Unknown input observer based neuro-adaptive fault-tolerant control for vehicle platoons with sensor fault and output quantization

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.

Purpose The purpose of this paper is to propose an adaptive neural-sliding mode-based observer for the estimation and reconstruction of unknown faults and disturbances for time-varying nonlinear systems such as aircraft, to ensure preciseness in the diagnosis of fault magnitude as well as the shape without enhancement of system complexity and cost. Fault-tolerant control (FTC) strategy based on adaptive neural-sliding mode is also proposed in the existence of faults for ensuring the stability of the faulty system. Design/methodology/approach In this paper, three strategies are presented: adaptive radial basis functions neural network (ARBFNN), conventional radial basis functions neural network (CRBFNN) and integral-chain differentiator. For the purpose of enhancement of fault diagnosis and isolation, a new sliding mode-based concept is introduced for the weight updating parameters of radial basis functions neural network (RBFNN).The main objective of updating the weight parameters adaptively is to enhance the effectiveness of fault diagnosis and isolation without increasing the computational complexities of the system. Results depict the effectiveness of the proposed ARBFNN approach in fault detection (FD) and approximation compared to CRBFNN, integral-chain differentiator and schemes existing in literature. In the second step, the FTC strategy is presented separately for each observer in the presence of unknown faults and failures for ensuring the stability of the system, which is validated on Boeing 747 100/200 aircraft. Findings The proposed adaptive neural-sliding mode approach is investigated, which depicts more effectiveness in numerous situations such as faults, disturbances and uncertainties compared to algorithms used in literature. In this paper, both the fault approximation and isolation and the fault tolerance approaches are studied. Practical implications For the enhancement of safety level as well as for avoiding any kind of damage, timely FD and fault tolerance have always had a significant role; therefore, the algorithms proposed in this research ensure the tolerance of faults and failures, which plays a vital role in practical life for avoiding any kind of damage. Originality/value In this study, a new neural-sliding mode concept is adopted for the adaptive faults approximation and reconstruction, and then the FTC algorithms are studied for each observer separately, whereas in previous studies, only the fault detection and isolation (FDI) or the fault tolerance problems were studied. Results demonstrate the effectiveness of the proposed strategy compared to the approaches given in the literature.

Track switches are essential in order to enable railway vehicles to change routes however they are also the largest single cause of failure on the railway network and remain a single point of failure. This thesis focusses on modelling and fault tolerant control of a new type of electromechanical railway track switch. Unlike conventional track switch machines, this switch needs closed loop feedback control. Firstly, a detailed simulation model of the switch is developed and validated against experimental results. Two model-based control designs are then developed and tested: a classical cascaded P/PI controller and a modern state feedback LQR controller. The two controllers are compared and it is found that, whilst there are some performance differences, both meet the requirements for use in a redundantly actuated track switch. Following this, a fault tolerant control scheme for sensor faults is developed and validated using fault detection, identification and accommodation methods applied to a detailed non-linear simulation model and then validated on the experimental test rig. The results demonstrate that using a reliable fault tolerant control configuration could increase the availability and reliability of the switch in the presence of sensor faults. Finally, a fault tolerant control approach to actuator faults on the switch with triplex redundancy is developed and validated. In order to achieve this, a dynamic model of a railway track is developed in simulation as the basis for load application to the system. Three parallel actuators with their associated controllers are used to actuate the switch showing good performance in meeting the position control requirements. Different actuator faults are applied and their control performance results are shown. A summary of the control performance is also presented highlighting the differences in performance with different permutations of actuator faults. Overall, it is shown that redundancy in actuation with a suitable control scheme provides benefits in achieving post-fault availability of a redundantly actuated electromechanical railway track switch in the presence of actuator faults.

Vehicle platoon, as an important application of connected automated vehicles (CAVs), is a hot topic in the intelligent transportation systems (ITSs). Most existing results on platoon control used the exact feedback linearization method to transform nonlinear vehicle dynamics into linear ones, which required complete prior knowledge of parameters. As the measurement errors and the environment disturbance exist, the accurate parameters are difficult to obtain in real world. This paper considers a nonlinear uncertain vehicle platoon under a network topology (NT) modeled by a spanning tree in a digraph. Radial basis function neural networks (RBFNNs) are used to approximate the uncertain function and an adaptive distributed controller is designed by backstepping control method. To reduce the update rate of the controllers, an event-triggered control scheme is proposed with two different kinds of triggering conditions. It is proven that vehicle platoon practical consensus can be achieved under the Zeno-free adaptive event-triggered control scheme. Moreover, for bidirectional (BD) NT and two predecessor-following (TPF) NT, vehicle platoon reaches the string stability. Finally, a vehicle platoon under three different kinds of NTs is simulated to demonstrate the effectiveness of the theoretical results.

This paper develops a novel fault reconstruction (FR) method and an FR-based fault-tolerant control (FTC) scheme for systems suffering from both sensor and actuator faults based on the combination of a Luenberger-like reduced-order observer and an interval observer. Firstly, by introducing an output transformation, an auxiliary output that is able to decouple the sensor fault is obtained. Secondly, for addressing the external disturbance and actuator fault, a multiple unknown input (MUI) is formed, and a reduced-order observer that is able to decouple the MUI is constructed. Consequently, asymptotic convergence estimations of the state and the sensor fault can be accomplished. Thirdly, in order to obtain the asymptotic convergence actual FR (AFR), an interval observer is designed. After this, an algebraic connection of the MUI and the state error estimation is given, and, based on the algebraic relationship, an algebraic MUI reconstruction (MUIR) method is proposed. Finally, an FTC scheme is developed by using the state estimation and MUIR. Under the FTC, the closed-loop system is asymptotically stable even if it suffers from sensor and actuator faults simultaneously. Theoretical analysis demonstrates that the observer-based FTC mechanism satisfies the separation principle. At last, two simulation examples are given to verify the effectiveness of the proposed methods.

Electro-hydraulic actuators (EHAs) have been widely used in modern industries. However, sensor faults and actuator faults in EHA systems can arise due to aging during operation, making the system unstable and unsafe. To solve these issues, fault-tolerant control (FTC) techniques for EHA systems have been studied intensively. In this paper, an FTC is proposed and developed for the mini motion package (MMP) EHA system. First, a mathematical model of the MMP system is formulated and improved to provide position tracking control using a well-known proportional-integral-derivative (PID) controller. Second, an unknown input observer (UIO) reconstruction is performed to estimate the states, disturbances, and sensor faults so that an asymptotically stable control error can be obtained by a linear matrix inequality (LMI) optimization algorithm through Lyapunov’s stability condition. Third, the FTC designed for the nonlinear discrete-time system is formed from fault compensation based on a residual logic signal to implement the fault compensation process and ensure stability and tracking performance with respect to minimizing impacts of disturbances and sensor faults. Here, residual is defined by the difference between state response and state estimation. Finally, numerical simulations and experiments of the MMP system are presented to illustrate the efficiency of the proposed FTC technique.

A novel simultaneous fault detection and diagnostics (FDD) and fault tolerant control (FTC) strategy for nonlinear stochastic systems in closed loops based on a continuous stirred tank reactor (CSTR) is presented. The purpose of control is to track the reactant concentration setpoint. Instead of output feedback we propose here to use proportional-integral-derivative (PID) state feedback, which is shown essential to achieve FTC against sensor faults. A new concept of "equivalent bias" is proposed to model the sensor faults. Both the states and the equivalent bias are on-line estimated by a pseudo separate-bias estimation algorithm. The estimated equivalent bias is then evaluated via a modified Bayes' classification based algorithm to detect and diagnose the sensor faults. Many kinds of sensor faults are tested by Monte Carlo simulations, which demonstrate that the proposed strategy has definite fault tolerant ability against sensor faults, moreover the sensor faults can be on-line detected, isolated, and estimated simultaneously.

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

This paper addresses the issues of sensor failures and actuator faults in mining tracked mobile vehicles (TMVs) operating in harsh environments by proposing a global fixed-time fault-tolerant control strategy based on a hierarchical unknown input observer structure. First, a kinematic and dynamic model of the TMV is established considering side slip and track slip, and its linear parameter-varying (LPV) model is constructed through parameter-dependent linearization. Then, a distributed structure consisting of four collaborating low-dimensional observers is designed, including a state observer, a disturbance observer, a position sensor fault observer, and a wheel speed sensor fault observer, and the fixed-time convergence of the closed-loop system is proven. Additionally, by equivalently treating actuator faults as power losses, an observer capable of identifying and compensating for motor efficiency losses is designed. Finally, an adaptive fault-tolerant control law is proposed by combining nominal control, disturbance compensation, and sliding mode switching terms, achieving global fixed-time stability and fault tolerance. Experimental results demonstrate that the proposed control system maintains excellent trajectory tracking performance even in the presence of sensor faults and actuator power losses, with tracking errors less than 0.1 m.

This paper presents an application of a sensor fault tolerant control (FTC) scheme on a flexible joint and flexible link. A linear observer is used to reconstruct the faults. Then the reconstruction is subtracted from the faulty sensors to form a `virtual sensor' and this signal (instead of the normally used faulty output) is then used to generate the control input. This minimizes performance degradation. A design method to make the virtual sensor insensitive to system uncertainties is presented. Two fault conditions are tested; total failure and incipient faults. Then the robustness is tested by implementing the joint's FTC scheme on the link. Excellent results have been obtained for both cases; the FTC scheme caused the system performance is almost identical to the fault-free scenario, even for simultaneous faults.

Adaptive fuzzy output feedback FTC for nonstrict-feedback systems with sensor faults and dead zone input

A resilient-type current sensor fault-tolerant control (FTC) scheme for indirect vector control (IVC) of induction motor (IM) drives has been developed in the present work. The FTC scheme utilizes fundamental equations of IM to estimate the stator current and a mathematical differential operator to detect the fault of a current sensor. The formulation of the current estimator for the FTC scheme is accomplished in a stationary reference frame. This choice does not necessitate slip or synchronous speed information, simplifying the FTC structure. Besides, the fault detection process is independent of the machine model. Even partial sensor fault conditions like gain-drop and dc offset can be detected satisfactorily using such an operator. The proposed concept of FTC for IVC-IM drive is validated experimentally with a 5.5-kW IM drive laboratory prototype by conducting different case studies, including the cases of partial sensor failure.

For the forklift equipped with electrical sensors, a fault tolerant control (FTC) strategy is proposed. First, considering the uncertainty of forklift cargo and the external output disturbance, the equivalent sensor fault model of forklift is constructed. Then, a sliding mode observer (SMO) with adaptive regulation law is proposed to solve the problem that some fault reconstruction methods demand the upper bound of faults. Based on the fault value reconstructed by SMO, a sliding mode fault-tolerant controller is designed. It can realize active FTC of typical sensor faults of forklift in the presence of uncertainties and output disturbance. Finally, experiment is given to verify the effectiveness of the proposed FTC strategy.

This paper discusses the design of an active fault-tolerant flight control strategy for improvement of the operational control capability of the aircraft system. The research work draws expertise from actions undertaken within the European Flight Mechanics Action Group [FM-AG(16)] on fault-tolerant control, which develops a collaborative effort in Europe to create new fault-tolerant control technologies that significantly advance the goals of the aviation safety. The methodology is applied to a trimmable horizontal stabilizer runaway fault occurring in a large transport aircraft. The goal is to provide a self-repairing capability to enable the pilot to land the aircraft safely. The fault-tolerant control strategy works in such a way that once the fault is detected by the fault detection and isolation unit, a compensation loop is activated for safe recovery. A key feature of the proposed strategy is that the design of the fault-tolerant control loop is done independently of the nominal autopilot and the nominal flight control system in place. Nonlinear simulation results demonstrate the effectiveness of the proposed fault-tolerant control scheme.

Sensor faults affect the system's performance in the closed loop when the faulty sensor readings are used in a feedback control system. This paper presents an observer based sensor fault tolerant control system for practical implementation on modified feedback configuration for close loop control systems. The purpose of this system is to maintain the safety of the system and reliability of the process even in presence of sensor fault by adjusting or modifying the control laws based on a comparison with the state observer. The observer based sensor fault compensating element that is physically connected in parallel with the nominal closed loop system does not interfere with nominal operations i.e. when sensors are not faulty, but will implicitly provide sensor fault compensation signals when sensor fault occurs. An augmentation of an observer based element is required to generate sensor fault compensating signals to a typical feedback control system when sensor fault occurs. In effect, sensor fault tolerance is introduced thus improving control system reliability. A temperature control system is used as a case study. Results of simulation and real time implementation for temperature control system concur and demonstrate the applicability and the obvious improvement of typical closed loop control system reliability via the proposed scheme.