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Hydrofoils, as the actuators in hydrofoil attitude control systems (HACSs), are prone to faults and failures resulting in fatal accidents. In this article, a fault detection and estimation (FDE) strategy for such failures is presented based on a developed baseline model. The actuator fault is first parameterized by rewriting the dynamic model of the HACS. To address non-Gaussian factors in the joint estimation of the unscented Kalman filter (UKF), the Gaussian mixture model (GMM) is then integrated with the conventional UKF to approximate the complex distributions. Considering the problem of singular or ill-conditioned covariance matrices in the GMM, a covariance regularization approach based on the posterior estimation with the inverse-Wishart distribution is explored. Actuator anomalies can be detected via a scale metric utilizing the covariance matrices, together with the peak signal-to-noise ratio (PSNR) index, and accurate fault estimation is implemented by isolating fault information from the augmented state even in the presence of non-Gaussian disturbances. The effectiveness of the proposed strategy is validated by the experiment carried out on a hardware-in-loop (HIL) platform. The RMSE results for fault estimation obtained through the method proposed in this article exhibit the reductions of 19.23% and 31.77% for the constant-value fault scenario, 5.03% and 16.31% for the time-varying fault mode, when compared with the results obtained using the joint UKF and the Bayesian-based adaptive Kalman filter with Gaussian-inverse-Wishart mixture (BAKF-GIWM) techniques. These findings underscore the superior efficacy and performance of the proposed method.

Platinum (Pt) resistance temperature detectors (RTDs) are extensively employed as thin-film temperature sensors. However, agglomeration of Pt thin films occurs above 800 °C due to grain boundary grooving on the free surface, ultimately limiting its application at high temperatures. In this work, a Pt RTD was prepared by depositing multilayer Al2O3 protective layer on Pt thin films using electrodynamic jet printing (EJP) technology. The surface morphology and energy-dispersive spectroscopy spectrum of Pt thin films indicated that the voids on the surface are reduced, the grains’ growth is inhibited, and the movement and grooving of grain boundaries are limited. The test results indicate that the Pt RTD has not failed after six cycles of repeated warming and cooling from 800 °C to 1300 °C. After repeated cycles, the initial resistance of the Pt RTD is with a rate of change of less than 0.5%. In addition, the maximum relative deviation of the resistance in a single cycle is less than 1.6%. The Pt RTD with an 18-layer Al2O3 protective layer has undergone 12 cycles without failure, indicating a cycle life exceeding 10 h. Pt RTDs are stable over the range of 25 °C–1400 °C with correlation coefficients ${R}^{{2}}$ greater than 0.999, showing good linear correlation. It can withstand temperatures up to 1440 °C when printed with 18 protective layers. Compared to a Pt RTD without protective layers, the operating temperature is increased by 40%. This advancement provides a viable solution for the high-temperature monitoring of hot-end components in aerospace applications.

A deep learning-based cooperative fault diagnosis method is proposed in this study. The proposed method aims to improve the reliability of contemporary fault diagnosis methods for the multipermanent magnet synchronous motor (PMSM) drive system of four-wheel-independent-drive electric vehicles (4WID-EVs). Specifically, a novel 1-D signal to 2-D RGB image conversion method is proposed to transform the fault diagnosis task into an image classification problem, and the impressive image classification capability of the convolutional neural network (CNN) is utilized to achieve a highly accurate fault diagnosis function. Following this, CNNs of various architectures are trained using the constructed RGB image dataset, and the fault diagnosis accuracy under different architectures is compared. In addition, the adaptability of the trained network is increased by utilizing two adaptive factors to ensure that the trained CNN can be compatible with all untrained combinations of angular speed and load torque. Furthermore, by combining the designed single fault diagnosis method with directed-graph theory, a comprehensive evaluation criteria-based cooperative diagnosis method is proposed, which further improves the accuracy significantly. The effectiveness of the proposed fault diagnosis method is demonstrated via adequate comparison.

Conventional planar coils in an asymmetric structure cannot provide stable mutual inductance over a wide range. To address this issue, a novel asymmetric flat cross-shaped solenoid magnetic coupler (FCSMC) with high lateral misalignment tolerance for a multiple-receiver wireless power transfer system is proposed in this article, which can achieve freer charging positions for multiple automated guided vehicles at a single wireless charging station. Moreover, the analytical model of FCSMC is analyzed to simplify the design process based on the air-core mutual inductance equations. Then, a general design process is proposed for larger-scale FCSMC, which greatly reduces the workload of finite-element analysis (FEA) simulations. Finally, a 200/400 W prototype is built to verify the validity of the system within a $\pm$ 90-mm misalignment. In single-receiver cases with a 10-mm air gap, the comparisons with conventional planar square coils show that FCSMC's (planner square coils') output power fluctuates within 5% (27%) with maximum efficiency of 88.55% (92.01%), indicating that FCSMC sacrifices about 3% efficiency for 22% improvement in power stability. At the highest $\pm$90-mm misalignments, the output power fluctuates within 1% (19%), improving about 18%. In multiple-receiver cases for FCSMC, the charging positions are free with maximum efficiency of 87.96% when the shortest distance between ferrites of receivers is 20 mm or more.

This article addresses the issues of the bipartite time-varying formation (BTVF) control for multiagent systems (MASs) on signed digraphs. All the designs are performed under the assumptions that the leader and followers suffer from external disturbances, the control input signal of the leader is unreachable to any follower, and the state variables of the followers are unmeasurable. To begin with, an unknown input observer (UIO) is designed for each follower using a traditional interval observer to obtain the state estimates. To realize the BTVF tracking, a distributed consensus error dynamic system is constructed. Furthermore, a distributed unknown input reconstruction method is developed to estimate the multiple disturbances in the consensus error system. Then, an event-triggered BTVF control protocol is proposed which allows two antagonistic time-varying formations to be formed, while excluding Zeno behavior. A simulation of a group of wheeled robots is used to demonstrate the performance of the proposed methods.

This paper investigates the event-triggered fixed-time multi-lane fusion control for vehicle platoon systems with distance keeping constraints where the vehicles are spread in multiple lanes. To realize the fusion of vehicles in different lanes, the vehicle platoon systems are firstly constructed with respect to a two-dimensional (2-D) plane. In case of the collision and loss of effective communication, the distance constraints for each vehicle are guaranteed by a barrier function-based control strategy. In contrast to the existing results regarding the command filter techniques, the proposed distance keeping controller can constrain the distance tracking error directly and the error generated by the command filter is coped with by adaptive fuzzy control technique. Moreover, to offset the impacts of the unknown system dynamics and the external disturbances, an unknown input reconstruction method with asymptotic convergence is developed by utilizing the interval observer technique. Finally, two relative threshold triggering mechanisms are utilized in the proposed fixed-time multi-lane fusion controller design so as to reduce the communication burden. The corresponding simulation results also verify the effectiveness of the proposed strategy.

This article proposes a current deadbeat-based fault-tolerant control scheme for a dual three-phase permanent magnet synchronous generator with a high-resistance connection (HRC) fault. First, the voltage deviation caused by the HRC fault is deduced, and the postfault prediction model is established. Then, the instantaneous active power and reactive power are analyzed considering the negative-sequence voltage and current. To eliminate the fluctuation components and improve the steady-state performance, the fault-tolerant current references are designed under the condition of HRC fault. The deadbeat principle is employed to track the periodic dq current references accurately. The two targets of eliminating output power fluctuations and stabilizing electromagnetic torque are achieved. Finally, the virtual voltage vectors are synthesized to generate the reference voltage and suppress the harmonic current. The proposed method effectively restrains the fluctuations of active power, reactive power, dc-link voltage, and electromagnetic torque. The experimental results verify the effectiveness of the proposed method.

Intending to address the issue of sensor fault-tolerant control, a model-free adaptive fault-tolerant constrained control strategy is proposed with virtual sensor technology. The novel introduction of observer-based model-free adaptive control to fault-tolerant control brings benefits to the nonlinear systems with unknown dynamics in the presence of sensor faults. In the design procedures, the dynamic linearization technique is utilized first to establish the equivalent linear model of nonlinear systems. Then, the virtual sensor technology is introduced by designing the novel state-observer-based estimation algorithm to fulfill the data-driven system dynamic and sensor fault modeling. Besides, the broad learning technique is employed with offline training to provide output information for observer-based data-driven modeling under the fault case. Based on the data-driven model, the fault-tolerant constrained control scheme is explored with the anti-windup compensator against input constraints caused by actuator saturation, and the stability analysis is supplied. Finally, the simulations are carried out for both affine and non-affine nonlinear systems to manifest the effectiveness and superiority of the proposed control strategy. [ABSTRACT FROM AUTHOR]

An accurate and efficient fault diagnosis method for battery systems is crucial to ensuring the safety of battery packs. Addressing the issue of insufficient actual fault data in battery operations, this paper proposes an intelligent fault diagnosis method based on feature-enhanced stochastic configuration networks and adversarial domain expansion of imbalanced battery fault data (AFDEM-FESCN). Firstly, we designed an adversarial fault domain data expansion method (AFDEM). By learning the distribution of fault data through adversarial training, the distribution of sample domains is balanced, thereby reducing model bias. Subsequently, we adjusted the distribution of SCN iterative parameters and added a linear feature layer. This enhances the feature extraction capability of the network through distribution overlay, enabling fault diagnosis. Finally, the effectiveness and feasibility of the proposed method were validated through a practical battery system fault diagnosis case, achieving a diagnostic accuracy of 92.1%. Experimental results demonstrate that the AFDEM-FESCN method exhibits good accuracy in battery system fault diagnosis, providing an effective solution to the challenge of imbalanced data in intelligent fault diagnosis. [ABSTRACT FROM AUTHOR]

Self-triggered pseudo terminal ingredients are proposed in this study for the classic dual-mode robust model predictive control (RMPC) of discrete-time linear systems. By resorting to the off-line design of pseudo terminal ingredients, viz. pseudo terminal set and pseudo terminal cost, the optimization problem to be solved online is transformed into several subproblems with short prediction horizons. Furthermore, the controller design is based on the nominal system state, which enables a self-triggered mechanism during the implementation. The proposed approach is able to steer the system state into a predetermined terminal constraint set via intermittent samplings. The resultant computational and communicational burden for the online part is significantly reduced, which brings great convenience for band-limited practical systems. Simulations demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The grid-connected system, composed of the multi-inverters with LCL filters, may cause harmonic amplification of grid-connected current by harmonic excitation, even oscillation of the system in severe cases. Therefore, analyzing the stability and harmonic interaction of the multi-inverter system is of great significance in improving the system’s power quality. According to the structure of a grid-connected system composed of the multi-inverters with LCL filters, the equivalent single-inverter model of the main circuit and control system are established, respectively. The grid-connected system's stability is analyzed using this model, and the correctness of the equivalent single-inverter model is verified by simulation and experiment. To improve the phase margin of the grid-connected inverter and suppress the harmonic interaction between grid-connected inverters and the power grid, a double second-order filter is added to the control system of the inverters. The effectiveness of this method is verified by simulation and experiment.

As an important component of microgrid system, the grid-connected inverter is composed of power electronic devices, which makes the system lack physical inertia and exhibit low output impedance. Especially in the transition process of grid connection, a large current impact will be generated, which may make the system unstable. Therefore, in response to these problems, a nonlinear control method is proposed that enables the grid-connected inverter to switch freely between grid-connected mode and island mode. The linear control part introduces the mechanical equations of the rotor of the synchronous motor, which has virtual inertia and damping, and at the same time derives the corresponding mathematical model. As regards the nonlinear control part, the nonlinear controller is designed by integrating the integral sliding mode control method and backstepping control method. Meanwhile, considering the uncertainties including external disturbances, measurement errors and modelling errors, an observer based on the radial basis function neural network (RBFNN) is proposed to estimate the uncertainties to offset their influence. Then, the stability of the control system is proved by Lyapunov stability criterion. Finally, the simulation results prove that the proposed control scheme can realize the stability of the microgrid system in several operation modes and ensure the sound dynamic performance with quick response comparing with other nonlinear control methods.

In order to handle the problem of frequency fluctuations caused by load disturbances in multi-area interconnected power systems, a sliding mode control strategy for hybrid energy storage system has been designed by combining interval observer and disturbance reconstruction technology. The hybrid energy storage system composed of a battery and a super capacitor has been used to improve the performance of load frequency control systems. Using the load frequency control model of the multi-area interconnected power system, the interval observers are designed for each area to get the information about interval bounds of the system state in each area online. Then, the load disturbance in each area is reconstructed online using the estimation information of system state, and a sliding mode controller based on interval disturbance reconstruction is designed for power consumption and storage of the hybrid energy storage system, so as to stabilize the power grid frequency. Simulation results have shown that the proposed control strategy can effectively suppress the frequency and tie-line power fluctuations caused by load disturbances, and ensure the reliability and stability of the power system.

Based on vehicle-to-grid technology, electric vehicles can be used as power sources in the case of power failure. With the aim to reduce voltage overshoot and improve the anti-disturbance ability of the vehicle-to-grid inverter, a high-performance voltage control strategy based on funnel control and finite-time disturbance observer is developed. First, the dynamic model of the inverter in dq-frame is established, and the lumped disturbance including the unmodeled part is considered. Next, a novel funnel variable is proposed to ensure that the voltage tracking error can be stabilized within the prescribed funnel boundary, and thus enhance the transient performance. Then, a novel finite-time disturbance observer is designed to estimate the lumped disturbance in the system such as load fluctuations, and improve the anti-disturbance ability of the controller. Moreover, the second-order sliding mode differentiator is introduced to estimate the derivative of the virtual control law and eliminate the explosion of complexity problem in the derivation process. Finally, the finite-time stability of the proposed voltage control strategy is analyzed via the Lyapunov theory. The effectiveness of the proposed control strategy is verified by two cases.

• The real-time control is carried out based on the SCN approximation model of PPD. • Prescribed performance and saturation problems are both considered in the controller. • The proposed control strategy has good performance in both LIM and BESS. To tackle the trajectory tracking problem and achieve high control accuracy in many actual nonlinear systems with unknown dynamics, a novel prescribed performance based model-free adaptive sliding mode constrained control (SMCC) strategy is studied which relies on the input/output data of plant rather than the specific model information via a pseudo partial derivative (PPD) parameter. Firstly, two approaches are introduced for PPD estimation, i.e., an observer-based adaptive algorithm, and an algorithm based on the stochastic configuration network approximating the controlled plant model, upon which the realtime control including PPD construction are carried out. Then, the prescribed performance is introduced in the model-free adaptive SMCC scheme as a prescribed range for the output tracking error. Meanwhile, an anti-windup compensation signal is employed to suppress the actuator saturation that commonly exists in many actual nonlinear systems. In addition, the stability analysis of the control system is presented to verify the rationality of the prescribed performance. Finally, simulations are carried out for both a linear induction motor and a battery energy storage system to demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In this article, the power distribution and tracking problems of the distributed energy storage system (ESS) are addressed by designing a cooperative adaptive terminal sliding mode (CATSM) controller based on a multi-agent network topology for each ESS. First, a novel adaptive power allocation algorithm (APAA) is proposed to achieve a consistent state-of-charge (SOC) for each battery in a distributed ESS. Then, considering the capacity degradation of the battery during long-term charging and discharging, we use real-time current and SOC to estimate the current capacity of the battery, which ensures the accuracy of the algorithm. Then, based on the proposed algorithm, the CATSM controllers are designed for each ESS via a multi-agent network topology for the distributed ESS, and the projection operator is used to guarantee the boundedness of adaptive estimation. Finally, the simulation results are provided to validate the feasibility and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Aiming at the problem of hybrid energy storage faults in large interconnected power systems, an integrated fault-tolerant control scheme is proposed to deal with actuator faults and external disturbances. Firstly, the hybrid energy storage system is introduced based on the traditional interconnected power system, and a new topological structure is given. Secondly, the state-space model of each area in the given topological structure is established considering the external disturbance and actuator fault of the power system. Then the sliding mode observer is designed and the fault-tolerant control of interconnected power systems is realized according to the estimated value and sliding mode technology. Finally, the simulation results on the model of four-area interconnected power system show that the proposed observer can realize fault estimation in a short time, and the fault-tolerant control effect is satisfied with nearly 30% reduction of regional control error compared with the traditional method.

In this paper, the influence of organic resin design on TFT characteristics is discussed. From the comparison of TFT characteristics, it can be concluded that the coverage of resin (full and partial) can solve the conductive trend of BCE a‐IGZO TFT. Combined with SiNxand SiO2in organic resin buffer layer process adjustment, Vth can be controlled at about 1.5V.

Abstract A new model-free adaptive sliding mode control method is proposed to solve some control issues in a class of discrete-time high-order nonlinear systems whose dynamics are unknown in this paper. In order to simplify the nonlinear system, a new concept called pseudo-partial derivative matrix (PPDM) is introduced to facilitate the nonlinear system by using a compact form dynamic linearization approach. Therefore, to estimate the PPDM, the identified adaptive observer is constructed using the input/output data from each subsystem of the higher order discrete time system. Taking into account the amplitude and rate constraints of real-world input signals, an anti-windup dynamic compensator is developed. Furthermore, the problems of complexity explosion and non-causality are solved by using discrete-time command filters while designing the controller. It has been shown that all the control variables in closed-loop systems are uniformly-ultimately bounded. An example of a linear induction motor taking into account the end effects is used to verify the effectiveness of the presented control strategy through simulations and experiments. [ABSTRACT FROM AUTHOR]

Abstract Robust model predictive control (RMPC) has gained much attention in the past two decades. For classic finite-horizon RMPC, a terminal constraint set together with a terminal cost function are usually employed for the purpose of closed-loop stability. However, computational burden and feasibility region may need to be carefully addressed when the prediction horizon length becomes large, especially for the cases with additive disturbances. In this paper, a novel RMPC approach with pseudo terminal designs is proposed. Specifically, a bank of pseudo terminal sets (PTSs) are designed given a predefined terminal constraint set. Besides, a pseudo terminal cost (PTC) term is considered for each PTS. With the proposed approach, a long-horizon RMPC problem can be divided into several short-horizon ones. It is shown that both the PTSs and the corresponding PTCs can be computed off-line recursively. In the online implementation, selecting a PTS is realized in a self-triggered way. Meanwhile, a time-varying cost function, which is always an upper bound of the infinite-horizon cost function, is optimized online. [ABSTRACT FROM AUTHOR]

Abstract This study focuses on the control of islanded photovoltaic (PV) microgrid and design of a controller for PV system. Because the system operates in islanded mode, the reference voltage and frequency of AC bus are provided by the energy storage system. We mainly designed the controller for PV system in this study, and the control objective is to control the DC bus voltage and output current of PV system. First, a mathematical model of the PV system was set up. In the design of PV system controller, command-filtered backstepping control method was used to construct the virtual controller, and the final controller was designed by using sliding mode control. Considering the uncertainty of circuit parameters in the mathematical model and the unmodeled part of PV system, we have integrated adaptive control in the controller to achieve the on-line identification of component parameters of PV system. Moreover, fuzzy control was used to approximate the unmodeled part of the system. In addition, the projection operator guarantees the boundedness of adaptive estimation. Finally, the control effect of designed controller was verified by MATLAB/Simulink software. By comparing with the control results of proportion-integral (PI) and other controllers, the advanced design of controller was verified. [ABSTRACT FROM AUTHOR]

Abstract In this paper, the problem of the speed control is considered for linear induction motor with the end effects, uncertain system parameters, and external load disturbance. Firstly, the proposed controller is based on backstepping method, and the adaptive laws are designed.The fuzzy logic modeling approach is used to deal with the unknown nonlinear functions and uncertain parameters. Secondly, a constrained command filter is employed to overcome the problem of differential expansion and controller saturation in the backstepping method, and a filter's compensating signal is used to mitigate the error caused by the constrained command filter. Thirdly, the projection operator introduced in the adaptive laws guarantees boundedness of the estimated functions and robustness of the designed controller in the presence of time-varying disturbances and uncertainties. Thus, the proposed control controller can ensure that all response signals in the closed-loop system are bounded. Finally, the effectiveness of the proposed controller is verified by simulation and comparison with command-filtered backstepping controller. [ABSTRACT FROM AUTHOR]

An increasing number of wireless intelligent equipment is applied to ICS networks. However, it is virtually impossible to use regular encryption methods and security patches to enhance the security level of legacy equipment in ICS networks due to weak computing and storage capabilities of the equipment. To address these concerns, a hybrid-augmented device fingerprinting approach is developed to enhance traditional intrusion detection mechanisms in the ICS network. Taking the advantage of the simplicity of the program process and stability of hardware configurations, we first measure inter-layer data response processing time, and then analyze network traffic to filter abnormal packets to achieve the intrusion classification and detection in ICS networks. The device fingerprinting- based intrusion classification and detection approach is evaluated using the data collected from a lab-level micro-grid, and forgery attacks and intrusions are launched against the proposed method to investigate its robustness and effectiveness.

In this paper, “IGZO deposition” and “IGZO Photo” are found to be the critical steps that occurs for ESD in Oxide TFTs. The mechanism of ESD has been studied, furthermore, several improvement methods has been proposed.

Abstract: In this paper, a decentralized asymptotic fault tolerant control system is proposed for near space vehicle (NSV) attitude dynamics. First, NSV reentry mode is described, and the actuator failure model is developed whose behavior is described by high-order dynamics. Next, the multi-model based fault diagnosis and identification (FDI) algorithm is proposed for high order actuator dynamics, which can accurately diagnose and identify the fault in short time. Based on sliding mode, command filter, and backstepping technique, using information of FDI, a constrained fault tolerant control (FTC) is designed for reentry NSV. Finally, simulation results are given to demonstrate the effectiveness and potential of the proposed FTC scheme. [Copyright &y& Elsevier]

In this article, a fault tolerant control approach is proposed for the formation control system of unmanned aerial vehicles with bounded external disturbance and unknown fault using both adaptive sliding mode control and H∞ control techniques. First, a linearized formation model of unmanned aerial vehicles is established under a straight and level formation flight condition. A reference model is introduced for the aim of the fault tolerant control problem. Then a sliding mode surface is designed for the deduced error dynamics, an virtual adaptive sliding mode controller and an adaptive fault estimation algorithm are proposed, which can drive the error dynamics onto the predefined sliding mode surface, and guarantee the property of asymptotical stability with a given disturbance attenuation level. On the basis of the normal proportional plus integral formation controller and the estimated fault information, a compensated control–based fault tolerant formation control scheme is proposed to ensure that the formation geometry is maintained in fault case. Finally, simulation results are given to show the effectiveness of the result obtained in this study.

In this paper, a fault-tolerant control scheme based on a second-order dynamic terminal sliding mode is proposed for a near-space vehicle attitude dynamical system in the presence of actuator faults, model parameter uncertainties and external disturbances. The principle of the proposed dynamic terminal sliding mode scheme is firstly introduced. Then, a near-space vehicle attitude faulty model with parameter uncertainty is established. Furthermore, two dynamic terminal sliding mode controllers are designed for the inner and outer loops. It is shown that the proposed algorithm can reduce chattering phenomenon and guarantee system stability and asymptotic state tracking. Finally, simulation results are provided to demonstrate the performance of the proposed fault-tolerant control scheme.

Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy modelBased on a Takagi-Sugeno (T-S) fuzzy model and an inverse system method, this paper deals with the problem of actuator fault estimation for a class of nonlinear dynamic systems. Two different estimation strategies are developed. Firstly, T-S fuzzy models are used to describe nonlinear dynamic systems with an actuator fault. Then, a robust sliding mode observer is designed based on a T-S fuzzy model, and an inverse system method is used to estimate the actuator fault. Next, the second fault estimation strategy is developed. Compared with some existing techniques, such as adaptive and sliding mode methods, the one presented in this paper is easier to be implemented in practice. Finally, two numerical examples are given to demonstrate the efficiency of the proposed techniques.

In this paper, the problem of two-dimensional wing flutter control with sensor and actuator failures is studied. Firstly, the aeroelastic equations of motion for two-dimensional wing with plunge and pitch are established; then the wing flutter model with failure modes is established considering the failure modes of sensor and actuator. Secondly, by designing a novel adaptive fault-tolerant controller, the wing flutter can be suppressed effectively and the external disturbance can be dealt with successfully. The stability of the system is proved by the constructed Lyapunov function. Finally, numerical simulation results show that the adaptive flutter fault-tolerant controller can effectively suppress wing flutter when sensors and actuators fail, and the controller has good robustness to the changes of external disturbances. [ABSTRACT FROM AUTHOR]

A fixed-time anti-disturbance constraint fuzzy synchronization control method is proposed, for the sake of solving the problem of fast recovery of synchronization between in-wheel permanent magnet synchronous motors (PMSMs) in four-wheel-independent drive electric vehicles. The system model of in-wheel PMSM is presented in the beginning, and fuzzy logic systems are used for approximating the uncertainty parts of the PMSM model. Based on the PMSM model, a fixed-time disturbance-observer is designed to account for fast estimation of fluctuating load torque. Then, the neighborhood synchronization error is constructed based on a directed-graph, and a performance function is designed to guarantee the neighborhood synchronization error evolves strictly within the prescribed bound. Besides, the fixed-time bound of all signals is proved. Finally, the hardware-in-the-loop platform is built, and the electronic differential and the nonlinear vehicle model are employed to validate the advanced performance of the design control method. [ABSTRACT FROM AUTHOR]

A permanent magnet linear synchronous motor (PMLSM) control strategy based on improved neural networks is proposed for the problem of inaccurate decoupling and poor adaptive performance of the traditional proportional–integral (PI) control method. In this paper, incremental broad learning (IBL) is selected as the neural networks training model. IBL is improved on the basis of broad learning, which can dynamically change the number of nodes while reducing the model training time. The IBL controller design process does not require a mathematical model of the control system. It can be designed based on data obtained from existing systems or factories without the necessary expertise, and can better enhance the nonlinearity of the controller. First, the IBL controller is trained and built by collecting relevant data based on the entire dynamic model of PMLSM. Then, test datasets and error evaluation metrics are used to determine the optimal hyperparameters of the IBL model. Finally, simulations and experiments in dSPACE show that the method proposed in this paper outperforms the conventional vector control method in terms of robustness and adaptivity. [ABSTRACT FROM AUTHOR]

The article deals with the problem of the yaw control of the unmanned aerial vehicle helicopter which is non-affine nonlinear by use of a novel projection-based adaptive fuzzy control approach. First, principle model and control design model of the yaw channel of the unmanned aerial vehicle helicopter are described. Then, a dynamic approximation technique is introduced to approach the non-affine model of the unmanned aerial vehicle helicopter into an affine model with variable parameters, which is applied to facilitate the design of nonlinear control scheme. Next, in the proposed controller, fuzzy controller is designed to deal with the unknown uncertainties and disturbances. Meanwhile, the projection-based adaptive law applied in fuzzy controller bounds the parameter estimation function and can also guarantee the robustness of the designed control scheme against uncertain disturbances. Moreover, the convergence and stability of the designed controller are proved by Lyapunov stability theory. Finally, the simulation results of the yaw channel of an unmanned aerial vehicle helicopter are performed to illustrate that the designed controller has good tracking performance, stability, and robustness under the condition of the time-vary uncertain disturbances.

In this thesis, an innovative model-free adaptive control strategy based on a multi-observer technique that takes advantage of input/output measurement data is proposed for the aeroelastic system of the two degree of freedom pitch-plunge wing, and this unknown complicated nonlinear system is a general multi-input multi-output plant with input constraints. In this algorithm, the multi-observer technique is applied to estimate the value of the pseudopartial derivative parameter matrix in the approach of the compact form dynamic linearization designed to linearize the model of the two-dimensional wing-flap system with input constraints. At the same time, this model-free adaptive control method consists of the approximate internal model and the optimal controller. Moreover, this control scheme is based on the linear matrix inequalities, which is a kind of real-time computation. In the design process for controlling this two-dimensional wing-flap system in the condition that the control inputs are subjected to amplitude and change rate limits, the problem of the dynamic control is transformed into the optimization problem, which can minimize the performance index. Finally, simulation results for the two-dimensional wing-flap system with input constraints can demonstrate the availability and potential of the presented multi-observer-based model-free optimal control strategy for unknown nonlinear multi-input multi-output system with input saturation.

This paper proposed a command-filtered backstepping controller to improve the dynamic performance of back-to-back voltage-source-converter high voltage direct current (BTB VSC-HVDC). First, the principle and model of BTB VSC-HVDC in abc and d-q frame are described. Then, backstepping method is applied to design a controller to maintain the voltage balance and realize coordinated control of active and reactive power. Meanwhile, command filter is introduced to deal with the problem of input saturation and explosion of complexity in conventional backstepping, and a filter compensation signal is designed to diminish the adverse effects caused by the command filter. Next, the stability and convergence of the whole system are proved via the Lyapunov theorem of asymptotic stability. Finally, simulation results are given to demonstrate that proposed controller has a better dynamic performance and stronger robustness compared to the traditional PID algorithm, which also proves the effectiveness and possibility of the designed controller.

In this article, a novel data-driven constrained control scheme is proposed for automatic parking systems. The design of the proposed scheme only depends on the steering angle and the orientation angle of the car, and it does not involve any model information of the car. Therefore, the proposed scheme-based automatic parking system is applicable to different kinds of cars. In order to further reduce the desired trajectory coordinate tracking errors, a coordinates compensation algorithm is also proposed. In the design procedure of the controller, a novel dynamic anti-windup compensator is used to deal with the change magnitude and rate saturations of automatic parking control input. It is theoretically proven that all the signals in the closed-loop system are uniformly ultimately bounded based on Lyapunov stability analysis method. Finally, a simulation comparison among the proposed scheme with coordinates compensation and Proportion Integration Differentiation (PID) control algorithm is given. It is shown that the proposed scheme with coordinates compensation has smaller tracking errors and more rapid responses than PID scheme.

This paper investigates the adaptive attitude tracking problem for the rigid satellite involving output constraint, input saturation, input time delay, and external disturbance by integrating barrier Lyapunov function (BLF) and prescribed performance control (PPC). In contrast to the existing approaches, the input delay is addressed by Pade approximation, and the actual control input concerning saturation is obtained by utilizing an auxiliary variable that simplifies the controller design with respect to mean value methods or Nussbaum function-based strategies. Due to the implementation of the BLF control, together with an interval notion-based PPC strategy, not only the system output but also the transformed error produced by PPC are constrained. An adaptive fuzzy controller is then constructed and the predesigned constraints for system output and the transformed error will not be violated. In addition, a smooth switch term is imported into the controller such that the finite time convergence for all error variables is guaranteed for a certain case while the singularity problem is avoided. Finally, simulations are provided to show the effectiveness and potential of the proposed new design techniques. [ABSTRACT FROM AUTHOR]

This paper studies the control of a medium-voltage DC (MVDC) traction power supply system for rail transit (RT). In order to optimize the ability of DC voltage fluctuation and frequency regulation of rail trains, a fuzzy adaptive cooperative secondary control strategy based on improved virtual synchronous machine (VSM) is proposed. Firstly, the improved VSM control strategy is adopted in the traction substations (TSSs), which makes the RT trains have the external characteristics of synchronous generator and have certain inertia and damping support capacity, so as to improve the ability of the RT traction system to cope with traction network transient changes. Secondly, the virtual inertia and virtual damping can be dynamically adjusted by the system frequency deviating from the nominal steady-state frequency, and the dynamic fuzzy adjustment can be carried out by the fuzzy logic system to slow down the frequency fluctuation. Then, due to the different power supply distances and parameter settings between multiple TSSs, cooperative control is used to coordinate local TSS perceptions of information between adjacent TSS to achieve consistency of frequency response of multiple TSSs under different parameters. Besides, a time-varying switching topology handoff method is considered to select the optimal communication topology between adjacent base stations. Finally, simulation results verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Highlights • The work studies finite-time stabilization for a class of non-affine nonlinear systems with unknown states and disturbance. The estimated states obtained via ESO are applied to system transformation and the design of FTDO and fast nonsingular terminal sliding mode controller. To our best knowledge, there are few results about finite-time output feedback control for uncertain non-affine nonlinear system. • The hyperbolic tangent function based ESO combines the characteristics of higher order observer and traditional ESO, and the convergence time and domain can be tuned via the parameter selection. • Based on hyperbolic tangent function based ESO and FTDO, this paper proposes a terminal sliding mode controller based on exponential function sliding mode, which not only enhances the robustness but also reduces chattering. Abstract This paper studies the problem of observer based fast nonsingular terminal sliding mode control schemes for nonlinear non-affine systems with actuator faults, unknown states, and external disturbances. A hyperbolic tangent function based extended state observer is considered to estimate unknown states, which enhances robustness by estimating external disturbance. Then, Taylor series expansion is employed for the non-affine nonlinear system with actuator faults, which transforms it to an affine form system to simplify disturbance observer and controller design. A finite time disturbance observer is designed to address unknown compound disturbances, which includes external disturbances and system uncertainties. A fast nonsingular terminal sliding mode with exponential function sliding mode is proposed to address output tracking. Simulation results show the proposed scheme is effective. [ABSTRACT FROM AUTHOR]

In this paper, the problem of active fault tolerant control (FTC) is studied for a class of flexible spacecraft attitude systems with Lipschitz nonlinearity and sensor fault. Firstly, a functional observer is designed for the attitude systems of flexible spacecraft in order to detect the time of unknown sensor fault occurred. Next, the sensor fault estimation is performed by filtering the output estimation error, as usually done in the residual generation framework. Then, a dynamic output feedback-based FTC approach is proposed to the flexible spacecraft in sensor faulty case, it not only attenuates flexible appendage disturbance with a given level γ , but also tolerates the effect of unknown sensor fault. Finally, the effectiveness of the proposed FTC method is demonstrated in the attitude systems of flexible spacecraft subject to a time-varying sensor fault. [ABSTRACT FROM AUTHOR]