An intelligent servo drive system for a permanent magnet-assisted synchronous reluctance motor (P... more An intelligent servo drive system for a permanent magnet-assisted synchronous reluctance motor (PMASynRM) that can adapt to the control requirements considering the motor’s nonlinear and time-varying natures is developed in this study. A recurrent wavelet fuzzy neural network (RWFNN) with intelligent backstepping control is proposed to achieve this. In this study, first, a maximum torque per ampere (MTPA) controlled PMASynRM servo drive is introduced. A lookup table (LUT) is created, which is based on finite element analysis (FEA) results by using ANSYS Maxwell-2D dynamic model to determine the current angle command of the MTPA. Next, a backstepping control (BSC) system is created to accurately follow the desired position in the PMASynRM servo drive system while maintaining robust control characteristics. However, designing an efficient BSC for practical applications becomes challenging due to the lack of prior uncertainty information. To overcome this challenge, this study introduc...
This paper focuses on the economic power dispatch (EPD) operation of a microgrid in an OPAL-RT en... more This paper focuses on the economic power dispatch (EPD) operation of a microgrid in an OPAL-RT environment. First, a long short-term memory (LSTM) network is proposed to forecast the load information of a microgrid to determine the output of a power generator and the charging/discharging control strategy of a battery energy storage system (BESS). Then, a deep reinforcement learning method, the deep deterministic policy gradient (DDPG), is utilized to develop the power dispatch of a microgrid to minimize the total energy expense while considering power constraints, load uncertainties and electricity price. Moreover, a microgrid built in Cimei Island of Penghu Archipelago, Taiwan, is investigated to examine the compliance with the requirements of equality and inequality constraints and the performance of the deep reinforcement learning method. Furthermore, a comparison of the proposed method with the experience-based energy management system (EMS), Newton particle swarm optimization (...
2016 International Smart Grid Workshop and Certificate Program (ISGWCP), 2016
The policy and development of smart grid in Taiwan will be introduced in this study. In Taiwan, t... more The policy and development of smart grid in Taiwan will be introduced in this study. In Taiwan, the National Energy Program (NEP)- Smart Grid General Project Phase 1 was implemented from 2010 to 2013. Phase 2 was launched in 2014 and slated to continue for five years. The objectives of NEP- Smart Grid General Project are meant to enhance the robustness of the power grid, reduce greenhouse gas emission, increase the penetration rate of renewable energy and develop smart grid industry in Taiwan. This study will introduce the positioning of the Smart Grid General Project among overall smart grid development, the results of Phase 1, and the smart grid technology commercialization process of Phase 2.
... However, the bound of the lumped uncertainty is difficult to obtain in advance in practical a... more ... However, the bound of the lumped uncertainty is difficult to obtain in advance in practical applications. Therefore. an adaptive law is derived to adapt the value of the lumped uncertainty in real-time, and an adaptive backstepping sliding mode control law is proposed. ...
2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), 2017
In this study, a recurrent fuzzy cerebellar model articulation controller (RFCMAC) is proposed to... more In this study, a recurrent fuzzy cerebellar model articulation controller (RFCMAC) is proposed to regulate the active and reactive power of a single-stage three-phase grid-tied photovoltaic (PV) system during grid faults. The proposed RFCMAC uses the signed distance and input space repartition mechanisms to convert the dual input variables to sole input variable and repartition the input space to an appropriate quantity. Therefore, the structure and computation complexities of the proposed RFCMAC are lowered and make it more practical. Moreover, in order to satisfy the low-voltage ride through (LVRT) requirements and ensure the injected currents within the safety value, the active and reactive power commands of the controllers are calculated by using the current profile of the LVRT grid requirements and the current limit of the inverter. Furthermore, varied learning-rate coefficients for the online parameters learning are designed to guarantee the convergence of the tracking error f...
An ultrasonic motor (USM) drive using a two-phase current-source parallel-resonant inverter is pr... more An ultrasonic motor (USM) drive using a two-phase current-source parallel-resonant inverter is proposed in this study. A single-phase equivalent model of the USM is first described. Then, the operating principles of the newly designed driving circuit for the USM, in which the inherent parasitic capacitances formed by the polarized piezoelectric ceramic of the USM are parts of the two parallel- resonant tanks, is introduced. Since the dynamic characteristics of the USM are greatly influenced by the variation in the quality factors of the parallel- resonant tanks, two transformers are added to feed the stored energy in the resonant tanks back to the DC source to reduce the quality factors. Some experimental results are provided to demonstrate the effectiveness of the proposed driving circuit.
The dynamic response of a slider-crank mechanism which is driven by a separately-excited DC motor... more The dynamic response of a slider-crank mechanism which is driven by a separately-excited DC motor is studied in this paper. The rod and crank are assumed to be rigid. The Hamilton’s principle and Lagrange multiplier method are applied to formulate the equation of motion. Reducing the differential-algebraic equations and employing the Runge-Kutta numerical method, the dynamic response of the mechanism motion and armature current are obtained. Finally, numerical examples show the dynamic response of the different quality including the angular velocities, angular acceleration of crank, and armature current and results are compared to give good picture for the slider-crank mechanism.
An intelligent complementary sliding-mode control (CSMC) (ICSMC) is proposed in this paper for th... more An intelligent complementary sliding-mode control (CSMC) (ICSMC) is proposed in this paper for the fault-tolerant control of a six-phase permanent-magnet synchronous motor (PMSM) drive system with open phases. First, the dynamics of the six-phase PMSM drive system with a lumped uncertainty is described in detail. Then, the fault detection and operating decision method is briefly introduced. Moreover, a CSMC is designed to stabilize the fault-tolerant control of the six-phase PMSM drive system. Furthermore, to improve the required control performance and to maintain the stability of the six-phase PMSM drive system under faulty condition, the ICSMC is developed. In this approach, a Takagi-Sugeno-Kang-type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) estimator with accurate approximation capability is employed to estimate the lumped uncertainty. In addition, the adaptive learning algorithms for the online training of the TSKFNN-AMF are derived using the Lyapunov theorem to guarantee the closed-loop stability. Additionally, to enhance the control performance of the proposed intelligent fault-tolerant control, a 32-b floating-point digital signal processor, TMS320F28335, is adopted for the implementation of the proposed fault-tolerant control system. Finally, some experimental results are illustrated to demonstrate the validity of the proposed fault-tolerant control for the six-phase PMSM drive system via ICSMC.
Communications in Nonlinear Science and Numerical Simulation, 2012
ABSTRACT In this paper, a robust control system combining backstepping and sliding mode control t... more ABSTRACT In this paper, a robust control system combining backstepping and sliding mode control techniques is used to realize the synchronization of two gap junction coupled chaotic FitzHugh–Nagumo (FHN) neurons in the external electrical stimulation. A backstepping sliding mode approach is applied firstly to compensate the uncertainty which occur in the control system. However, the bound of uncertainty is necessary in the design of the backstepping sliding mode controller. To relax the requirement for the bound of uncertainty, an adaptive backstepping sliding mode controller with a simple adaptive law to adapt the uncertainty in real time is designed. The adaptive backstepping sliding mode control system is robust for time-varying external disturbances. The simulation results demonstrate the effectiveness of the control scheme.Highlights► A backstepping sliding mode controller is firstly used to synchronize two coupled chaotic FHN neurons. ► Then, an adaptive law is derived to adapt the uncertainty of control system in real time. ► The adaptive backstepping sliding mode controller is robust for external disturbance. ► The simulation results demonstrate the effectiveness of the control scheme.
An intelligent servo drive system for a permanent magnet-assisted synchronous reluctance motor (P... more An intelligent servo drive system for a permanent magnet-assisted synchronous reluctance motor (PMASynRM) that can adapt to the control requirements considering the motor’s nonlinear and time-varying natures is developed in this study. A recurrent wavelet fuzzy neural network (RWFNN) with intelligent backstepping control is proposed to achieve this. In this study, first, a maximum torque per ampere (MTPA) controlled PMASynRM servo drive is introduced. A lookup table (LUT) is created, which is based on finite element analysis (FEA) results by using ANSYS Maxwell-2D dynamic model to determine the current angle command of the MTPA. Next, a backstepping control (BSC) system is created to accurately follow the desired position in the PMASynRM servo drive system while maintaining robust control characteristics. However, designing an efficient BSC for practical applications becomes challenging due to the lack of prior uncertainty information. To overcome this challenge, this study introduc...
This paper focuses on the economic power dispatch (EPD) operation of a microgrid in an OPAL-RT en... more This paper focuses on the economic power dispatch (EPD) operation of a microgrid in an OPAL-RT environment. First, a long short-term memory (LSTM) network is proposed to forecast the load information of a microgrid to determine the output of a power generator and the charging/discharging control strategy of a battery energy storage system (BESS). Then, a deep reinforcement learning method, the deep deterministic policy gradient (DDPG), is utilized to develop the power dispatch of a microgrid to minimize the total energy expense while considering power constraints, load uncertainties and electricity price. Moreover, a microgrid built in Cimei Island of Penghu Archipelago, Taiwan, is investigated to examine the compliance with the requirements of equality and inequality constraints and the performance of the deep reinforcement learning method. Furthermore, a comparison of the proposed method with the experience-based energy management system (EMS), Newton particle swarm optimization (...
2016 International Smart Grid Workshop and Certificate Program (ISGWCP), 2016
The policy and development of smart grid in Taiwan will be introduced in this study. In Taiwan, t... more The policy and development of smart grid in Taiwan will be introduced in this study. In Taiwan, the National Energy Program (NEP)- Smart Grid General Project Phase 1 was implemented from 2010 to 2013. Phase 2 was launched in 2014 and slated to continue for five years. The objectives of NEP- Smart Grid General Project are meant to enhance the robustness of the power grid, reduce greenhouse gas emission, increase the penetration rate of renewable energy and develop smart grid industry in Taiwan. This study will introduce the positioning of the Smart Grid General Project among overall smart grid development, the results of Phase 1, and the smart grid technology commercialization process of Phase 2.
... However, the bound of the lumped uncertainty is difficult to obtain in advance in practical a... more ... However, the bound of the lumped uncertainty is difficult to obtain in advance in practical applications. Therefore. an adaptive law is derived to adapt the value of the lumped uncertainty in real-time, and an adaptive backstepping sliding mode control law is proposed. ...
2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017 - ECCE Asia), 2017
In this study, a recurrent fuzzy cerebellar model articulation controller (RFCMAC) is proposed to... more In this study, a recurrent fuzzy cerebellar model articulation controller (RFCMAC) is proposed to regulate the active and reactive power of a single-stage three-phase grid-tied photovoltaic (PV) system during grid faults. The proposed RFCMAC uses the signed distance and input space repartition mechanisms to convert the dual input variables to sole input variable and repartition the input space to an appropriate quantity. Therefore, the structure and computation complexities of the proposed RFCMAC are lowered and make it more practical. Moreover, in order to satisfy the low-voltage ride through (LVRT) requirements and ensure the injected currents within the safety value, the active and reactive power commands of the controllers are calculated by using the current profile of the LVRT grid requirements and the current limit of the inverter. Furthermore, varied learning-rate coefficients for the online parameters learning are designed to guarantee the convergence of the tracking error f...
An ultrasonic motor (USM) drive using a two-phase current-source parallel-resonant inverter is pr... more An ultrasonic motor (USM) drive using a two-phase current-source parallel-resonant inverter is proposed in this study. A single-phase equivalent model of the USM is first described. Then, the operating principles of the newly designed driving circuit for the USM, in which the inherent parasitic capacitances formed by the polarized piezoelectric ceramic of the USM are parts of the two parallel- resonant tanks, is introduced. Since the dynamic characteristics of the USM are greatly influenced by the variation in the quality factors of the parallel- resonant tanks, two transformers are added to feed the stored energy in the resonant tanks back to the DC source to reduce the quality factors. Some experimental results are provided to demonstrate the effectiveness of the proposed driving circuit.
The dynamic response of a slider-crank mechanism which is driven by a separately-excited DC motor... more The dynamic response of a slider-crank mechanism which is driven by a separately-excited DC motor is studied in this paper. The rod and crank are assumed to be rigid. The Hamilton’s principle and Lagrange multiplier method are applied to formulate the equation of motion. Reducing the differential-algebraic equations and employing the Runge-Kutta numerical method, the dynamic response of the mechanism motion and armature current are obtained. Finally, numerical examples show the dynamic response of the different quality including the angular velocities, angular acceleration of crank, and armature current and results are compared to give good picture for the slider-crank mechanism.
An intelligent complementary sliding-mode control (CSMC) (ICSMC) is proposed in this paper for th... more An intelligent complementary sliding-mode control (CSMC) (ICSMC) is proposed in this paper for the fault-tolerant control of a six-phase permanent-magnet synchronous motor (PMSM) drive system with open phases. First, the dynamics of the six-phase PMSM drive system with a lumped uncertainty is described in detail. Then, the fault detection and operating decision method is briefly introduced. Moreover, a CSMC is designed to stabilize the fault-tolerant control of the six-phase PMSM drive system. Furthermore, to improve the required control performance and to maintain the stability of the six-phase PMSM drive system under faulty condition, the ICSMC is developed. In this approach, a Takagi-Sugeno-Kang-type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) estimator with accurate approximation capability is employed to estimate the lumped uncertainty. In addition, the adaptive learning algorithms for the online training of the TSKFNN-AMF are derived using the Lyapunov theorem to guarantee the closed-loop stability. Additionally, to enhance the control performance of the proposed intelligent fault-tolerant control, a 32-b floating-point digital signal processor, TMS320F28335, is adopted for the implementation of the proposed fault-tolerant control system. Finally, some experimental results are illustrated to demonstrate the validity of the proposed fault-tolerant control for the six-phase PMSM drive system via ICSMC.
Communications in Nonlinear Science and Numerical Simulation, 2012
ABSTRACT In this paper, a robust control system combining backstepping and sliding mode control t... more ABSTRACT In this paper, a robust control system combining backstepping and sliding mode control techniques is used to realize the synchronization of two gap junction coupled chaotic FitzHugh–Nagumo (FHN) neurons in the external electrical stimulation. A backstepping sliding mode approach is applied firstly to compensate the uncertainty which occur in the control system. However, the bound of uncertainty is necessary in the design of the backstepping sliding mode controller. To relax the requirement for the bound of uncertainty, an adaptive backstepping sliding mode controller with a simple adaptive law to adapt the uncertainty in real time is designed. The adaptive backstepping sliding mode control system is robust for time-varying external disturbances. The simulation results demonstrate the effectiveness of the control scheme.Highlights► A backstepping sliding mode controller is firstly used to synchronize two coupled chaotic FHN neurons. ► Then, an adaptive law is derived to adapt the uncertainty of control system in real time. ► The adaptive backstepping sliding mode controller is robust for external disturbance. ► The simulation results demonstrate the effectiveness of the control scheme.
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