Sensor Compensation in Motor Drives using Kernel Regression

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.

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.

The problem of fault tolerant shape control for particle size distribution (PSD) process subject to simultaneous time‐varying actuator and sensor faults is studied. In this work, sensor and actuator faults are taken into consideration in a unified framework, and estimated by using adaptive observer technique. For the PSD process, the output distribution, rather than the system output signal itself, is adopted for shape control. Square root rational B‐spline approximation is used to fit the distribution shape. An innovative on‐line fault estimation scheme is proposed for simultaneous actuator and sensor faults estimation. Then an augmented controller based on the virtual actuator and virtual sensor techniques is designed to compensate for the faults and realise PSD shape tracking. A simulation example of emulsion polymerisation is used to validate the proposed scheme and satisfactory performance is obtained.

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.

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.

This research presents a fault tolerant (FT) control method for three-phase induction motor drives (IMDs) against sensor failures in the operating process. In this paper, an IMD applied the field oriented (FO) control for the speed and torque control is used to study the operation under sensor fault conditions. A fault detection isolation function is integrated into the FO control loop as an intermediary component to evaluate the quality of the measured signals of the sensors and provide proper signals for speed control of the drive system. A combined method of a comparison algorithm and a third difference operator (TDO) is proposed for the fault diagnosis function to improve the sustainable operation of the drive. The reliability of the proposed method will be verified through the operation mechanism of the FT function corresponding to three sensor fault states and a random noise state in the simulation environment by MATLAB/Simulink software.

A vehicle health monitoring system based on analytical redundancy, is developed for automated passenger vehicles. A residual generator and a residual processor are designed together to detect and identify actuator and sensor faults of the Buick LeSabre rapidly. The residual generator includes fault detection filters and parity equations. It uses the control commands and sensor measurements to generate the residuals, which have a unique static pattern in response to each fault. Then, the residual processor interrogates the residuals by matching them to one of several known patterns. It computes the probability of each hypothesis conditioned on the history of residuals. The fault detection latency is reduced by integrating the design of the residual generator and the residual processor. The vehicle health monitoring system is evaluated in real-time on a Buick LeSabre. The vehicle sensor and actuator faults are simulated artificially by the computer or created manually by the driver. In one experiment, a real intermittent sensor fault occurred and was immediately detected and identified. The real-time evaluation demonstrates that the vehicle health monitoring system can detect and identify actuator and sensor faults under various disturbances and uncertainties with almost minimal detection latency.

Sensor fault compensation via software sensors: Application in a heat pump's helical evaporator

FULL VEHICLE ACTIVE SUSPENSION: SENSOR FAULT DIAGNOSIS AND FAULT TOLERANCE

Disturbance observer based fault estimation and dynamic output feedback fault tolerant control for fuzzy systems with local nonlinear models

This paper investigates the consensus control problem for unknown nonlinear multi-agent systems (MASs) with both sensor and actuator faults. Different from the existing data-driven control methods for unknown nonlinear MASs without faults, a new data-driven adaptive fault-tolerant control (DDC-FTC) method is proposed. Firstly, the data mapping of agents with sensor and actuator faults is established by the locally dynamic linearisation technique. Then, by employing an adaptive fault compensation method, a fault-tolerant controller is designed for unknown nonlinear MASs. Especially, through the stability analysis, it is proven that the consensus tracking error under the designed controller is bounded, where the error bound is related with the parameters in the proposed compensation mechanism, which can be effectively decreased by tuning the parameters. Finally, simulations are given to verify the correctness of the proposed DDA-FTC approach.

Loss of control accounts for over 25% of aircraft accidents worldwide. This study presents a fault tolerant flight control strategy for increasing aircraft safety. The work has been undertaken within the Action Group on fault tolerant control (FTC) of the European GARTEUR programme, which develops collaborative efforts in Europe to create new FTC technologies that could significantly advance the goals of the aviation safety. After the fault detection and confirmation by the in-flight dedicated systems, a compensation loop is activated to ensure safe recovery. The design of the FTC loop is achieved without any changes in the nominal (and certificated) flight control system (FCS). The FTC scheme design is formulated as an H∞ strong stabilisation problem. Fault compensability is subsequently discussed and formulated as a trim-deficiency analysis problem. The proposed technique is implemented on the SIMONA flight simulator and evaluated through a pilot experiment. The tested scenario corresponds to the landing approach of a large transport aircraft (B747-100/200). The faulty situation is related to trimmable horizontal stabiliser (THS) failures. Piloted flight simulator experiments show that fault tolerance can be achieved under the condition that there exists sufficient remaining control authority.

This paper develops a novel observer-based fault-tolerant control (FTC) for wind turbine blade pitch system subjected to simultaneous actuator and sensor faults. The main contribution of this paper is the proposal of new architecture based on a combination of sliding mode control (SMC) and a proportional–proportional–integral-observer (PPIO) to provide tight reference blade pitch angle tracking regardless of the effects of actuator and sensor faults. Within this architecture, an integral sliding surface-based SMC (ISMC) has been developed to stabilize tracking error dynamics during sliding phase while the system is subjected to actuator faults. The robust PPIO-based sensor fault estimation is utilized to compensate sensor fault from the input of ISMC and thereby guarantee closed-loop system robustness against actuator and sensor faults. Stability analysis has clearly demonstrated using linear matrix inequality and Lyapunov approach. The proposed method is applied to 4.8 MW wind turbine FTC benchmark model.

This paper studies the problem of the design method of the active fault-tolerant controller, under the constraint of control input saturation, for the circumstance of simultaneous actuator and sensor faults. Considering the system with control input saturation, the design method of fault-tolerant tracking controller based on adaptive law and LMI is proposed, the saturation constraint is described by convex combination method, the adaptive law applied in actuator fault is designed, and the problem of the design of controller is transformed into optimization problem under the constraint of linear matrix inequalities. Besides, the proposed method avoids the design of fault reconstruction observer module, which simplifies the system design, and the Effectiveness of the proposed method is verified by a numerical example.

Detection, isolation and identification of multiple actuator and sensor faults in nonlinear dynamic systems: Application to a waste water treatment process