Fault-tolerant Cooperative Control Scheme Research Articles

Neural-Network-Based Adaptive Fault-Tolerant Cooperative Control of Heterogeneous Multiagent Systems With Multiple Faults and DoS Attacks.

In this article, the issue of adaptive fault-tolerant cooperative control is addressed for heterogeneous multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults and sensor faults under denial-of-service (DoS) attacks. First, a unified control model with actuator faults and sensor faults is developed based on the dynamic models of the UAVs and UGVs. To handle the difficulty introduced by the nonlinear term, a neural-network-based switching-type observer is established to obtain the unmeasured state variables when DoS attacks are active. Then, the fault-tolerant cooperative control scheme is presented by utilizing an adaptive backstepping control algorithm under DoS attacks. According to Lyapunov stability theory and improved average dwell time method by integrating the duration and frequency characteristics of DoS attacks, the stability of the closed-loop system is proved. In addition, all vehicles can track their individual references, while the synchronized tracking errors among vehicles are uniformly ultimately bounded. Finally, simulation studies are given to demonstrate the effectiveness of the proposed method.

Distributed resilient fault-tolerant cooperative automatic generation control and multi-event triggering mechanism co-design for wind energy conversion power system

In wind energy conversion power system, some sensor and actuator fall into abnormal condition which may lead to lower wind energy utilization rate and poor system performance or even system collapse. Meanwhile, with the increasing complexity of wind energy conversion power system, more device nodes compete for limited network communication resources, there are time-delays and packets dropout in data transmission, and these may reduce the efficiency of wind energy conversion. Accordingtoaboveconsideration, the multi-event triggering mechanism based distributed resilient fault-tolerant cooperative control scheme for wind energy conversion power system is put forward. A novel model of the wind energy conversion power system is established when the sensor and actuator faults simultaneously. According to Lyapunov stability theory, the sufficient condition for system exponential mean-square stable is obtained. Different from previous fault-tolerant control method, the proposed control strategy considered the wind energy conversion power system with data transmission management under simultaneous stochastic sensor and actuator faults. The simulation demonstrates that the method proposed in this paper is effective and the multi-event triggering mechanism based distributed resilient fault-tolerant controller provides stronger reliability and higher wind energy utilization efficiency.

Virtual Coupling-Based H∞ Active Fault-Tolerant Cooperative Control for Multiple High-Speed Trains With Unknown Parameters and Actuator Faults

This paper investigates the cooperative control problem of multiple high-speed trains subject to unknown parameters and actuator faults. The cooperative operation of multiple high-speed trains is modeled as a coupled control system. On the basis of the virtual coupling technique, the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> active fault-tolerant cooperative control scheme is established to guarantee the desired tracking performances and cooperative performances. The adaptive control technique is adopted to estimate the unknown Davis’ coefficients and the fault parameters and linear matrix inequalities are utilized to derive the control gain of the cooperative control protocols for the trains. Rigorous analysis is provided to corroborate the closed-loop stability of the cooperative train control system and numerical simulation is conducted to verify the effectiveness and feasibility of the proposed results.

Fault Detection and Fault-Tolerant Cooperative Control of Multi-UAVs under Actuator Faults, Sensor Faults, and Wind Disturbances

Fault detection (FD) and fault-tolerant cooperative control (FTCC) strategies are proposed in this paper for multiple fixed-wing unmanned aerial vehicles (UAVs) under actuator faults, sensor faults, and wind disturbances. Firstly, the faulty model is introduced while the effectiveness loss, deviation of thrust throttle setting, and pitot sensor faults are considered. Secondly, the faulty UAV model with wind disturbances is linearized and the system is then converted into two subsystems by using state and output transformations. Further, cooperative unknown input observers (UIOs) are developed to estimate the faults, disturbances, and states. By combining with the observers’ estimations, adaptive thresholds are designed to detect actuator and sensor faults in the system. Then, considering state constraints, a backstepping-based FTCC scheme is proposed for multiple UAVs (multi-UAVs) suffering from actuator faults, sensor faults, and wind disturbances. It is shown by Lyapunov analysis that the tracking errors are fixed-time convergent. Finally, the effectiveness of the FD and FTCC scheme is verified by numerical simulation.

Distributed adaptive event‐triggered fault‐tolerant cooperative control of multiple UAVs and UGVs under DoS attacks

AbstractHere, the issue of distributed adaptive event‐triggered fault‐tolerant cooperative control (FTCC) is studied for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in the presence of actuator faults under denial‐of‐service attacks. To save the limited communication network resources, the distributed adaptive event‐triggered FTCC scheme is investigated for the multiple UAVs and UGVs which does not require continuous information relating to its neighbours. It is proven that the tracking errors are uniformly ultimately bounded by utilizing the Lyapunov function approach. Furthermore, the Zeno behaviour is excluded with the proposed scheme. Finally, simulation studies are provided to demonstrate the efficiency of the proposed scheme.

Neural network-based smooth fixed-time cooperative control of high-Order multi-agent systems with time-varying failures

This article tries to achieve smooth fixed-time cooperative control for high-order multi-agent systems in the presence of nonlinear uncertainties, time-varying failures and single-way communication. Due to the lemma of fixed-time stabilization involving fractional and high-power terms, it is nontrivial to design C1 smooth controllers for such systems. To eliminate linear growth conditions of uncertainties, neural networks are introduced; To ensure all fixed-time controllers are C1 continuous, a novel smooth fixed-time cooperative control framework is provided by designing C1 smooth switching and implementing dynamic surface control such that singularity and chattering problem are eliminated completely; To achieve smooth fixed-time fault-tolerant control, based on bound estimation method, the fixed-time compensation of time-varying failures is made by designing two continuous adaptive laws. Then, a novel smooth fixed-time fault-tolerant cooperative control scheme is proposed to guarantee that all control signals are continuous, smooth and bounded. Meanwhile, all internal errors will converge to arbitrarily small zones of zero within fixed time. To confirm the effectiveness of the proposed smooth fixed-time fault-tolerant cooperative control schemes, simulations based on a numerical example and a practical example are made.

Fractional order PID-based adaptive fault-tolerant cooperative control of networked unmanned aerial vehicles against actuator faults and wind effects with hardware-in-the-loop experimental validation

This paper proposes an adaptive fault-tolerant cooperative control (FTCC) scheme for networked unmanned aerial vehicles (UAVs) in the presence of actuator faults and wind effects by artfully introducing fractional order calculus, proportional–integral–derivative (PID), and recurrent neural networks. Fractional order sliding-mode surface and PID-type error mapping are first utilized to transform the synchronization tracking errors of all UAVs into a new set of errors. Then, based on these newly constructed errors, an FTCC scheme is developed to synchronously track their references. Moreover, Butterworth low-pass filter (BLF) and recurrent neural network (RNN) learning strategies are assimilated to handle the unknown terms induced by the actuator faults and wind effects. Finally, theoretical analysis and comparative hardware-in-the-loop experimental demonstrations have shown the effectiveness of the proposed control scheme.

Fault-Tolerant Cooperative Control in a Wind Farm Using Adaptive Control Reconfiguration and Control Reallocation

High reliability and availability are crucial for cost-effective operation of any wind farm. In this regard, effective schemes for fault detection, diagnosis and accommodation need to be developed to improve the reliability and availability of wind turbines and consequently wind farms (groups of wind turbines). Addressing this issue in a wind farm, this paper proposes a novel fault-tolerant cooperative control scheme based on an adaptive control reconfiguration approach that is augmented with an innovative control reallocation mechanism in a cooperative framework. Applied to a wind farm, this scheme tackles the effects of power loss faults in wind turbines, whether mild (due to mild icing or debris build-up on rotor blades) or severe (due to heavy icing). Different simulations on a wind farm benchmark model indicate the high effectiveness of the proposed scheme.

Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology

In this paper, a decentralized fault-tolerant cooperative control scheme is developed for multiple unmanned aerial vehicles (UAVs) in the presence of actuator faults and a directed communication network. To counteract in-flight actuator faults and enhance formation flight safety, neural networks (NNs) are used to approximate unknown nonlinear terms due to the inherent nonlinearities in UAV models and the actuator loss of control effectiveness faults. To further compensate for NN approximation errors and actuator bias faults, the disturbance observer (DO) technique is incorporated into the control scheme to increase the composite approximation capability. Moreover, the prediction errors, which represent the approximation qualities of the states induced by NNs and DOs to the measured states, are integrated into the developed fault-tolerant cooperative control scheme. Furthermore, prescribed performance functions are imposed on the attitude synchronization tracking errors, to guarantee the prescribed synchronization tracking performance. One of the key features of the proposed strategy is that unknown terms due to the inherent nonlinearities in UAVs and actuator faults are compensated for by the composite approximators constructed by NNs, DOs, and prediction errors. Another key feature is that the attitude synchronization tracking errors are strictly constrained within the prescribed bounds. Finally, simulation results are provided and have demonstrated the effectiveness of the proposed control scheme.

Prescribed performance-based distributed fault-tolerant cooperative control for multi-UAVs

In this paper, a prescribed performance-based distributed neural adaptive fault-tolerant cooperative control (FTCC) scheme is proposed for multiple unmanned aerial vehicles (multi-UAVs). A distributed sliding-mode observer (SMO) technique is first utilized to estimate the leader UAV’s reference. Then, by transforming the tracking errors of follower UAVs with respect to the estimated references into a new set, a distributed neural adaptive FTCC protocol is developed based on the combination of dynamic surface control (DSC) and minimal learning parameters of neural network (MLPNN). Moreover, auxiliary dynamic systems are exploited to deal with input saturation. Furthermore, the proposed control scheme can guarantee that all signals of the closed-loop system are bounded, and tracking errors of follower UAVs with respect to the estimated references are confined within the prescribed bounds. Finally, comparative simulation results are presented to illustrate the effectiveness of the proposed distributed neural adaptive FTCC scheme.

Fault-Tolerant Cooperative Control Design of Multiple Wheeled Mobile Robots

This brief investigates fault-tolerant cooperative control (FTCC) strategies for multiple differentially driven autonomous wheeled mobile robots (WMRs) in the presence of actuator faults during formation operation. First, for normal/fault-free cases and for preparation to the faults occurrence cases, an integrated approach combining input-output feedback linearization and distributed linear model predictive control techniques is designed and implemented on a team of WMRs to accomplish a formation task. Second, when actuator faults occur in one of the robots of the team, two cases are explicitly considered: 1) if the faulty robot cannot complete its assigned task due to a severe fault, then the faulty robot has to get out from the formation mission, and an FTCC strategy is designed such that the tasks of the WMRs team are reassigned to the remaining healthy robots to complete the mission with graceful performance degradation and 2) if the faulty robot can continue the mission with degraded performance, then the other team members reconfigure their controllers considering the capability of the faulty robot. Thus, the FTCC strategy is designed to re-coordinate the motion of each robot in the team. Within the proposed scheme, a fault detection and diagnosis unit using a two-stage Kalman filter to detect and diagnose actuator faults is presented. Then, the FTCC problem is formulated as an optimal assignment problem, where a Hungarian algorithm is applied. Moreover, a collision avoidance algorithm based on mechanical impedance principle is proposed to avoid the potential collision between the healthy robots and the faulty ones. Formation operation of the robot team is based on a leader-follower approach, while the control algorithm is implemented in a distributed manner. The results of real experiments demonstrate the effectiveness of the proposed FTCC scheme in different fault scenarios.

Fault-Tolerant Cooperative Control for Multiple UAVs Based on UDE and Model Following SMC

This paper presents a fault-tolerant cooperative control (FTCC) design approach with application to multiple unmanned aerial vehicles (UAVs), where the outer-loop control and the inner-loop control are designed. By virtue of a proportional control, the outer-loop of the follower UAV is able to generate reference commands. Moreover, within the proposed FTCC context, the inner-loop control is designed by resorting to the uncertainty and disturbance estimator (UDE) and model following sliding mode control (SMC) techniques, such that the deleterious effects of failed actuators can be counteracted and the safety of the cooperative flight can be ensured. The effectiveness of the developed FTCC scheme is illustrated by the numerical simulations of UAVs cooperative flight.

Fault-tolerant cooperative control for multiple UAVs based on sliding mode techniques

This paper proposes a fault-tolerant cooperative control (FTCC) design approach for multiple unmanned aerial vehicles (UAVs), where the outer-loop control and the inner-loop fault accommodation are explicitly considered. The reference signals for the inner-loop of the follower UAV can be directly produced by resorting to a proportional control. In the presence of actuator faults, the estimation of the fault information can be completed within finite time. Moreover, the control of the inner-loop is reconfigured based on the fault information adaptation and sliding mode techniques, such that the deleterious effects due to failed actuators can be compensated within finite time. Simulations of UAV cooperative flight are conducted to illustrate the effectiveness of this FTCC scheme.

Passive Fault-tolerant Cooperative Control in an Offshore Wind Farm

The rapid growth in size and capacity of wind turbines together with harsh climate conditions and limited accessibility in offshore regions all result in higher failure rates and increased maintenance requirements and costs. Such difficulties motivate the use of advanced fault detection and diagnosis as well as fault-tolerant control schemes in wind farms to improve their reliability and availability. Given the importance of this issue, the current paper employs a fuzzy model reference adaptive control approach in a cooperative framework that is oriented to the design and development of a novel passive fault-tolerant cooperative control scheme in a wind farm. This scheme handles decreased power generation faults in a wind farm caused by turbine blade erosion and debris buildup on the blades over time. The effectiveness and performance of the proposed scheme is demonstrated by a series of simulations on an advanced large off-shore wind farm benchmark model.

Real-Time Fault-Tolerant Cooperative Control of Multiple UAVs-UGVs in the Presence of Actuator Faults

This paper investigates fault-tolerant cooperative control (FTCC) strategy for a team of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in the presence of actuator faults. When actuator faults occur in one or more of the UGVs, two cases are considered: 1) the faulty UGV cannot complete its assigned task due to a severe fault occurrence, it has to get out from the formation mission. Then, FTCC strategy is designed to re-assign the mission to the remaining healthy vehicles; and 2) the faulty UGV can continue the mission with degraded performance, then the other team members will reconfigure their controllers considering the capability of faulty UGV. Thus, the FTCC strategy is designed to re-coordinate the motion of each UAV-UGV in the team. FTCC problem is formulated as an optimal assignment problem, where a Hungarian algorithm is applied. Simulation results and real-time experiments are presented in order to demonstrate the effectiveness of the proposed FTCC scheme in different fault scenarios.

Distributed Fault-Tolerant Control of Networked Uncertain Euler-Lagrange Systems Under Actuator Faults.

This paper investigates the distributed fault-tolerant control problem of networked Euler-Lagrange systems with actuator and communication link faults. An adaptive fault-tolerant cooperative control scheme is proposed to achieve the coordinated tracking control of networked uncertain Lagrange systems on a general directed communication topology, which contains a spanning tree with the root node being the active target system. The proposed algorithm is capable of compensating for the actuator bias fault, the partial loss of effectiveness actuation fault, the communication link fault, the model uncertainty, and the external disturbance simultaneously. The control scheme does not use any fault detection and isolation mechanism to detect, separate, and identify the actuator faults online, which largely reduces the online computation and expedites the responsiveness of the controller. To validate the effectiveness of the proposed method, a test-bed of multiple robot-arm cooperative control system is developed for real-time verification. Experiments on the networked robot-arms are conduced and the results confirm the benefits and the effectiveness of the proposed distributed fault-tolerant control algorithms.