Fractional Gradient Descent RBFNN for Active Fault-Tolerant Control of Plant Protection UAVs

With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.

Review of Field Weakening Control Strategies of Permanent Magnet Synchronous Motors

Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the speed range under finite DC-bus voltage,extensive research on field weakening(FW)control strategies has been conducted.This paper summarizes the major FW control strategies of PMSMs,which are categorized into calculation-based methods,voltage closed-loop control methods,and model predictive control related methods.The existing strategies are analyzed and compared according to performance,robustness,and execution difficulty,which can facilitate the implementation of FW control.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

Model-free Speed Control of Single-phase Flux Switching Motor with an Asymmetrical Rotor

This paper proposes and implements a model-free open-loop iterative learning control(ILC)strategy to realize the speed control of the single-phase flux switching motor(FSM)with an asymmetrical rotor.Base on the proposed winding control method,the asymmetrical rotor enables the motor to generate continuous positive torque for positive rotation,and relatively small resistance torque for negative rotation.An initial iteration coefficient and variable iteration coefficient optimized scheme was proposed based on the characteristics of the hardware circuit,thereby forming the model-free strategy.A series of prototype experiments was carried out.Experimental results verify the effectiveness and practicability of the proposed ILC strategy.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Enhanced Fuzzy Logic Control Model and Sliding Mode Based on Field Oriented Control of Induction Motor

In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.

Analyzing the Combination Effects of Repetitive Transcranial Magnetic Stimulation and Motor Control Training on Balance Function and Gait in Patients with Stroke-Induced Hemiplegia

Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.

Operation Control Method of Relay Protection in Flexible DC Distribution Network Compatible with Distributed Power Supply

A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.

Indirect Vector Control of Linear Induction Motors Using Space Vector Pulse Width Modulation

Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance applications.This trend promotes the development of precise and efficient control schemes for individual motors.This research aims to present a novel framework for speed and thrust force control of LIM using space vector pulse width modulation(SVPWM)inverters.The framework under consideration is developed in four stages.To begin,MATLAB Simulink was used to develop a detailed mathematical and electromechanical dynamicmodel.The research presents a modified SVPWM inverter control scheme.By tuning the proportional-integral(PI)controller with a transfer function,optimized values for the PI controller are derived.All the subsystems mentioned above are integrated to create a robust simulation of the LIM’s precise speed and thrust force control scheme.The reference speed values were chosen to evaluate the performance of the respective system,and the developed system’s response was verified using various data sets.For the low-speed range,a reference value of 10m/s is used,while a reference value of 100 m/s is used for the high-speed range.The speed output response indicates that themotor reached reference speed in amatter of seconds,as the delay time is between 8 and 10 s.The maximum amplitude of thrust achieved is less than 400N,demonstrating the controller’s capability to control a high-speed LIM with minimal thrust ripple.Due to the controlled speed range,the developed system is highly recommended for low-speed and high-speed and heavy-duty traction applications.

Cascaded Model Predictive Control of Six-phase Permanent Magnet Synchronous Motor with Fault Tolerant Ability

In the field of high-power electric drives, multiphase motors have the advantages of high power-density, excellent fault tolerance and control flexibility. But their decoupling control and modulation process are much more complicated compared with three-phase motors due to the increased degree of freedom. Finite control set model predictive control can reduce the difficulties of controlling six-phase motors because it does not require modulation process. In this paper, a cascaded model predictive control strategy is proposed for the optimal control of high-power six-phase permanent magnet synchronous motors. Firstly, the current prediction model of torque and harmonic subspaces are established by decoupling the six-phase spatial variables. Secondly, a cascaded cost function with fault-tolerant capability is proposed to eliminate the weighting factor in the cost function. And finally, the proposed strategy is demonstrated through theoretical analysis and experiments. It is validated that the proposed method is able to maintain excellent steady-state control accuracy and fast dynamic response while significantly reduce the control complexity of the system. Besides, it can easily achieve fault-tolerant operation under open-phase fault.

Fault Detection for Motor Drive Control System of Industrial Robots Using CNN-LSTM-based Observers

The complex working conditions and nonlinear characteristics of the motor drive control system of industrial robots make it difficult to detect faults.In this paper,a deep learning-based observer,which combines the convolutional neural network(CNN)and the long short-term memory network(LSTM),is employed to approximate the nonlinear driving control system.CNN layers are introduced to extract dynamic features of the data,whereas LSTM layers perform time-sequential prediction of the target system.In terms of application,normal samples are fed into the observer to build an offline prediction model for the target system.The trained CNN-LSTM-based observer is then deployed along with the target system to estimate the system outputs.Online fault detection can be realized by analyzing the residuals.Finally,an application of the proposed fault detection method to a brushless DC motor drive system is given to verify the effectiveness of the proposed scheme.Simulation results indicate the impressive fault detection capability of the presented method for driving control systems of industrial robots.

Adaptive Gain Tuning Rule for Nonlinear Sliding-mode Speed Control of Encoderless Three-phase Permanent Magnet Assisted Synchronous Motor

In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control(NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous reluctance motor(PMa-Syn RM) with considering the parameter uncertainties. A nonlinear sliding surface whose parameters are altering with time is designed at first. The proposed NSMSC can minimize the settling time without any overshoot via utilizing a low damping ratio at starting along with a high damping ratio as the output approaches the target set-point. In addition, it eliminates the problem of the singularity with the upper bound of an uncertain term that is hard to be measured practically as well as ensures a rapid convergence in finite time, through employing a simple adaptation law. Moreover, for enhancing the system efficiency throughout the constant torque region, the control system utilizes the maximum torque per ampere technique. The nonlinear sliding surface stability is assured via employing Lyapunov stability theory. Furthermore, a simple sliding mode estimator is employed for estimating the system uncertainties. The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed speed estimation and the NSMSC approach for a 1.1-k W PMa-Syn RM under different speed references, electrical and mechanical parameters disparities, and load disturbance conditions.

Privacy Protection Based Access Control Scheme in Cloud-Based Services

With the rapid development of computer technology, cloud-based services have become a hot topic. They not only provide users with convenience, but also bring many security issues, such as data sharing and privacy issue. In this paper, we present an access control system with privilege separation based on privacy protection(PS-ACS). In the PS-ACS scheme, we divide users into private domain(PRD) and public domain(PUD) logically. In PRD, to achieve read access permission and write access permission, we adopt the Key-Aggregate Encryption(KAE) and the Improved Attribute-based Signature(IABS) respectively. In PUD, we construct a new multi-authority ciphertext policy attribute-based encryption(CP-ABE) scheme with efficient decryption to avoid the issues of single point of failure and complicated key distribution, and design an efficient attribute revocation method for it. The analysis and simulation result show that our scheme is feasible and superior to protect users' privacy in cloud-based services.

High-Speed Trains Automatic Operation with Protection Constraints: A Resilient Nonlinear Gain-based Feedback Control Approach

This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.

Architecture Design for Integrated Wide Area Protection and Control Systems

This paper firstly reviews the recent development in power system protection and control, with special attention paid to the wide-area and integrated protection, in order to look into future development of integration of protection and control for smart grids. This paper mainly reports on the development of integrated wide area protection and control for power systems. The concept of integrated wide area protection and control is introduced, in which a hierarchical protection and control system provides the protection and control of wide area or regional power substations/ plants and their associated power network. The system is mainly divided into three levels, the local, the substation/plant and the wide area/regional protection and control. The integrated functions at each level are described in details with an aim to develop an optimal coordination mechanism between the levels. One of the core elements in the system is the synchronised wide area communication network between the substations and the protection and control system, in which latest communication technology is employed. Another important player in the system is the wide area synchronized protection and control information platform, which not only enables the fusion three line of defence for power system protection and control, but also provides a perfect tool for the application of cloud computing to substations and power networks.

DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

The Brushless DC Motor drive systems are used widely with renewable energy resources.The power converter controlling technique increases the performance by novel techniques and algorithms.Conventional approaches are mostly focused on buck converter,Fuzzy logic control with various switching activity.In this proposed research work,the QPSO(Quantum Particle Swarm Optimization algorithm)is used on the switching state of converter from the generation unit of solar module.Through the duty cycle pulse from optimization function,the MOSFET(Metal-Oxide-Semiconductor Field-Effect Transistor)of the Boost converter gets switched when BLDC(Brushless Direct Current Motor)motor drive system requires power.Voltage Source three phase inverter and Boost converter is controlled by proportional-integral(PI)controller.Based on the BLDC drive,the load utilized from the solar generating module.Experimental results analyzed every module of the proposed grid system,which are solar generation utilizes the irradiance and temperature depends on this the Photovoltaics(PV)power is generated and the QPSO with Duty cycle switching state is determined.The Boost converter module is boost stage based on generation and load is obtained.Single Ended Primary Inductor Converter(SEPIC)and Zeta converter model is compared with the proposed logic;the proposed boost converter achieves the results.Three phase inverter control,PI,and BLDC motor drive results.Thus the proposed grid model is constructed to obtain the better performance results than most recent literatures.Overall design model is done by using MATLAB/Simulink 2020a.

Seismic protection of frame structures via semi-active control:modeling and implementation issues

Theoretical and practical issues concerning the multi-faceted task of mitigating the latero-torsional seismic response of a prototypal frame structure with asymmetric mass distribution are approached, Chevron braces with embedded magnetorheological dampers acting on the interstory drift are used to ensure additional energy dissipation. The semi-active control strategy employed to govern the modification of the damper characteristics via feedback is based on the selection of optimal forces according to a H2/LQG criterion, with respect to which the actual forces are regulated by a clipped-optimal logic. A dynamic observer is used to estimate the state through a non-collocated placement of the acceleration sensors. Several aspects to be addressed throughout the complex process including the design, modelization, and implementation phases of semi-active protection systems are discussed. Finally, experimental results obtained to mitigate the motion induced by ground excitation in a large-scale laboratory prototype, simulating the seismic response of a two-story building, are summarized.

Protection and Quality Control of Wild Chinese Herbal Medicine Resources in Nature Reserves by Taking Longyuwan Scenic Spot Within Funiu Mountain Nature Reserve as an Example

This paper discussed how to protect and control the quality of wild Chinese herbal medicine resources in nature reserves by taking Longyuwan National Forest Park within Funiu Mountain Nature Reserve as an example. Through the combination of three methods including literature review, visiting and investigational studies, and field surveys, the data of investigation, collection and collation were analyzed. According to data of surveys, collection and collation, problems related to the protection of wild Chinese herbal medicine resources faced by Longyuwan Scenic Spot within Funiu Mountain Nature Reserve were also analyzed and protection strategies and quality control of wild Chinese herbal medicine resources in this nature reserve were discussed. It was expected that the results would provide important scientific references for the sustainable development, protection and quality control of wild Chinese herbal medicine resources within nature reserves.

Immobilization of antibodies on the self-assembled monolayer by antigen-binding site protection and immobilization kinetic control

The orientation of the biological molecule immobi-lized on a solid surface has been critical in devel-opment of various applications. In this study, ori-entation of antibody was retained by protecting the antigen-binding site of the antibody prior to immo-bilization to -functionalized mixed self-assembled monolayer (SAM) of 12-mercaptododecanoic acid and 1-heptanethiol. More importantly, the number of immobilization bonds formed between each an-tigen-binding site protected antibody molecule and the solid surface was controlled by optimizing the mole fraction of the activated carboxyl group of the linker molecules in the mixed SAM. The amount of antibody used in this study was approximately equivalent to the amount for one monolayer surface coverage. The resulting activity of protected immo-bilized antibody was about 10 fold higher than that of random immobilized

Study on DeviceNet communication mechanism and its application in protection measurement and control system

To fit in with the developing requirement of int and communication of protective relays, a protection egrated functions of protection measurement, control measurement and control system based on DeviceNet fieldbus is designed. The communication mechanism of DeviceNet is studied and data trigger modes, communication connection, message types and other key technologies are analyzed. The object modeling and device description of the device are realized too. Results of network test, dynamic simulation and test in the field indicate that this system can accomplish all the communication tasks in real time and can make precise response to every kind of faults of the motor, transformer, line and capacitor. Moreover, this system has higher measurement precision and better control capability.