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.

Guaranteed Cost Active Fault-tolerant Control of Networked Control System with Packet Dropout and Transmission Delay

The problem of guaranteed cost active fault-tolerant controller （AFTC） design for networked control systems （NCSs） with both packet dropout and transmission delay is studied in this paper. Considering the packet dropout and transmission delay, a piecewise constant controller is adopted. With a guaranteed cost function, optimal controllers whose number is equal to the number of actuators are designed, and the design process is formulated as a convex optimal problem that can be solved by existing software. The control strategy is proposed as follows： when actuator failures appear, the fault detection and isolation unit sends out the information to the controller choosing strategy, and then the optimal stabilizing controller with the smallest guaranteed cost value is chosen. Two illustrative examples are given to demonstrate the effectiveness of the proposed approach. By comparing with the existing methods, it can be seen that our method has a better performance.

Novel active fault-tolerant control scheme and its application to a double inverted pendulum system

On the basis of the gain-scheduled H∞ design strategy, a novel active fault-tolerant control scheme is proposed. Under the assumption that the effects of faults on the state-space matrices of systems can be of affine parameter dependence, a reconfigurable robust H∞ linear parameter varying controller is developed. The designed controller is a function of the fault effect factors that can be derived online by using a well-trained neural network. To demonstrate the effectiveness of the proposed method, a double inverted pendulum system, with a fault in the motor tachometer loop, is considered.

Backstepping-based active fault-tolerant control for a class of uncertain SISO nonlinear systems

Active fault-tolerant control is investigated for a class of uncertain SISO nonlinear flight control systems based on the adaptive observer, feedback linearization and backstepping theory.Firstly an adaptive observer is constructed to estimate the fault in the faulty system.A new fault updating law is presented to simplify the assumption conditions of the adaptive observer.The asymptotical stability of the observer and the uniform ultimate boundedness of the fault estimation error are guaranteed by Lyapunov theorem.Then a backstepping-based active fault-tolerant controller is designed for the faulty system.The asymptotical stability of the closed-loop system and uniform ultimate boundedness of the tracking error are proved based on Lyapunov theorem.The effectiveness of the proposed scheme is demonstrated through the numerical simulation of a flight control system.

Active fault-tolerant control scheme of aerial manipulators with actuator faults

In this paper,an active fault-tolerant control(FTC)strategy of aerial manipulators based on non-singular terminal sliding mode(NTSM)and extended state observer(ESO)is proposed.Firstly,back-stepping technology is adopted as the control framework to ensure the global asymptotic stability of the closed-loop system.Next,the NTSM with estimated parameters of actuator faults is used as main robustness controller to deal with actuator faults.Then,the ESO is utilized to estimate and compensate the complex coupling effects and external disturbances.The Lyapunov stability theory can guarantee the asymptotic stability of aerial manipulators system with actuator faults and external disturbances.The proposed FTC scheme considers both actuator fault and modelling errors,combined with the adaptive law of actuator fault,which has better performance than traditional FTC scheme,such as NTSM.Finally,several comparative simulations are conducted to illustrate the effectiveness of the proposed FTC scheme.

Robust and Active Fault-tolerant Control for a Class of Nonlinear Uncertain Systems

A novel integrated design strategy for robust fault diagnosis and fault-tolerant control （FTC） of a class of nonlinear uncertain systems is proposed. The uncertainties considered in this paper are more general than those in other existing works, and faults are described in a new formulation. It is proven that the states of a closed-loop system converge asymptotically to zero even if there are uncertainties and faults in a system. Simulation results on a simple pendulum are presented for illustration.

Active fault-tolerant control strategy of large civil aircraft under elevator failures

Aircraft longitudinal control is the would lead to catastrophic accident of aircraft. most important actuation system and its failures This paper proposes an active fault-tolerant control （AFTC） strategy for civil aircraft with different numbers of faulty elevators. In order to improve the fault-tolerant flight control system performance and effective utilization of the control surface, trim- mable horizontal stabilizer （THS） is considered to generate the extra pitch moment. A suitable switching mechanism with performance improvement coefficient is proposed to determine when it is worthwhile to utilize THS. Furthermore, AFTC strategy is detailed by using model following technique and the proposed THS switching mechanism. The basic fault-tolerant controller is designed to guarantee longitudinal control system stability and acceptable performance degradation under partial elevators failure. The proposed AFTC is applied to Boeing 747-200 numerical model and simulation results validate the effectiveness of the proposed AFTC approach.

Fast Active Fault-Tolerant Control for a Quadrotor UAV Against Multiple Actuator Faults

This paper proposes a fast adaptive fault estimator-based active fault-tolerant control strategy for a quadrotor UAV against multiple actuator faults.A fast adaptive fault estimation algorithm is designed to estimate the unknown actuator fault parameters.By synthesizing the fast adaptive fault estimator with the embedded control law,an active fault-tolerant control mechanism is established to compensate the adverse e®ects of multiple actuator faults.The e®ectiveness of the proposed strategy is validated through both numerical simulations and experimental tests.

Active fault-tolerant control of rotation angle sensor in steer-by-wire system based on multi-objective constraint fault estimator

Purpose–Steer-by-wire(SBW)system mainly relies on sensors,controllers and motors to replace the traditionally mechanical transmission mechanism to realize steering functions.However,the sensors in the SBW system are particularly vulnerable to external influences,which can cause systemic faults,leading to poor steering performance and even system instability.Therefore,this paper aims to adopt a fault-tolerant control method to solve the safety problem of the SBW system caused by sensors failure.Design/methodology/approach–This paper proposes an active fault-tolerant control framework to deal with sensors failure in the SBW system by hierarchically introducing fault observer,fault estimator,fault reconstructor.Firstly,the fault observer is used to obtain the observation output of the SBW system and then obtain the residual between the observation output and the SBW system output.And then judge whether the SBW system fails according to the residual.Secondly,dependent on the residual obtained by the fault observer,a fault estimator is designed using bounded real lemma and regional pole configuration to estimate the amplitude and time-varying characteristics of the faulty sensor.Eventually,a fault reconstructor is designed based on the estimation value of sensors fault obtained by the fault estimator and SBW system output to tolerate the faulty sensor.Findings–The numerical analysis shows that the fault observer can be rapidly activated to detect the fault while the sensors fault occurs.Moreover,the estimation accuracy of the fault estimator can reach to 98%,and the fault reconstructor can make the faulty SBW system to retain the steering characteristics,comparing to those of the fault-free SBW system.In addition,it was verified for the feasibility and effectiveness of the proposed control framework.Research limitations/implications–As the SBW fault diagnosis and fault-tolerant control in this paper only carry out numerical simulation research on sensors faults in matrix and laboratory/Simulink,the subsequent hardware in the loop test is needed for further verification.Originality/value–Aiming at the SBW system with parameter perturbation and sensors failure,this paper proposes an active fault-tolerant control framework,which integrates fault observer,fault estimator and fault reconstructor so that the steering performance of SBW system with sensors faults is basically consistent with that of the fault-free SBW system.

Passive activity enhances residual control ability in patients with complete spinal cord injury

Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.

A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.

Flexible linear clock-based distributed self-triggered active power-sharing secondary control of AC microgrids

Traditional active power sharing in microgrids,achieved by the distributed average consensus,requires each controller to continuously trigger and communicate with each other,which is a wasteful use of the limited computation and communication resources of the secondary controller.To enhance the efficiency of secondary control,we developed a novel distributed self-triggered active power-sharing control strategy by introducing the signum function and a flexible linear clock.Unlike continuous communication–based controllers,the proposed self-triggered distributed controller prompts distributed generators to perform control actions and share information with their neighbors only at specific time instants monitored by the linear clock.Therefore,this approach results in a significant reduction in both the computation and communication requirements.Moreover,this design naturally avoids Zeno behavior.Furthermore,a modified triggering condition was established to achieve further reductions in computation and communication.The simulation results confirmed that the proposed control scheme achieves distributed active power sharing with very few controller triggers,thereby substantially enhancing the efficacy of secondary control in MGs.

Learning active flow control strategies of a swept wing by intelligent wind tunnel

An intelligent wind tunnel using an active learning approach automates flow control experiments to discover the aerodynamic impact of sweeping jet on a swept wing. A Gaussian process regression model is established to study the jet actuator's performance at various attack and flap deflection angles. By selectively focusing on the most informative experiments, the proposed framework was able to predict 3721 wing conditions from just 55experiments, significantly reducing the number of experiments required and leading to faster and cost-effective predictions. The results show that the angle of attack and flap deflection angle are coupled to affect the effectiveness of the sweeping jet. Meanwhile, increasing the jet momentum coefficient can contribute to lift enhancement;a momentum coefficient of 3% can increase the lift coefficient by at most 0.28. Additionally, the improvement effects are more pronounced when actuators are placed closer to the wing root.

Analysis of a uniform passive fault-tolerant control method for multicopters

For the multicopter with more than four rotors,the rotor fault information is unobservable,which limits the applica-tion of active fault-tolerant on multicopters.This paper applies an existing fault-tolerant control method for quadcopter to multi-copter with more than four rotors.Without relying on rotor fault information,this method is able to stabilize the multicopter with multiple rotor failures,which is validated on the hexacopter and octocopter using the hardware-in-the-loop simulations.Addi-tionally,the hardware-in-the-loop simulations demonstrate that a more significant tilt angle in flight will inhibit the maximum tolera-ble number of rotor failures of a multicopter.The more signifi-cant aerodynamic drag moment will make it difficult for the mul-ticopter to regain altitude control after rotor failure.

A Modified Iterative Learning Control Approach for the Active Suppression of Rotor Vibration Induced by Coupled Unbalance and Misalignment

This paper proposes a modified iterative learning control(MILC)periodical feedback-feedforward algorithm to reduce the vibration of a rotor caused by coupled unbalance and parallel misalignment.The control of the vibration of the rotor is provided by an active magnetic actuator(AMA).The iterative gain of the MILC algorithm here presented has a self-adjustment based on the magnitude of the vibration.Notch filters are adopted to extract the synchronous(1×Ω)and twice rotational frequency(2×Ω)components of the rotor vibration.Both the notch frequency of the filter and the size of feedforward storage used during the experiment have a real-time adaptation to the rotational speed.The method proposed in this work can provide effective suppression of the vibration of the rotor in case of sudden changes or fluctuations of the rotor speed.Simulations and experiments using the MILC algorithm proposed here are carried out and give evidence to the feasibility and robustness of the technique proposed.

Active Disturbance Rejection Control of Hydraulic Quadruped Robots Rotary Joints for Improved Impact Resistance

Hydraulic actuated quadruped robots have bright application prospects and significant research values in unmanned area investigation,disaster rescue and other scenarios,due to the advantages of high payload and high power to weight ratio.Among these fields,inevitable collision of robots may occur when contact with unknown objects,step on empty objects,or collapse,all of which have an impact on the working hydraulic system.To overcome the unknown external disturbances,this paper proposes an active disturbance rejection control(ADRC)strategy of double vane hydraulic rotary actuators for the hip joints of the quadruped robots.Considering the order of the valve-controlled actuator model,a three-stage tracking differentiator,a four-stage extended state observer,and a state error feedback controller are designed relatively,and the extended state observer is adopted to observe and compensate the uncertainty of external load torque of the system.The effectiveness of the ADRC method is verified in simulation environment and a single joint experimental platform.Moreover,the impact experiments of the limb leg unit are carried out after introducing the proposed ADRC strategy into hip joint,the limb leg unit of quadruped robots presents better impact resistance ability.

Predictive active control of building structures using LQR and artificial intelligence

This study presents a neural network-based model for predicting linear quadratic regulator(LQR)weighting matrices for achieving a target response reduction.Based on the expected weighting matrices,the LQR algorithm is used to determine the various responses of the structure.The responses are determined by numerically analyzing the governing equation of motion using the state-space approach.For training a neural network,four input parameters are considered:the time history of the ground motion,the percentage reduction in lateral displacement,lateral velocity,and lateral acceleration,Output parameters are LQR weighting matrices.To study the effectiveness of an LQR-based neural network(LQRNN),the actual percentage reduction in the responses obtained from using LQRNN is compared with the target percentage reductions.Furthermore,to investigate the efficacy of an active control system using LQRNN,the controlled responses of a system are compared to the corresponding uncontrolled responses.The trained neural network effectively predicts weighting parameters that can provide a percentage reduction in displacement,velocity,and acceleration close to the target percentage reduction.Based on the simulation study,it can be concluded that significant response reductions are observed in the active-controlled system using LQRNN.Moreover,the LQRNN algorithm can replace conventional LQR control with the use of an active control system.

Tension Active Disturbance Rejection Control of Automatic Yarn Splicing Robots for Ring Spinning

Automatic splicing of interrupted yarns in ring spinning has always been a problem in the industry.Factors such as low yarn strengths and environmental influence on yarn tensions make it difficult to control the yarn tension during the robotic splicing process.The purpose of this research is to design active disturbance rejection control(ADRC)for a third-order nonlinear tension system subject to external disturbances.Firstly,a third-order extended state observer(ESO)is designed to achieve the suppression and the compensation of the internal modeling error and the external disturbances of the system.Secondly,the adaptive gain error feedback control and the filtering process are designed to reduce the influence of sensor noise on the disturbance observation.Finally,the tension control during the splicing process is simulated and experimented,and the experiments show that the method has good robustness in the tension tracking task under a dynamic environment,which verifies the effectiveness of the method.

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.

Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid

The merits of compressed air energy storage(CAES)include large power generation capacity,long service life,and environmental safety.When a CAES plant is switched to the grid-connected mode and participates in grid regulation,using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage.This occurs because the CAES output voltage does not match the frequency,amplitude,and phase of the power grid voltage.Therefore,an adaptive linear active disturbance-rejection control(A-LADRC)strategy was proposed.Based on the LADRC strategy,which is more accurate than the traditional proportional integral controller,the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters,resulting in improved accuracy and response speed.The problem of large impulse current when CAES is switched to the grid-connected mode is addressed,and the frequency fluctuation is reduced.Finally,the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform.The influence of the k value in the adaptive-adjustment formula on the A-LADRC was analyzed through simulation.The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.