Period-control and chaos-anti-control of a semiconductor laser using the twisted fiber

A novel semiconductor laser system is presented based on a twisted fiber.To study the period-control and chaos-anticontrol of the laser system,we design a type of optic path as a control setup using the combination of the twisted fiber and the polarization controller while we present a physical dynamics model of the delayed dual-feedback laser containing the twisted fiber effect.We give an analysis of the effect of the twisted fiber on the laser.We use the effects of the delayed phase and the rotation angle of the twisted fiber and the characteristics of the system to achieve control of the laser.The laser is deduced to a stable state,a double-periodic state,a period-6 state,a period-8 state,a period-9 state,a multi-period state,beat phenomenon,and so on.The periodic laser can be anti-controlled to chaos.Some chaos-anti-control area is found.The laser system is very useful for the study of chaos-control of the laser setup and the applications of some physics effects.

High-Speed,High-Power Motor Design for a Four-Legged Robot Actuator Optimized using the Weighted Sum and Response Surface Methods

In this paper,a design is presented for a high-speed,high-power motor for a four-legged robot actuator that was optimized using the weighted sum method(WSM)based on the Taguchi method,and the response surface method(RSM).First,output torque,torque constant,torque ripple,and efficiency were selected as objective functions for the optimized design.The sampling method was implemented to use a mixed orthogonal array and the single response characteristics of each objective function were compared using the Taguchi method.Moreover,to consider the multi-response characteristic of the objective functions,WSM was applied.Second,the 2D finite element analysis result of the RSM was compared with that using the WSM.Finally,an experiment was carried out on the manufactured motor and the optimized model is presented here.

Fuzzy Adaptive Control of a Fractional Order Chaotic System With Unknown Control Gain Sign Using a Fractional Order Nussbaum Gain

In this paper we propose an improved fuzzy adaptive control strategy, for a class of nonlinear chaotic fractional order(SISO) systems with unknown control gain sign. The online control algorithm uses fuzzy logic sets for the identification of the fractional order chaotic system, whereas the lack of a priori knowledge on the control directions is solved by introducing a fractional order Nussbaum gain. Based on Lyapunov stability theorem, stability analysis is performed for the proposed control method for an acceptable synchronization error level. In this work, the Gr ¨unwald-Letnikov method is used for numerical approximation of the fractional order systems. A simulation example is given to illustrate the effectiveness of the proposed control scheme.

Robust Finite-time Synchronization of Non-identical Fractional-order Hyperchaotic Systems and Its Application in Secure Communication

This paper proposes a novel adaptive sliding mode control(SMC) method for synchronization of non-identical fractional-order(FO) chaotic and hyper-chaotic systems. Under the existence of system uncertainties and external disturbances,finite-time synchronization between two FO chaotic and hyperchaotic systems is achieved by introducing a novel adaptive sliding mode controller(ASMC). Here in this paper, a fractional sliding surface is proposed. A stability criterion for FO nonlinear dynamic systems is introduced. Sufficient conditions to guarantee stable synchronization are given in the sense of the Lyapunov stability theorem. To tackle the uncertainties and external disturbances, appropriate adaptation laws are introduced. Particle swarm optimization(PSO) is used for estimating the controller parameters. Finally, finite-time synchronization of the FO chaotic and hyper-chaotic systems is applied to secure communication.

A Review of Gallium Nitride Power Device and Its Applications in Motor Drive

Wide band-gap gallium nitride(GaN)device has the advantages of large band-gap,high electron mobility and low dielectric constant.Compared with traditional Si devices,these advantages make it suitable for fast-switching and high-power-density power electronics converters,thus reducing the overall weight,volume and power consumption of power electronic systems.As a review paper,this paper summarizes the characteristics and development of the state-of-art GaN power devices with different structures,analyzes the research status,and forecasts the application prospect of GaN devices.In addition,the problems and challenges of GaN devices were discussed.And thanks to the advantages of GaN devices,both the power density and efficiency of motor drive system are improved,which also have been presented in this paper.

Metallic spherical anechoic chamber for antenna pattern measurement

Anechoic chambers are used for indoor antenna measurements. The common method of constructing an anechoic chamber is to cover all inside walls by the electromagnetic absorbers. In this paper, a fully metallic spherical chamber structure is presented in which the propagation of the electromagnetic waves inside the chamber is controlled and they are guided to an absorber. In the proposed method, an appropriate quiet zone is obtained, and unlike ordinary anechoic chambers, the absorber usage amount is reduced greatly. The performance of the chamber is evaluated by simulation. The results show that the proposed method could provide a useful technique for the indoor antenna measurements.

A Proposed Design, Implementation and Control of Doubly Fed Switched Reluctance Motor

In this paper,rotor of switched reluctance motor(SRM)is employed by mounting copper windings on the rotor poles as well as the stator poles.Rotor and stator windings are excited from DC supply in order to increase the developed electro-magnetic torque;thus enhancing the output power of the drive and keeping the system compactness.Furthermore,the proposed SRM offers higher reliability than conventional one,if excitation of rotor windings is lost,the drive will turn into a conventional SRM,the drive will continue running as a conventional SRM.Finite element method magnetics(FEMM)software is applied to obtain the magnetic characteristics of the proposed SRM.A control strategy for excitation of rotor and stator windings is presented.MATLAB/Simulink modeling of the proposed SRM is given and validated by practical experiment.Experimental Results on a prototype show that the proposed SRM is capable of achieving an increased torque compared with conventional SRM drive.

Renewable and Storage Energy Integration for Smart Grid Housing

This paper presents the design, implementation and testing of an embedded system that integrates solar and storage energy resources to smart homes within the smart mierogrid. The proposed system provides the required home energy by installing renewable energy and storage devices. It also manages and schedules the power flow during peak and off-peak periods. In addition, a two-way communication protocol is developed to enable the home owners and the utility service provider to improve the energy flow and the consumption efficiency. The system can be an integral part for homes in a smart grid or smart microgrid power networks. A prototype for the proposed system was designed, implemented and tested by using a controlled load bank to simulate a scaled random real house consumption behavior. Three different scenarios were tested and the results and findings are reported. Moreover, data flow security among the home, home owners and utility server is developed to minimize cyber-attaeks.

Ear Field Adaptive Noise Control for Snoring:An Real-time Experimental Approach

In this paper, an active noise control(ANC) system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer's bed partner. An adaptive least mean square(LMS)algorithm optimized for different kinds of snore signals is introduced and theoretically analyzed. Also, a residual noise masking approach is proposed to further reduce the effect of the snore noise without interfering with the LMS algorithm. Computer simulations followed by real-time experiments are conducted to demonstrate the feasibility of the snore ANC systems based on a pillow setup. For the optimum effect based on the characteristics of human hearing, the performance of the proposed approach is evaluated by using the multi-channel feedforward ANC systems based on the filtered-X least mean square(FXLMS) algorithm.Compared with a traditional headboard setup for snoring noise control, the proposed snore ANC systems optimized for ear field operation yield much higher noise reduction around the ears of the snorer's bed partner.

Research on Cogging Force Suppression for Toroidal PMLSM Based on Disturbance Observer

For a new type of toroidal permanent magnet linear motor(TPMLSM), this paper analyzes the thrust fluctuation in the constant acceleration operation of the motor from the Angle of the cogging force of the linear motor. For the motor whose structure has been determined and processed, the structural parameters of the motor cannot be changed, and its performance cannot be improved from the perspective of the motor body.Therefore, this paper tries to consider the influence of the cogging force on the normal operation of the motor from the perspective of control. In this paper, starting from the body structure of motor, first on the annular linear motor of the cogging force characteristics were extracted, and its expression is obtained by Fourier decomposition, then investigated considering the cogging force and does not consider the cogging force control of motor model, it can be seen that the control performance deteriorates significantly after considering cogging force of the motor, and the acceleration fluctuation increases significantly during the operation of the motor. On this basis, disturbance observation algorithm is introduced, and feedforward compensation is carried out by extracting the characteristic values of the disturbance model. The results show that the disturbance observer can suppress the thrust fluctuation caused by the motor cogging force to a large extent, and it can reduce the peak-to-peak value of the thrust fluctuation by more than 85% during the motor acceleration operation.

A Data-driven Method for Fast AC Optimal Power Flow Solutions via Deep Reinforcement Learning

With the increasing penetration of renewable energy,power grid operators are observing both fast and large fluctuations in power and voltage profiles on a daily basis.Fast and accurate control actions derived in real time are vital to ensure system security and economics.To this end,solving alternating current(AC)optimal power flow(OPF)with operational constraints remains an important yet challenging optimization problem for secure and economic operation of the power grid.This paper adopts a novel method to derive fast OPF solutions using state-of-the-art deep reinforcement learning(DRL)algorithm,which can greatly assist power grid operators in making rapid and effective decisions.The presented method adopts imitation learning to generate initial weights for the neural network(NN),and a proximal policy optimization algorithm to train and test stable and robust artificial intelligence(AI)agents.Training and testing procedures are conducted on the IEEE 14-bus and the Illinois 200-bus systems.The results show the effectiveness of the method with significant potential for assisting power grid operators in real-time operations.

Adaptive Virtual Synchronous Generator Considering Converter and Storage Capacity Limits

A virtual synchronous generator(VSG)control has been proposed as a means to control a voltage source converter interfaced generation and storage to retain the dynamics of a conventional synchronous generator.The storage is used to provide the inertia power and droop power in the VSG control to improve the frequency stability.Since the parameters in the VSG control can be varied,it is necessary for it to be tuned to be adaptive,in order to achieve an optimal response to grid frequency changes.However,the storage cannot provide infinite power and the converter has a strict power limitation which must be observed.The adaptive VSG control should consider these limitations,which have not been considered previously.This paper proposes an adaptive VSG control aimed at obtaining the optimal grid supporting services during frequency transients,accounting for converter and storage capacity limitations.The proposed control has been validated via hardware-in-the-loop testing.It is then implemented in storage co-located with wind farms in a modified IEEE 39-bus system.The results show that the proposed control stabilizes the system faster and has better cooperation with other VSGs,considering storage and converter limits.

Maximum Power Enhancement Under Partial Shadings Using a Modified Sudoku Reconfiguration

Partial shading is one of the important factors in reducing maximum power generation from PV(Photovoltaic)arrays.Maximum power generation can be improved by selecting a PV array through a Total-Cross-Tied(T-C-T)connection.However,maximum power generated from T-C-T can still be improved by distribution of shading over various rows.Due to distribution of shading,the current entering the node increases and results in improved maximum power generation.This can be done effectively by using Sudoku reconfiguration techniques.These techniques are economical,since they don’t require any sensors and switching networks.This technique only changes the physical location of the PV panel but the electrical connection between the panels remains the same.This paper proposes a Modified Sudoku reconfiguration pattern which enhances the maximum power from the T-C-T connected PV array.Furthermore,the theoretical calculation of row current and power output have been done for existing and proposed topologies under various shading patterns.The performance of the proposed pattern has been analyzed and compared using specifications,such as Global Maximum Power(GMP),Fill Factor(FF),mismatch losses,and efficiency.From the results,it can be concluded that the Modified Sudoku reconfiguration enhances the GMP under all shading conditions.

Strategic Bidding in Distribution Network Electricity Market Focusing on Competition Modeling and Uncertainties

Developing the electricity market at the distribution level can facilitate the energy transactions in distribution networks with a high penetration level of distributed energy resources(DERs)and microgrids(MGs).However,the lack of comprehensive information about the marginal production cost of competitors leads to uncertainties in the optimal bidding strategy of participants.The electricity demand within the network and the price in the wholesale electricity market are two other sources of the uncertainties.In this paper,a day-ahead-market-based framework for managing the energy transactions among MGs and other participants in distribution networks is introduced.A game-theory-based method is presented to model the competition and determine the optimal bidding strategy of participants in the market.Robust optimization technique is employed to capture the uncertainties in the marginal cost of competitors.Additionally,the uncertainties in demand are modeled using a scenario-based stochastic approach.The results ob-tained from case studies reveal the merit of considering competition modeling and uncertainties.

Deep Reinforcement Learning Based Real-time AC Optimal Power Flow Considering Uncertainties

Modern power systems are experiencing larger fluctuations and more uncertainties caused by increased penetration of renewable energy sources(RESs) and power electronics equipment. Therefore, fast and accurate corrective control actions in real time are needed to ensure the system security and economics. This paper presents a novel method to derive realtime alternating current(AC) optimal power flow(OPF) solutions considering the uncertainties including varying renewable energy and topology changes by using state-of-the-art deep reinforcement learning(DRL) algorithm, which can effectively assist grid operators in making rapid and effective real-time decisions. The presented DRL-based approach first adopts a supervised-learning method from deep learning to generate good initial weights for neural networks, and then the proximal policy optimization(PPO) algorithm is applied to train and test the artificial intelligence(AI) agents for stable and robust performance. An ancillary classifier is designed to identify the feasibility of the AC OPF problem. Case studies conducted on the Illinois 200-bus system with wind generation variation and N-1 topology changes validate the effectiveness of the proposed method and demonstrate its great potential in promoting sustainable energy integration into the power system.

Nonlinear Coordinated Passivation Control of Single Machine Infinite Bus Power System with Static Var Compensator

We propose a nonlinear coordinated control of the generator excitation and the static var compensator(SVC) in order to enhance the transient stability and voltage regulation of power system by the passivation approach. SVC is installed in the middle of the transmission line of power system and consists of a single machine infinite bus(SMIB) system. The design of the proposed controller consists of two parts. On one hand,the generator excitation controller is designed based on a backstepping controller. On the other hand, the conception of SVC control input is based on the coordinated passivation approach,which can guarantee the asymptotic stability of the closed-loop system. The simulation results show the effectiveness of the proposed controller compared with other methods, which ensures better performance than the uncoordinated control when the system is subjected to a disturbance.

Coordinated Control of DFIG Converters to Comply with Reactive Current Requirements in Emerging Grid Codes

The doubly-fed induction generator(DFIG)is considered to provide a low-reactance path in the negative-sequence system and naturally comply with requirements on the negative-sequence reactive current in emerging grid codes.This paper shows otherwise and how the control strategy of converters plays a key role in the formation of the active and reactive current components.After investigating the existing control strategies from the perspective of grid code compliance and showing how they fail in addressing emerging requirements on the negative-sequence reactive current,we propose a new coordinated control strategy that complies with reactive current requirements in grid codes in the positive-and negative-sequence systems.The proposed method fully takes advantage of the current and voltage capacities of both the rotor-side converter(RSC)and grid-side converter(GSC),which enables the grid code compliance of the DFIG under unbalanced three-phase voltages due to asymmetrical faults.The mathematical investigations and proposed strategy are validated with detailed simulation models using the Electric Power Research Institute(EPRI)benchmark system.The derived mathematical expressions provide analytical clarifications on the response of the DFIG in the negative-sequence system from the grid perspective.

Ferroresonance Overvoltage Mitigation Using STATCOM for Grid-connected Wind Energy Conversion Systems

We present the ferroresonance overvoltage mitigation concerning the power systems of the grid-connectcd wind energy conversion systems(WECSs).WECS is considered based on a doubly-fed induction generator(DFIG).Ferroresonance overvoltage associated with a single-pole outage of the line breaker is mitigated by fast regulating the reactive power using the static compensator(STATCOM).STATCOM controller is introduced,in which t>\o incorporated proportional-integral(PI)controllers are optimally tuned using a modified flow-er pollination algorithm(MFPA)as an optimization technique.To show the capability of the proposed STATCOM controller in mitigating the ferroresonance overvoltage,two test cases are introduced,which are based on the interconnection status of the power transformer used with the grid-connected DFIGs.The results show that the ferroresonance disturbance can occur for the power transformers installed in the wind farms although the transformer terminals are interconnected,and neither side of the transformer is isolated.Furthermore,as a mitigation method of ferroresonance overvoltage,the proposed STATCOM controller succeeds in improving the system voltage profile and speed profile of the wind turbine as well as protecting the system components against the ferroresonance overvoltage.

Locomotion trajectory with cooperative metrics in wireless sensor networks

Detection coverage control is one of the most important topics in the intrusion detection problem of wireless sensor networks （WSN）. However, its converse, i.e., to design an object locomotion trajectory in WSN, has not received enough attention. This article proposes a heuristic algorithm, namely, the security ＆ speed （SS） algorithm, to depict such a trajectory that takes into consideration both security and speed. The merit of the SS algorithm is its topology independency. When compared with traditional algorithms, the SS algorithm approaches the optimal trajectory better, and enjoys considerably lower computational load, and a better and adjustable tradeoff between trajectory security and speed.

Faulty Phase Identification for Transmission Line with Metal Oxide Varistor-protected Series Compensator

The nonlinear operation of metal oxide varistor(MOV)-protected series compensator in transmission lines introduces complications into fault detection approaches. The accuracy of a conventional fault detection schemes is adversely affected by continuous change of the system impedance and load current at the point of a series compensation unit. Thus, this study suggests a method for detecting the faulted phase in MOV-protected series-compensated transmission lines. Primarily, the fault feature is identified using the covariance coefficients of the current samples during the fault period and the current samples during the pre-fault period. Furthermore, a convenience fault detection index is established by applying the cumulative sum technique. Extensive validation through different fault circumstances is accomplished, including different fault positions,resistances, and inception times. The experimental results show that the proposed method performs well with high resistance or impedance faults, faults in noisy conditions, and close-in and far-end faults. The proposed method is simple and efficient for faulty phase detection in MOV-protected series-compensated transmission lines.