Tolerant Control Research Articles

A comprehensive investigation of brushless direct current (bldc) motors: current state, advanced control strategies, and utilization systems

In the field of dynamic applications, specifically within automotive, pumping, and rolling sectors, there exists a noteworthy preference for the use of Brushless Direct Current (BLDC) motors. Projections show that, by the year 2030, BLDC motors are poised to supersede classic induction motors as the dominating force in industrial power transmission. This transformation, however, is accompanied by crucial issues and unresolved research challenges in the environment of BLDC motors.The core concern revolves around the dependability and endurance of BLDC motors. These motors presently encounter obstacles in achieving advanced fault tolerance, reduced electromagnetic interference, lowered acoustic noise, as well as mitigated flux and torque fluctuations. The path of closed-loop vector control emerges as a possible technique to address these challenges.In recent literature studies spanning the previous five years, a striking scarcity of exploration in the domain of BLDC motor controllers and design becomes clear. Furthermore, key areas such as the comparative study of existing vector control schemes, the increase of fault tolerance control, the attenuation of electromagnetic interference inside BLDC motor controllers, and other pivotal elements remain undiscovered. These research lacunae serve as a motivator for the undertaking of an intensive investigation to face the fundamental issues related with BLDC motors. BLDC motors have quickly become the motor of choice for electric vehicle (EV) applications due to the fact that they are reliable, simple, and energy efficient.This detailed survey goes deep into numerous sophisticated control strategies for BLDC motors. These encompass fault tolerance control, electromagnetic interference reduction, field orientation control (FOC), direct torque control (DTC), current shaping, input voltage control, intelligent control, drive-inverter topology, and the underlying operational principles aimed at the minimization of torque irregularities. Additionally, the study goes through the historical narrative of BLDC motors, the categorization of BLDC motor kinds, their structural complexity, mathematical modeling, and the standards that govern BLDC motor uses in varied industries.

Dynamic output feedback based fault tolerant control for continuous-time switched affine systems via reduced-order observer

In this study, the issue on dynamic output feedback fault-tolerant controller design is addressed for a class of continuous-time switched affine systems in the presence of actuator faults. The existence of affine terms gives rise to the lack of a common equilibrium point and further makes it more difficult to propose the desired output-feedback-based fault-tolerant control scheme. Firstly, the actuator fault estimation is achieved through a reduced-order observer design approach. Then, a kind of dynamic output feedback controller is constructed to perform the fault tolerance goal by utilizing fault estimation information. Moreover, the mode-dependent average dwell time switching constraint is borrowed to avoid the chattering owing to the high-frequency switching. The sufficient conditions with less conservative are derived to guarantee the practical exponential stability of closed-loop system with a prescribed L∞ gain. Finally, both the effectiveness and validity of the designed fault-tolerant control strategy are illustrated via a case study of a buck-boost DC-DC converter.

Integral sliding mode-based event-triggered optimal fault tolerant tracking control of continuous-time nonlinear systems

In this paper, the integral sliding mode-based event-triggered optimal fault tolerant tracking control of continuous-time nonlinear systems is investigated via adaptive dynamic programming. The developed control scheme consists of two parts, i.e., integral sliding mode control and event-triggered optimal tracking control. For the first part, an integral sliding mode controller is designed to eliminate the affect of actuator fault and the dynamics of nominal nonlinear systems is obtained. For the second part, a novel quadratic cost function with respect to the tracking error and its dynamics is developed such that the feedforward control law or the discount factor is not required, which reduces the complexity of the control method and guarantees the tracking performance. Moreover, a critic-only structure is established to obtain the solution of tracking Hamilton–Jacobi–Bellman equation. It should be noted that the optimal tracking control law is updated only at triggering moments in order to preserve computing and communication resources. Finally, the effectiveness of the present approach is demonstrated through simulation examples of a robotic arm system and a Van der Pol circuit system.

Tolerance analysis of slat gear rotary actuator in civil aircraft

Abstract The slat gear rotary actuator of civil aircraft needs to meet the requirements of small space and large transmission ratio. The planetary gear system based on triple teeth is a common actuator design, and the design structure is complex, so its tolerance control is also strict. In order to meet the design requirements of its internal structure, this paper presents a deviation analysis method for the internal structure design of a typical civil aircraft slat gear rotary actuator. The results of preliminary tolerance distribution and improved tolerance distribution are analyzed using the Jacobi-based assembly deviation model. By comparing the standard deviation of the analysis results, the validity of this deviation analysis method is verified, which proves that this method can be used to analyze the internal structure deviation of the rotary actuator of slat gear in civil aircraft.

Alternative splicing drives the functional diversification of a bHLH transcription factor in the control of growth and drought tolerance in rice

Alternative splicing drives the functional diversification of a bHLH transcription factor in the control of growth and drought tolerance in rice

Online Full Range Copper Loss Minimization for Single-Phase Short-Circuit Fault Tolerant Control in Five-Phase PMSM

Online Full Range Copper Loss Minimization for Single-Phase Short-Circuit Fault Tolerant Control in Five-Phase PMSM

Fault tolerant control of permanent magnet synchronous motor based on hybrid control strategies DTC-SVM with second order sliding mode control using multi-variable filter

This paper describes direct torque control (DTC) of a permanent magnet synchronous machine (PMSM) powered by a two-level voltage inverter whose switching of switches is based on the Space Vector Modulation. To overcome the robustness of the control to the presence of a fault, we included an improvement of the direct torque control with Space vector modulation (DTC-SVM) by the use of the filters for the flux and the torque and compared to the direct torque control of the DTC-SVM, the PI controllers are replaced with sliding mode blocks, This control method allows giving a new structure DTC -SVM with sliding mode control. The analysis of the results shows good performances for the speed and a considerable reduction of the fluctuations at the level of the torque and the flux.

Adaptive Takagi–Sugeno (T–S) fuzzy observer based fault tolerant control for DC–DC converters with robustness against uncertainties

AbstractThis paper proposes a Takagi–Sugeno fuzzy system model based fault tolerant control scheme for DC–DC converters, which is robust against parameter uncertainties and achieves the output voltage of an ideal converter. The control involves estimating the duty cycle change in the form of a fault parameter required to track the output voltage, in the presence of several uncertain conditions including converter losses, variation in input voltage, and unknown and changing output load. An adaptive law is designed to estimate the fault parameter that guarantees state and parameter error convergence. The adaptive law is derived using the Lyapunov stability theorem and the required parameters are evaluated by solving a linear matrix inequalities optimization problem. The load resistance is estimated in parallel by using a Kalman filter and fed to the fault parameter estimation scheme. Furthermore, a fast and robust method to detect short and open circuit switch faults is also presented. The proposed technique offers a simple, yet effective method to regulate the output voltage under several faulty and uncertain conditions. The proposed technique is tested on a DC–DC boost converter simulation model and the demonstrated MATLAB/Simulink results show the effectiveness of the proposed algorithm.

Data-based deep reinforcement learning and active FTC for unmanned surface vehicles

In this study, we investigate the active fault tolerant control(AFTC) of unmanned surface vehicles (USV) under actuator faults and environmental disturbances using deep reinforcement learning(DRL). We realize the perception of the environment and continuous control through end-to-end learning based on neural networks(NN). The contents of AFTC include 1) actuator fault estimation(FE) based on long short-term memory(LSTM) and 2) a fault tolerant control(FTC) framework based on a deep deterministic policy gradient to enable the USV to learn autonomous decision making through training. We introduce mixed noise based on Gaussian noise and Ornstein–Uhlenbeck noise into the training, which increases the exploration space and improves the generalization ability of the USV. An experiential replay method based on quantum computing is designed to distinguish the importance of samples through preparation and depreciation operations, enabling a guided learning process. Finally, we verify the universality and effectiveness of the AFTC framework by tracking straight and sinusoidal trajectories.

Open-fault diagnosis and tolerant control of a dual inverter fed open-end winding interior permanent magnet synchronous motor

Open-fault diagnosis and tolerant control of a dual inverter fed open-end winding interior permanent magnet synchronous motor

Integral reinforcement learning–based adaptive fuzzy fault tolerant control of hypersonic flight vehicle

The fault tolerant control (FTC) of hypersonic flight vehicle (HFV) with actuator fault is proposed in this paper. The fault model considered in this paper is a general model which HFV may encounter in practice. For designing the FTC, the nonlinear model of HFV is represented by T-S fuzzy models, and policy iteration (PI) strategy is utilized to solve the design problem of T-S controller for the built T-S model of HFV without actuator fault. Then, based on the normal T-S controller, an adaptive fuzzy FTC controller is proposed, in which the feedback gain matrices can improve themselves according to the special fault. The stability of the proposed adaptive fuzzy FTC is proved by Lyapunov theory, and an integral reinforcement learning (IRL)–based solving algorithm is proposed. Simulations on three different kinds of actuator faults are proposed, and the simulation results show that, under three different faults, the designed adaptive FTC can ensure the reliable flight of HFV.

Disturbance observer–based finite‐time fault tolerant control of quadrotor unmanned aerial vehicles with command filtered and event‐triggered techniques

AbstractThis article primarily focuses on the finite‐time fault‐tolerant tracking control problem of quadrotor unmanned aerial vehicle (UAV) systems. Our main innovation points are: (1) A simple cubic form of Lyapunov function is applied to the design of the position ring controller of the quadrotor UAV; (2) The command filtering technology effectively solves the challenge of derivation of complex coupling matrixs in the controller design process; (3) An improved disturbance observer and a variable threshold event‐triggered mechanism are applied in the Quadrotor UAV system. In summary, the overall approach combines the backstepping method and finite‐time Lyapunov stability to prove the finite‐time stability of all the signals in the system. Finally, the effectiveness and rationality of the algorithm are verified through simulation experiments and its application on an actual simulation platform.

A Solanum lycopersicum polyamine oxidase contributes to the control of plant growth, xylem differentiation, and drought stress tolerance.

Polyamines are involved in several plant physiological processes. In Arabidopsis thaliana, five FAD-dependent polyamine oxidases (AtPAO1 to AtPAO5) contribute to polyamine homeostasis. AtPAO5 catalyzes the back-conversion of thermospermine (T-Spm) to spermidine and plays a role in plant development, xylem differentiation, and abiotic stress tolerance. In the present study, to verify whether T-Spm metabolism can be exploited as a new route to improve stress tolerance in crops and to investigate the underlying mechanisms, tomato (Solanum lycopersicum) AtPAO5 homologs were identified (SlPAO2, SlPAO3, and SlPAO4) and CRISPR/Cas9-mediated loss-of-function slpao3 mutants were obtained. Morphological, molecular, and physiological analyses showed that slpao3 mutants display increased T-Spm levels and exhibit changes in growth parameters, number and size of xylem elements, and expression levels of auxin- and gibberellin-related genes compared to wild-type plants. The slpao3 mutants are also characterized by improved tolerance to drought stress, which can be attributed to a diminished xylem hydraulic conductivity that limits water loss, as well as to a reduced vulnerability to embolism. Altogether, this study evidences conservation, though with some significant variations, of the T-Spm-mediated regulatory mechanisms controlling plant growth and differentiation across different plant species and highlights the T-Spm role in improving stress tolerance while not constraining growth.

Sliding mode observer-based fault diagnosis and continuous control set fault tolerant control for PMSM with demagnetization fault

A fault detection, estimation and fault tolerant control scheme for demagnetization fault in the permanent magnet synchronous motor systems is proposed in this paper. When demagnetization fault occurs, the system will deviate from the normal state severely. To facilitate the calculation, the demagnetization fault is converted to the dq coordinate system for processing and the resistance change is modeled as the system uncertainty, and the effect of the uncertainty on the system is analyzed. Then a fault detection observer is designed to detect the fault occurrence time, and a sliding mode observer based fault estimation algorithm is designed to estimate the fault and disturbance information. The observer parameters are determined by linear matrix inequality. When the fault information is obtained, a continuous control set fault tolerant control scheme is presented to minimize the impact of fault as far as possible. Finally, experimental results provide evidence of the feasibility of the suggested algorithm.

Adaptive sliding mode and RBF neural network based fault tolerant attitude control for spacecraft with unknown uncertainties and disturbances

Taking the external disturbance, model uncertainty, actuator failure, and actuator saturation into consideration, this paper investigates the nonlinear fault-tolerant attitude control problem for the spacecraft. First, to deal with the disturbance and uncertainty with unknown boundaries, an adaptive sliding mode control method is proposed to stabilize the state variables of the spacecraft attitude control system. Then the actuator failure and saturation are further considered, and the second spacecraft fault-tolerant attitude controller is derived based on adaptive sliding mode control and radial basis function (RBF) neural networks. The adaptive control gains reduction technique is applied in the design process, which can weaken the chattering phenomenon of the controller to some extent, and the stability of the attitude control system is analyzed through Lyapunov theory. In the proposed controller, model information and external disturbance are not required and only the system states are needed. Furthermore, the boundaries of the model uncertainty, external disturbance, actuator fault and saturation are assumed to be existing but unknown by the proposed controllers. These features make the proposed attitude controllers need few modeling information of the spacecraft, or maintain strong robustness even if the model or external environment occurs significant changes. Finally, numerical simulations demonstrate the great performance of the proposed fault-tolerant attitude control method.

Integral terminal sliding mode fault tolerant control of quadcopter UAV systems

The article presents an active fault-tolerant control scheme with an integral terminal sliding mode controller for the UAV systems. This scheme effectively addresses saturation issues, disturbances, and sensor and actuator faults. Initially, the quadcopter UAV's model is represented in state space form. Subsequently, an augmented system incorporating auxiliary states from sensor faults is developed. An adaptive sliding mode observer is proposed for estimating the actuator and sensor faults. The integral terminal sliding mode fault-tolerant control, designed for altitude and attitude regulation, relies on fault estimation data. In contrast, a cascade proportional-integral-derivative (PID) controller is employed for position control. Simulation results demonstrate the superiority of the proposed method over existing control algorithms.

Multiple model fault diagnosis and fault tolerant control for the launch vehicle’s attitude control system

Abstract For the launch vehicle attitude control problem, traditional methods can seldom accurately identify the fault types, making the control method lack of pertinence, which largely affects the effect of attitude control. This paper proposes an active fault tolerant control strategy, which mainly includes fault diagnosis and fault tolerant control. In the fault diagnosis part, a small deviation attitude dynamics model of the launch vehicle is established, Kalman filters with different structures are designed to detect and isolate faults through residual changes, and the fault quantity of the actuator is further estimated. In the fault tolerant control part, the following control scheme is adopted according to the above diagnostic information: when the sensor fault is detected, the sensor measurement data is reconstructed; when the actuator fault is identified, the control allocation matrix is reconstructed. Simulation results show that the proposed method can effectively diagnose sensor fault and actuator faults, and significantly improve attitude tracking accuracy and control adjustment time.

Asymptotic voltage restoration in islanded microgrids via an adaptive asynchronous event-triggered finite-time fault-tolerant control

As the actuators of distributed generators involved in Microgrids (MGs) may experience different faults, it is highly recommended to design an appropriate secondary Fault Tolerant (FT) controller to provide resilience and robustness with respect to these malicious events. Meanwhile, the reduction of communication network workload from controller-to-actuator may be helpful to mitigate actuators stress. By virtue of the above, this article aims at introducing a novel distributed adaptive FT-Event-Triggered Control (FT-ETC) scheme for secondary voltage regulation control in AC islanded MG able to compensate faulty actuators effects while reducing the waste of communication network resources. The proposed control scheme is derived with the aid of the backstepping method and the ETC theory, whose combination ensures resilience with respect to possible faulty signals, while no knowledge of global information is required. Adaptive mechanisms are derived by exploiting Lyapunov theory, while Zeno-freeness property is proven by contradiction. Compared with the existing state-of-the-art on FT-ETC in islanded MG, here the main novelty relies in achieving the asymptotic rather than the practical stability of the voltage tracking errors despite an unhealthy environment, while the remaining adaptive signals involved in the closed-loop systems are bounded in finite-time. Finally, an extensive simulation analysis, also involving real-time Hardware In-the-Loop (HIL) experiments, confirms the theoretical derivation.

Concurrent Learning Robust Adaptive Fault Tolerant Boundary Regulation of Hyperbolic Distributed Parameter Systems.

This article develops a robust adaptive boundary output regulation approach for a class of complex anticollocated hyperbolic partial differential equations subjected to multiplicative unknown faults in both the boundary sensor and actuator. The regulator design is based on the internal model principle, which amounts to stabilize a coupled cascade system, which consists of a finite-dimensional internal model driven by a hyperbolic distributed parameter system (DPS). To this end, a systematic sliding mode equipped with a backstepping approach is developed such that the robust state feedback control can be realized. Moreover, since the available information is a faulty boundary measurement at the right side point, state estimation is required. However, due to the presence of boundary unknown faults, we need to solve an issue of joint fault-state estimation. Restrictive persistent excitation conditions are usually required to guarantee the exact estimation of faults but are unrealistic in practice. To this end, a novel concurrent learning (CL) adaptive observer is proposed so that exponential convergence is obtained. It is the first time that the spirit of CL is introduced to the field of DPSs. Consequently, the observer-based adaptive boundary fault tolerant control scheme is developed, and rigorous theoretical analysis is given such that the exponential output regulation can be achieved. Finally, the effectiveness of the proposed methodology is demonstrated via comparative simulations.

A Simple Online Fault Location and Tolerant Control Strategy for Power Electronic Transformers With a Single IGBT Open-Circuit Fault

A Simple Online Fault Location and Tolerant Control Strategy for Power Electronic Transformers With a Single IGBT Open-Circuit Fault