With the development of the national economy, the demand of electric power market has become higher than before. The stable and reliable power system is one of the important national economic securities. Reliability o...With the development of the national economy, the demand of electric power market has become higher than before. The stable and reliable power system is one of the important national economic securities. Reliability of generator excitation system is one of the important elements to determine the stability of the power system. Traditional PID cannot meet the requirements of the increasingly complex power system due to some defects. This essay introduces FLC control, combining with the traditional PID control. Using Matlab software, we analyze the curve and FLC is better than that by comparing with the traditional PID.展开更多
In this paper, the design of a proportional integral controller (PIC) plus fuzzy logic controller (FLC) for the negative output elementary super lift Luo converter (NOESLLC) operated in discontinuous conduction mode (...In this paper, the design of a proportional integral controller (PIC) plus fuzzy logic controller (FLC) for the negative output elementary super lift Luo converter (NOESLLC) operated in discontinuous conduction mode (DCM) is presented. In spite of the many benefits viz. the high voltage transfer gain, the high efficiency, and the reduced inductor current and the capacitor voltage ripples, it natured with non-minimum phase. This characteristic makes the control of NOESLLC cumbersome. Any attempt of direct controlling the output voltage may erupt to instability. To overcome this problem, indirect regulation of the output voltage based on the two-loop controller is devised. The savvy in the inductor current control improves the dynamic response of the output voltage. The FLC is designed for the outer (voltage) loop while the inner (current) loop is controlled by the PIC. For the developed ?19.6 V NOESLLC, the dynamic performances for different perturbations (line, load and component variations) are obtained for PIC plus FLC and compared with PIC plus PIC. The study of two cases is performed at various operating regions by developing the MATLAB/Simulink model.展开更多
The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations.Internet of Things(IoT)based Modern fish farming systems can significantly optimi...The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations.Internet of Things(IoT)based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish production.This objective requires intensive monitoring,prediction,and control by optimizing leading factors that impact fish growth,including temperature,the potential of hydrogen(pH),water level,and feeding rate.This paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish farming.The proposed fish farm control mechanism has a predictive optimization to deal with water quality control and efficient energy consumption problems.Fish farm indoor and outdoor values are applied to predict the water quality parameters,whereas a novel objective function is proposed to achieve an optimal fish growth environment based on predicted parameters.Fuzzy logic control is utilized to calculate control parameters for IoT actuators based on predictive optimal water quality parameters by minimizing energy consumption.To evaluate the efficiency of the proposed system,the overall approach has been deployed to the fish tank as a case study,and a number of experiments have been carried out.The results show that the predictive optimization module allowed the water quality parameters to be maintained at the optimal level with nearly 30%of energy efficiency at the maximum actuator control rate compared with other control levels.展开更多
In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear un...In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.展开更多
This paper presents the design of a non-linear controller to prevent an electric power system losing synchronism after a large sudden fault and to achieve good post fault voltage level. By Direct Feedback Linearizatio...This paper presents the design of a non-linear controller to prevent an electric power system losing synchronism after a large sudden fault and to achieve good post fault voltage level. By Direct Feedback Linearization (DFL) technique robust non-linear excitation controller is designed which will achieve stability enhancement and voltage regulation of power system. By utilizing this technique, there is a possibility of selecting various control loops for a particular application problem. This method plays an important role in control system and power system engineering problem where all relevant variables cannot be directly measured. Simulated results carried out on a single machine infinite bus power system model which shows the enhancement of transient stability regardless of the fault and changes in network parameters.展开更多
The performance of any fuzzy logic controller (FLC) is greatly dependent on its inference rules. In most cases, the closed-loop control performance and stability are enhanced if more rules are added to the rule base o...The performance of any fuzzy logic controller (FLC) is greatly dependent on its inference rules. In most cases, the closed-loop control performance and stability are enhanced if more rules are added to the rule base of the FLC. However, a large set of rules requires more on-line computational time and more parameters need to be adjusted. In this paper, a robust PD-type FLC is driven for a class of MIMO second order nonlin- ear systems with application to robotic manipulators. The rule base consists of only four rules per each de- gree of freedom (DOF). The approach implements fuzzy partition to the state variables based on Lyapunov synthesis. The resulting control law is stable and able to exploit the dynamic variables of the system in a lin- guistic manner. The presented methodology enables the designer to systematically derive the rule base of the control. Furthermore, the controller is decoupled and the procedure is simplified leading to a computationally efficient FLC. The methodology is model free approach and does not require any information about the sys- tem nonlinearities, uncertainties, time varying parameters, etc. Here, we present experimental results for the following controllers: the conventional PD controller, computed torque controller (CTC), sliding mode con- troller (SMC) and the proposed FLC. The four controllers are tested and compared with respect to ease of design, implementation, and performance of the closed-loop system. Results show that the proposed FLC has outperformed the other controllers.展开更多
The Unified Power Quality Conditioner (UPQC) plays an important role in the constrained delivery of electrical power from the source to an isolated pool of load or from a source to the grid. The proposed system can co...The Unified Power Quality Conditioner (UPQC) plays an important role in the constrained delivery of electrical power from the source to an isolated pool of load or from a source to the grid. The proposed system can compensate voltage sag/swell, reactive power compensation and harmonics in the linear and nonlinear loads. In this work, the off line drained data from conventional fuzzy logic controller. A novel control system with a Combined Neural Network (CNN) is used instead of the traditionally four fuzzy logic controllers. The performance of combined neural network controller compared with Proportional Integral (PI) controller and Fuzzy Logic Controller (FLC). The system performance is also verified experimentally.展开更多
In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a mo...In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a model-free fuzzy sliding mode control. The equivalent controller has been substituted for by a fuzzy system and the uncertainties are estimated on-line. The approach of the AFSMC has the learning ability to generate the fuzzy control actions and adaptively compensates for the uncertainties. Despite the high nonlinearity and coupling effects, the control input of the proposed control algorithm has been decoupled leading to a simplified control mechanism for robotic systems. Simulations have been carried out on a two link planar robot. Results show the effectiveness of the proposed control system.展开更多
With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant...With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant impacts to power system during their charging and discharging operations. This article established a model of single machine infinite bus (SMIB) power system considering EV as a case study of load disturbance for power system oscillation. The objective of this research is to enhance stability and overcome the drawbacks of traditional control algorithms such as power system stabilizer (PSS), PID controller and fuzzy logic controller (FLC). The implementation’s effect of FLC parallel with PID controller (Fuzzy-PID) has been shown in this paper. The speed deviation (?ω) and electrical power (Pe) are the important factors to be taken into consideration without EV (only change in mechanical torque), EV with change in the mechanical torque and sudden plug-in EV. The obtained result by nonlinear simulation using Matlab/Simulink of a SMIB power system with EV has shown the effectiveness of using (Fuzzy-PID) against all disturbances.展开更多
Some typical structural schemes of Fuzzy control have been surveyed. Besides general structure of fuzzy logic controller (FLC), the structural schemes include PID fuzzy controller, self-organizing fuzzy controller, se...Some typical structural schemes of Fuzzy control have been surveyed. Besides general structure of fuzzy logic controller (FLC), the structural schemes include PID fuzzy controller, self-organizing fuzzy controller, selftuning fuzzy controller, self-learning fuzzy controller, and expect fuzzy controller, etc. This survey focuses on the control principle, and provides a basis for potential applications. Most of the structures have been used in various control fields, one of application areas is in the metallurgy industry, e. g., the temperature control of the electric furnace, the control of the aluminum smelting process, etc. According to the application requirements, one can choose a structural scheme for special use.展开更多
文摘With the development of the national economy, the demand of electric power market has become higher than before. The stable and reliable power system is one of the important national economic securities. Reliability of generator excitation system is one of the important elements to determine the stability of the power system. Traditional PID cannot meet the requirements of the increasingly complex power system due to some defects. This essay introduces FLC control, combining with the traditional PID control. Using Matlab software, we analyze the curve and FLC is better than that by comparing with the traditional PID.
文摘In this paper, the design of a proportional integral controller (PIC) plus fuzzy logic controller (FLC) for the negative output elementary super lift Luo converter (NOESLLC) operated in discontinuous conduction mode (DCM) is presented. In spite of the many benefits viz. the high voltage transfer gain, the high efficiency, and the reduced inductor current and the capacitor voltage ripples, it natured with non-minimum phase. This characteristic makes the control of NOESLLC cumbersome. Any attempt of direct controlling the output voltage may erupt to instability. To overcome this problem, indirect regulation of the output voltage based on the two-loop controller is devised. The savvy in the inductor current control improves the dynamic response of the output voltage. The FLC is designed for the outer (voltage) loop while the inner (current) loop is controlled by the PIC. For the developed ?19.6 V NOESLLC, the dynamic performances for different perturbations (line, load and component variations) are obtained for PIC plus FLC and compared with PIC plus PIC. The study of two cases is performed at various operating regions by developing the MATLAB/Simulink model.
基金funded by the Ministry of Science,ICT CMC,202327(2019M3F2A1073387)this work was supported by the Institute for Information&communications Technology Promotion(IITP)(NO.2022-0-00980,Cooperative Intelligence Framework of Scene Perception for Autonomous IoT Device).
文摘The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations.Internet of Things(IoT)based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish production.This objective requires intensive monitoring,prediction,and control by optimizing leading factors that impact fish growth,including temperature,the potential of hydrogen(pH),water level,and feeding rate.This paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish farming.The proposed fish farm control mechanism has a predictive optimization to deal with water quality control and efficient energy consumption problems.Fish farm indoor and outdoor values are applied to predict the water quality parameters,whereas a novel objective function is proposed to achieve an optimal fish growth environment based on predicted parameters.Fuzzy logic control is utilized to calculate control parameters for IoT actuators based on predictive optimal water quality parameters by minimizing energy consumption.To evaluate the efficiency of the proposed system,the overall approach has been deployed to the fish tank as a case study,and a number of experiments have been carried out.The results show that the predictive optimization module allowed the water quality parameters to be maintained at the optimal level with nearly 30%of energy efficiency at the maximum actuator control rate compared with other control levels.
文摘In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.
文摘This paper presents the design of a non-linear controller to prevent an electric power system losing synchronism after a large sudden fault and to achieve good post fault voltage level. By Direct Feedback Linearization (DFL) technique robust non-linear excitation controller is designed which will achieve stability enhancement and voltage regulation of power system. By utilizing this technique, there is a possibility of selecting various control loops for a particular application problem. This method plays an important role in control system and power system engineering problem where all relevant variables cannot be directly measured. Simulated results carried out on a single machine infinite bus power system model which shows the enhancement of transient stability regardless of the fault and changes in network parameters.
文摘The performance of any fuzzy logic controller (FLC) is greatly dependent on its inference rules. In most cases, the closed-loop control performance and stability are enhanced if more rules are added to the rule base of the FLC. However, a large set of rules requires more on-line computational time and more parameters need to be adjusted. In this paper, a robust PD-type FLC is driven for a class of MIMO second order nonlin- ear systems with application to robotic manipulators. The rule base consists of only four rules per each de- gree of freedom (DOF). The approach implements fuzzy partition to the state variables based on Lyapunov synthesis. The resulting control law is stable and able to exploit the dynamic variables of the system in a lin- guistic manner. The presented methodology enables the designer to systematically derive the rule base of the control. Furthermore, the controller is decoupled and the procedure is simplified leading to a computationally efficient FLC. The methodology is model free approach and does not require any information about the sys- tem nonlinearities, uncertainties, time varying parameters, etc. Here, we present experimental results for the following controllers: the conventional PD controller, computed torque controller (CTC), sliding mode con- troller (SMC) and the proposed FLC. The four controllers are tested and compared with respect to ease of design, implementation, and performance of the closed-loop system. Results show that the proposed FLC has outperformed the other controllers.
文摘The Unified Power Quality Conditioner (UPQC) plays an important role in the constrained delivery of electrical power from the source to an isolated pool of load or from a source to the grid. The proposed system can compensate voltage sag/swell, reactive power compensation and harmonics in the linear and nonlinear loads. In this work, the off line drained data from conventional fuzzy logic controller. A novel control system with a Combined Neural Network (CNN) is used instead of the traditionally four fuzzy logic controllers. The performance of combined neural network controller compared with Proportional Integral (PI) controller and Fuzzy Logic Controller (FLC). The system performance is also verified experimentally.
文摘In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a model-free fuzzy sliding mode control. The equivalent controller has been substituted for by a fuzzy system and the uncertainties are estimated on-line. The approach of the AFSMC has the learning ability to generate the fuzzy control actions and adaptively compensates for the uncertainties. Despite the high nonlinearity and coupling effects, the control input of the proposed control algorithm has been decoupled leading to a simplified control mechanism for robotic systems. Simulations have been carried out on a two link planar robot. Results show the effectiveness of the proposed control system.
文摘With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant impacts to power system during their charging and discharging operations. This article established a model of single machine infinite bus (SMIB) power system considering EV as a case study of load disturbance for power system oscillation. The objective of this research is to enhance stability and overcome the drawbacks of traditional control algorithms such as power system stabilizer (PSS), PID controller and fuzzy logic controller (FLC). The implementation’s effect of FLC parallel with PID controller (Fuzzy-PID) has been shown in this paper. The speed deviation (?ω) and electrical power (Pe) are the important factors to be taken into consideration without EV (only change in mechanical torque), EV with change in the mechanical torque and sudden plug-in EV. The obtained result by nonlinear simulation using Matlab/Simulink of a SMIB power system with EV has shown the effectiveness of using (Fuzzy-PID) against all disturbances.
文摘Some typical structural schemes of Fuzzy control have been surveyed. Besides general structure of fuzzy logic controller (FLC), the structural schemes include PID fuzzy controller, self-organizing fuzzy controller, selftuning fuzzy controller, self-learning fuzzy controller, and expect fuzzy controller, etc. This survey focuses on the control principle, and provides a basis for potential applications. Most of the structures have been used in various control fields, one of application areas is in the metallurgy industry, e. g., the temperature control of the electric furnace, the control of the aluminum smelting process, etc. According to the application requirements, one can choose a structural scheme for special use.
