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.

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.

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.

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.

Research on Grid-Connected Control Strategy of Distributed Generator Based on Improved Linear Active Disturbance Rejection Control

The virtual synchronous generator(VSG)technology has been proposed to address the problem of system frequency and active power oscillation caused by grid-connected new energy power sources.However,the traditional voltage-current double-closed-loop control used in VSG has the disadvantages of poor disturbance immunity and insufficient dynamic response.In light of the issues above,a virtual synchronous generator voltage outer-loop control strategy based on improved linear autonomous disturbance rejection control(ILADRC)is put forth for consideration.Firstly,an improved first-order linear self-immunity control structure is established for the characteristics of the voltage outer loop;then,the effects of two key control parameters-observer bandwidthω_(0)and controller bandwidthω_(c)on the control system are analyzed,and the key parameters of ILADRC are optimally tuned online using improved gray wolf optimizer-radial basis function(IGWO-RBF)neural network.A simulationmodel is developed using MATLAB to simulate,analyze,and compare the method introduced in this paper.Simulations are performed with the traditional control strategy for comparison,and the results demonstrate that the proposed control method offers superior anti-interference performance.It effectively addresses power and frequency oscillation issues and enhances the stability of the VSG during grid-connected operation.

Active Cancelation of Acoustic Noise in Waveguides by Standard Control Task Decision Usage

Cybernetic decision variants were analyzed in order to use for physical task of active noise cancelation. 10 dB mean active noise cancellation is demonstrated in two decades frequency band by usage of cybernetic decision for acoustical duct physical scale model. The used decision was found on minimization of acoustical field power transfer function from the beginning of waveguide to their end.

Temperature Control of Proton Exchange Membrane Fuel Cell Based on Linear Active Disturbance Rejection Control

The performance of proton exchange membrane fuel cells is very sensitive to temperature. The electrochemical reaction results directly in temperature variations in the proton exchange membrane fuel cell. Ensuring effective temperature control is crucial to ensure fuel cell reliability and durability. This paper uses active disturbance rejection control in the thermal management system to maintain the operating temperature and the stack inlet and outlet temperature difference at the set value. First, key cooling system modules such as expansion tanks, coolant circulation pumps and radiators based on Simulink were built. Then, physical modeling and simulation of the fuel cell cooling system was carried out. In order to ensure the effectiveness of the control strategy and reduce the parameter tuning workload, an active disturbance rejection control parameter optimization method using an elite genetic algorithm was proposed. When the optimized control strategy responds to input disturbances, the maximum overshoot of the system is only 1.23% and can reach stability again in 30 s, so the fuel cell temperature can be controlled effectively. Simulation results show that the optimized control strategy can effectively control the stack temperature and coolant temperature difference under the influence of stepped charging current without interference or with interference, and has strong robustness and anti-interference capability.

Active Vibration Control of Beam Using Electro-magnetic Constrained Layer Damping

This paper investigates vibration control of beam through electro-magnetic constrained layer damping （EMCLD） which consists of electromagnet layer, permanent magnet layer and viscoelastic damping layer. When the coil of the electromagnet is electrified with proper control strategy, the electromagnet can exert magnetic force opposite to the direction of structural deformation so that the structural vibration is attenuated. A mathematical model is developed based on the equivalent current method to calculate the electromagnetic control force produced by EMCLD. The governing equations of the system are obtained using Hamilton＇s Principle and then reduced with the assumed-mode method. A simulation on vibration control of a cantilever beam is conducted under the velocity proportional feedback to demonstrate the energy dissipation capability of EMCLD, and the beam system with the same parameter is experimented. The results of experiment and simulation are compared and the results show that the EMCLD is an effective means for suppressing modal vibration. The results also indicate that the beam system has better control performance for larger control current. The EMCLD method presented in this paper provides an applicable and efficient tool for the vibration control of structures.

Active Control of Initial Disturbances for Rockets and Missiles

The active control theory and methods of initial disturbances for rockets and missiles are investigated. The rocket or missile/launcher is simplified as a flexible beam excited by a moving varying velocity rigid body which has two points in contact with the beam. The control force is applied at the supporting point on the beam. Active control strategies based on optimal control theory are proposed and computer simulation is carried out. Simulation results are consistent with the theoretical results, and show that the active control strategies proposed can accomplish the purpose to control the initial disturbances actively. The results show that active control of initial disturbances for rockets and missiles is feasible for application.

Simulation Study on Active Roll Control of Vehicles

The effects of active control on the vehicle roll were studied. Based on the theory that distributing the greater roll stiffness to the rear axle can improve tracking trajectory capacity and increase maneuver stability, an eight degrees of freedom vehicle model was established and feedforward feedback control strategy was devised to control distribution of lateral load transfer on the front axle and the rear one. Simulation results showed that the proposed control strategy can improve comfort, maneuver stability and safety effectively.