control method by comparing with those of the conventional PID control method. The result reveals that the proposed method outperforms the conventional method. Finally, an experimental platform is constructed, and the proposed system is applied to a winding machine. The performance and stability of the tension control system are demonstrated via a series of experiments using carbon fiber under di erent reference speeds and tensions. This paper proposes a novel tension control method to regulate the fiber tension and transport speed.
基金Supported by National Natural Science Foundation of China(Grant No.51405229)Jiangsu Provincial Natural Science Foundation of China(Grant No.BK20151470)
文摘A bionic flexible manipulator driven by pneumatic muscle actuator(PMA)can better reflect the flexibility of the mechanism.Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic manipulator system.Compared with traditional electro-hydraulic actuators,the structure of PMA is simple but possesses strong nonlinearity and flexibility,which leads to the difficulty in improving the control accuracy.In this paper,the configuration design of a bionic flexible manipulator is performed by human physiological map,the kinematic model of the mechanism is established,and the dynamics is analyzed by Lagrange method.A fuzzy torque control algorithm is designed based on the computed torque method,where the fuzzy control theory is applied.The hardware experimental system is established.Through the co-simulation contrast test on MATLAB and ADAMS,it is found that the fuzzy torque control algorithm has better tracking performance and higher tracking accuracy than the computed torque method,and is applied to the entity control test.The experimental results show that the fuzzy torque algorithm can better control the trajectory tracking movement of the bionic flexible manipulator.This research proposes a fuzzy torque control algorithm which can compensate the error more effectively,and possesses the preferred trajectory tracking performance.
基金supported by the National Natural Science Foundation of China, China (No. 11572151)
文摘Firstly, a multi-field coupling finite element formulation of composited beam laminated with the photostrictive actuators is developed in this paper. Moreover, an optimal fuzzy active control algorithm is also proposed on the basis of the combination of optimal control and fuzzy one.This method opens a new avenue to resolve the contradiction between the linear system control method and nonlinear actuating characteristics of photostrictive actuators. The desired control for suppressing multi-modal vibration of photoelectric laminated beam is firstly obtained through optimal control and then the fuzzy control is used to approach the desired mechanical strain induced by photostrictive actuators. Thus, the multi-mode vibration control of beam is realized.In the design process of optimal fuzzy controller, the design of fuzzy control is independent of optimal control. The simulation results demonstrate that the proposed control method can effectively realize multi-modal vibration control of photoelectric laminated beams, and the control effect of optimal fuzzy control is better than that of optimal state feedback control.
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Supported by the National Natural Science Foundation of China(61472136)the Best Youth of the Education Department of Hunan Province(16B023)
文摘This paper focuses on the stability analysis of nonlinear networked control system with integral quadratic constraints(IQC) performance, dynamic quantization, variable sampling intervals, and communication delays. By using input-delay and parallel distributed compensation(PDC) techniques, we establish the Takagi-Sugeno(T-S) fuzzy model for the system, in which the sampling period of the sampler and signal transmission delay are transformed to the refreshing interval of a zero-order holder(ZOH). By the appropriate Lyapunov-Krasovskii-based methods, a delay-dependent criterion is derived to ensure the asymptotic stability for the system with IQC performance via the H∞ state feedback control. The efficiency of the method is illustrated on a simulation exampler.
文摘This paper presents an analysis of the KM （Karnik-Mendel） algorithms performance under real time implementation using 3 types： the non-iterative, the iterative and the enhanced, and their feasibility for real-time interval type 2 fuzzy logic control system applications. The results are also compared against NT （Nie-Tan） method that is one of the fastest and simplest defuzzification methods. Because the DC （direct current） servo-motor is one of the most used motors in different industrial applications and the model of the motor is nonlinear, this motor was selected for validating the implementation in real time hardware. This DC motor is a perfect option for studying the real time performance of KM algorithms in order to show up its limits and possibilities for real-time control system applications. These methodologies are implemented in National Instruments LabVIEW FPGA （field programmable gate array） module hardware which is one of the most used platforms in the industry. The results show that the E-KM （enhanced KM） algorithm and the NT method present good results for implementing real-time control applications in real time hardware. Although fuzzy logic type 2 is a good option for working with nonlinear and noise from the sensors, the defuzzification method has to react in a short period of time in order to allow good control response. Hence, a complete study of defuzzification is needed for improving the real time implementations of fuzzy type 2.
文摘A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.
文摘Double-column bridge piers are prone to local damage during earthquakes,leading to the destruction of bridges.To improve the earthquake resistance of double-column bridge piers,a novel swing column device(SCD),consisting of a magnetorheological(MR)damper,a current controller,and a swing column,was designed for the present work.To verify the seismic energy dissipation ability of the SCD,a lumped mass model for a double-column bridge pier with the SCD was established according to the low-order modeling method proposed by Steo.Furthermore,the motion equation of the double-column bridge pier with the SCD was established based on the D′Alembert principle and solved with the use of computational programming.It was found that the displacement response of the double-column bridge pier was effectively controlled by the SCD.However,due to rough current selection and a time delay,there is a significant overshoot of the bridge acceleration using SCD.Hence,to solve the overshoot phenomenon,a current controller was designed based on fuzzy logic theory.It was found that the SCD design based on fuzzy control provided an ideal shock absorption effect,while reducing the displacement and acceleration of the bridge pier by 36.43%‒40.63%and 30.06%‒33.6%,respectively.
文摘This paper uses a methodology based in Fuzzy Sets Theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae)—the soybean aphid, and its predator, Orius insidiosus (Hemiptera: Anthocoridae) and to propose a biological control to soybean aphid. Economic thresholds were already developed for this pest. The model includes biotic (predator) and abiotic (temperature) factors, which affect the soybean aphid population dynamics. The dynamic model results in a fuzzy model that preserves the biological meaning and nature of the predator-prey model. The paper also includes a comparison between the fuzzy model and real data reported in the literature. Subsequently, we propose a biological control to soybean aphid by another fuzzy rule-based system. This model has allowed to predict timing and releasing number of predators for soybean aphid biological control. On the one hand, the soybean aphid has still not found in Brazil. Therefore, before any eventual invasion, a predictive model to enhance biological control program is desirable. On the other hand, the soybean aphid has become the most devastating insect pest of soybeans in the United States. Brazil is the second largest exporter of soybean at present, after the USA and before Argentina. According to the Bureau of Agriculture of the USA, it has been estimated that Brazil will be the largest soybean exporter in 2023.
基金Dr.Ali Jameel and Noraziah Man are very grateful to the Ministry of Higher Education of Malaysia for providing them with the Fundamental Research Grant Scheme(FRGS)S/O No.14188 that supported this research.
文摘Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an efficient way to examine and analyze the accuracy of linear and nonlinear problems.The main aim of this work is to explore the approximate solutions of fuzzy Volterra integral equations(both linear and nonlinear)with a separable kernel via HAM.This method provides a reliable way to ensure the convergence of the approximation series.A new general form of HAM is presented and analyzed in the fuzzy domain.A qualitative convergence analysis based on the graphical method of a fuzzy HAM is discussed.The solutions sought by the proposed method show that the HAM is easy to implement and computationally quite attractive.Some solutions of fuzzy second kind Volterra integral equations are solved as numerical examples to show the potential of the method.The results also show that HAM provides an easy way to control and modify the convergence area in order to obtain accurate solutions.
基金supported in part by the Australian Research Council(DP240100830)。
文摘Sliding mode control(SMC)is a widely adopted control technology known for its robustness and simplicity.The essence of SMC is to use discontinuous control to drive a system into a pre-defined motion,called the sliding mode,which is designed with desirable dynamical properties.In the sliding mode,the controlled system is insensitive to the matched uncertainties and disturbances.Most SMC theory and methods have been developed based on the dynamical systems in the continuous-time domain,where switching functions play a critical role.Ideal switching is supposed to be instantaneous,activating as soon as the switching condition is met.However,in practice,switching mechanisms are affected by imperfections such as time delays,unmodeled dynamics,defects,digitization effects,and actuation limitations,which can degrade the salient properties of SMC.Understanding these effects and developing mitigation strategies are essential for industrial applications.Furthermore,the advent of networked control environments presents new challenges like limited communication bandwidth,latency and cyberattack,which have seen the emergence of the event-triggered SMC recently.Despite these significant advances,there is a lack of comprehensive studies which examine the commonalities and distinctions of utilizing switching in SMC across the continuous-time and discrete-time domains and beyond.This paper investigates the role of switching in SMC from a spatio-temporal perspective,considering both state-space and time aspects.The aim is to facilitate better understanding of its effects and misbehaviors,and to unlock its full potential for future applications.The interplay between SMC methods in the continuous-time and discrete-time domains is analyzed,and their shared principles and unique challenges are identified.Furthermore,important technical issues relating to switching across these time domains are explored,and several myths and pitfalls in their theory and applications are depicted.The relationships of SMC with other switching-based control systems such as switched control systems,fuzzy control systems,and event-triggered control systems are discussed.The impact of networked control environments on SMC in the continuous-time and discrete-time domains is also examined.Finally,key challenges and opportunities are outlined for future work in SMC and beyond.
文摘To effectively select risk control schemes in uncertain environments,this paper has proposed an analysis and evaluation method based on the fuzzy comprehensive evaluation method.Firstly,enterprises have adopted the brainstorming method and the Delphi method to identify risks in engineering projects,and organized the identified risks in the form of checklists to facilitate further analysis.Secondly,the fuzzy comprehensive evaluation theory was introduced to determine the comparison matrix of each risk factor and its weight.Furthermore,the top five risk factors in terms of weight ranking were taken as the evaluation factors for the selection of risk control plans.The plans were scored through the weighted scoring method,and the optimal risk control plan was determined based on the score.Finally,the feasibility of the proposed selection technology was verified through A research example of the risk control plan assessment for the construction project of Enterprise A.
