Control Strategies for Digital Twin Systems

With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.

Open-circuit Fault-tolerant Control Strategy Based on Five-level Power Converter for SRM System

Switched reluctance motor power converters are prone to open-circuit faults because it need to withstand large voltages and currents.Due to the small number of traditional asymmetrical half bridge topology switches,it is difficult to carry out fault tolerant control when power converters has an open-circuit fault,resulting in larger output torque ripple.This paper presents a five-level power converter based on the traditional asymmetric half-bridge power converter.The five-level topology has more switching states and can work in multi-level mode.Based on the topology,different excitation and demagnetization voltages can be choose at different speeds.A fault-tolerance strategy is developed to decrease the influence of the open-circuit fault.The five-level power converter has four switches per phase,and two of them will be used in one of the operating mode.So the remaining two of the switches can be used for safe backup,enabling fault-tolerant control when an open-circuit occur.Since each phase of the five-level power converter proposed in this paper is independent of each other,a reasonable control strategy can be used to avoid the unbalance of the midpoint potential.Finally,the topology and fault-tolerant strategy proposed in this paper are verified by simulation and experiment.

Data-based Fault Tolerant Control for Affine Nonlinear Systems Through Particle Swarm Optimized Neural Networks

In this paper, a data-based fault tolerant control(FTC) scheme is investigated for unknown continuous-time(CT)affine nonlinear systems with actuator faults. First, a neural network(NN) identifier based on particle swarm optimization(PSO) is constructed to model the unknown system dynamics. By utilizing the estimated system states, the particle swarm optimized critic neural network(PSOCNN) is employed to solve the Hamilton-Jacobi-Bellman equation(HJBE) more efficiently.Then, a data-based FTC scheme, which consists of the NN identifier and the fault compensator, is proposed to achieve actuator fault tolerance. The stability of the closed-loop system under actuator faults is guaranteed by the Lyapunov stability theorem. Finally, simulations are provided to demonstrate the effectiveness of the developed method.

Fault tolerant control based on stochastic distribution via RBF neural networks

A new fault tolerant control（FTC） via a controller reconfiguration approach for general stochastic nonlinear systems is studied.Different from the formulation of classical FTC methods,it is supposed that the measured information for the FTC is the probability density functions（PDFs） of the system output rather than its measured value.A radial basis functions（RBFs） neural network technique is proposed so that the output PDFs can be formulated in terms of the dynamic weighings of the RBFs neural network.As a result,the nonlinear FTC problem subject to dynamic relation between the input and the output PDFs can be transformed into a nonlinear FTC problem subject to dynamic relation between the control input and the weights of the RBFs neural network approximation to the output PDFs.The FTC design consists of two steps.The first step is fault detection and diagnosis（FDD）,which can produce an alarm when there is a fault in the system and also locate which component has a fault.The second step is to adapt the controller to the faulty case so that the system is able to achieve its target.A linear matrix inequality（LMI） based feasible FTC method is applied such that the fault can be detected and diagnosed.An illustrated example is included to demonstrate the efficiency of the proposed algorithm,and satisfactory results have been obtained.

Fault Tolerant Control for Networked Control Systems with Packet Loss and Time Delay

In this paper,a fault tolerant control with the consideration of actuator fault for a networked control system （NCS） with packet loss is addressed.The NCS with data packet loss can be described as a switched system model.Packet loss dependent Lyapunov function is used and a fault tolerant controller is proposed respectively for arbitrary packet loss process and Markovian packet loss process.Considering a controlled plant with external energy-bounded disturbance,a robust H ∞ fault tolerant controller is designed for the NCS.These results are also expanded to the NCS with packet loss and networked-induced delay.Numerical examples are given to illustrate the effectiveness of the proposed design method.

Adaptive sliding mode backstepping control for near space vehicles considering engine faults

A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backstepping with the sliding mode control strategy could guarantee the system’s stability and track desired signals under external disturbances and engine faults. Firstly, attitude mode description and the engine faulty model are given. Secondly, a nominal control law is designed.Thirdly, a sliding mode observer is given later in order to estimate both the information of engine faults and external disturbances. An adaptive sliding mode technology based on the previous nominal control law is developed via updating faulty parameters. Finally,analyze the system’s fault-tolerant performance and reliability through experiment simulation, which verifies the proposed design of fault-tolerant control can tolerate engine faults, as well as the strong robustness for external disturbance.

Model-Based Fault Tolerant Control for Hybrid Dynamic Systems with Sensor Faults

A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system during the time delay of fault detection and diagnosis (FDD) and fault accommodation (FA), which can be regarded as the first line of defence against sensor faults. Simulation results of a three-tank system with sensor fault are given to show the efficiency of the method.

Fault tolerant control for a robot collaborative system

A new fault-tolerant control scheme is proposed for a nonlinear collaborative system that contains two robot subsystems. When fault occurs in one subsystem, the fault-free subsystem is used to compensate the fault influence of the faulty one on the whole collaborative system. When the faulty subsystem could not repair itself or the repair process needs a long time, the controller of the fault-free subsystem is reconfigured using the fault diagnosis information and other measured infor- mation, leading to the fault tolerant control of the robot collaborative system. Simulations of fault tolerant control for the robot collaborative system show the effectiveness of the proposed method.

Event-triggered sampling and fault-tolerant control co-design based on fault diagnosis observer

A co-design scheme of event-triggered sampling mechanism and active fault tolerant control(FTC) is developed. Firstly,a fault diagnosis observer is designed to estimate both the fault and the state simultaneously by using the event-triggered sampled output. Some H∞constraints between the estimation errors and the event-triggered sampling mechanism are established to ensure the estimation accuracy. Then, based on the constraints and the obtained fault information, an event-triggered detector and a static fault tolerant controller are co-designed to guarantee the stability of the faulty system and to reduce the sensor communication cost.Furthermore, the problem of the event detector and dynamic FTC co-design is also investigated. Simulation results of an unstable batch reactor are finally provided to illustrate the effectiveness of the proposed method.

Fault Tolerant Control Scheme Design for Formation Flight Control System of Multiple Unmanned Aerial Vehicles

The command tracking problem of formation flight control system(FFCS)for multiple unmanned aerial vehicles(UAVs)with sensor faults is discussed.And the objective of the addressed control problem is to design a robust fault tolerant tracking controller such that,for the disturbances and sensor faults,the closed-loop system is asymptotically stable with a given disturbance attenuation level.A robust fault tolerant tracking control scheme,combining an observer with H∞ performance,is proposed.Furthermore,it is proved that the designed controller can guarantee asymptotic stability of FFCS despite sensor faults.Finally,a simulation of two UAV formations is employed to demonstrate the effectiveness of the proposed approach.

Physical Safety and Cyber Security Analysis of Multi-Agent Systems:A Survey of Recent Advances

Multi-agent systems(MASs)are typically composed of multiple smart entities with independent sensing,communication,computing,and decision-making capabilities.Nowadays,MASs have a wide range of applications in smart grids,smart manufacturing,sensor networks,and intelligent transportation systems.Control of the MASs are often coordinated through information interaction among agents,which is one of the most important factors affecting coordination and cooperation performance.However,unexpected physical faults and cyber attacks on a single agent may spread to other agents via information interaction very quickly,and thus could lead to severe degradation of the whole system performance and even destruction of MASs.This paper is concerned with the safety/security analysis and synthesis of MASs arising from physical faults and cyber attacks,and our goal is to present a comprehensive survey on recent results on fault estimation,detection,diagnosis and fault-tolerant control of MASs,and cyber attack detection and secure control of MASs subject to two typical cyber attacks.Finally,the paper concludes with some potential future research topics on the security issues of MASs.

Research on improved integrated FDD/FTC with effectiveness factors

This paper investigates the integrated fault detection and diagnosis（FDD） with fault tolerant control（FTC） method of the control system with recoverable faults.Firstly,a quasi-linear parameter-varying（QLPV） model is set up,in which effectiveness factors are modeled as time-varying parameters to quantify actuators and sensors faults.Based on the certainty equivalency principle,replacing the real time states in the nonlinear term of the QLPV model with the estimated states,the parameters and states can be estimated by a two-stage Kalman filtering algorithm.Then,a polynomial eigenstructure assignment（PEA） controller with time-varying parameters and states is designed to guarantee the performance of the system with recoverable faults.Finally,mathematical simulation is performed to validate the solution in a satellite closed-loop attitude control system,and simulation results show that the solution is fast and effective for on-orbit real-time computation.

Decoupling Adaptive Sliding Mode Observer Design for Wind Turbines Subject to Simultaneous Faults in Sensors and Actuators

This paper proposes an adaptive sliding mode observer(ASMO)-based approach for wind turbines subject to simultaneous faults in sensors and actuators.The proposed approach enables the simultaneous detection of actuator and sensor faults without the need for any redundant hardware components.Additionally,wind speed variations are considered as unknown disturbances,thus eliminating the need for accurate measurement or estimation.The proposed ASMO enables the accurate estimation and reconstruction of the descriptor states and disturbances.The proposed design implements the principle of separation to enable the use of the nominal controller during faulty conditions.Fault tolerance is achieved by implementing a signal correction scheme to recover the nominal behavior.The performance of the proposed approach is validated using a 4.8 MW wind turbine benchmark model subject to various faults.Monte-Carlo analysis is also carried out to further evaluate the reliability and robustness of the proposed approach in the presence of measurement errors.Simplicity,ease of implementation and the decoupling property are among the positive features of the proposed approach.

Fault Tolerant Synchronization for a General Complex DynamicalNetwork with Random Delay

A fault tolerant synchronization strategy is proposed to synchronize a complex network with random time delays and sensor faults. Random time delays over the network transmission are described by using Markov chains. Based on the Lyapunov stability theory and stochastic analysis, several passive fault tolerant synchronization criteria are derived,which can be described in the form of linear matrix inequalities. Finally,a numerical simulation example is carried out and the results show the validity of the proposed fault tolerant synchronization controller.

Fault tolerant attitude control of under-actuated spacecraft:Theory and experiment

This paper investigates fault tolerant attitude control theory and experiment for underactuated spacecraft with one reaction wheel completely broken and two others suffering actuator faults of partial loss of effectiveness or bias.A non-smooth robust adaptive fault tolerant control law is proposed under the zero-momentum and input saturation conditions.It shows that the available reaction wheels need to produce sufficient control torque for the fault tolerance.Such a new control method is implemented in a semi-physical simulation system of an air-bearing platform.Experimental results show the effectiveness of the proposed method in spacecraft practical engineering.

Impact angle constrained fuzzy adaptive fault tolerant IGC method for Ski-to-Turn missiles with unsteady aerodynamics and multiple disturbances

An impact angle constrained fuzzy adaptive fault tolerant integrated guidance and control method for Ski-to-Turn(STT)missiles subject to unsteady aerodynamics and multiple disturbances is proposed.Unsteady aerodynamics appears when flight vehicles are in a transonic state or confronted with unstable airflow.Meanwhile,actuator failures and multisource model uncertainties are introduced.However,the boundaries of these multisource uncertainties are assumed unknown.The target is assumed to execute high maneuver movement which is unknown to the missile.Furthermore,impact angle constraint puts forward higher requirements for the interception accuracy of the integrated guidance and control(IGC)method.The impact angle constraint and the precise interception are established as the object of the IGC method.Then,the boundaries of the lumped disturbances are estimated,and several fuzzy logic systems are introduced to compensate the unknown nonlinearities and uncertainties.Next,a series of adaptive laws are developed so that the undesirable effects arising from unsteady aerodynamics,actuator failures and unknown uncertainties could be suppressed.Consequently,an impact angle constrained fuzzy adaptive fault tolerant IGC method with three loops is constructed and a perfect hit-to-kill interception with specified impact angle can be implemented.Eventually,the numerical simulations are conducted to verify the effectiveness and superiority of the proposed method.

Civil aircraft fault tolerant attitude tracking based on extended state observers and nonlinear dynamic inversion

For the problem of sensor faults and actuator faults in aircraft attitude control,this paper proposes a fault tolerant control(FTC)scheme based on extended state observer(ESO)and nonlinear dynamic inversion(NDI).First,two ESOs are designed to estimate sensor faults and actuator faults respectively.Second,the angular rate signal is reconstructed according to the estimation of sensor faults.Third,in angular rate loop,NDI is designed based on reconstruction of angular rate signals and estimation of actuator faults.The FTC scheme proposed in this paper is testified through numerical simulations.The results show that it is feasible and has good fault tolerant ability.

Sensor Fault Diagnosis and Tolerant Control Based on Belief Rule Base for Complex System

This paper develops a new fault diagnosis and tolerant control framework of sensor failure(SFDTC)for complex system such as rockets and missiles.The new framework aims to solve two problems:The lack of data and the multiple uncertainty of knowledge.In the SFDTC framework,two parts exist:The fault diagnosis model and the output reconstruction model.These two parts of the new framework are constructed based on the new developed belief rule base with power set(BRB-PS).The multiple uncertainty of knowledge can be addressed by the local ignorance and global ignorance in the new developed BRB-PS model.Then,the stability of the developed framework is proved by the output error of the BRB-PS model.For complex system,the sensor state is determined by many factors and experts cannot provide accurate knowledge.The multiple uncertain knowledge will reduce the performance of the initial SDFTC framework.Therefore,in the SFDTC framework,to handle the influence of the uncertainty of expert knowledge and improve the framework performance,a new optimization model with two optimization goals is developed to ensure the smallest output uncertainty and the highest accuracy simultaneously.A case study is conducted to illustrate the effectiveness of the developed framework.

基于模型的航空发动机气路故障容错控制方法

A fault tolerant control method is proposed in this paper for a turbofan engine gas path degradation through the full flight envelope. A Quantum-behaved Particle Swarm Optimization(QPSO) algorithm is applied to obtain engine inputs adjustments, which contribute to construct off-line performance accommodation interpolation schedules. With a double closed-loop control system structure, command control is corrected based on real-time fault diagnostic results. Simulations indicate that fault tolerant control could reduce thrust and stall margin loss effectively in gas path faults.

Type-2 fuzzy logic applications designed for active parameter adaptation in metaheuristic algorithm for fuzzy fault-tolerant controller

Purpose-In recent times,fuzzy logic is gaining more and more attention,and this is because of the capability of understanding the functioning of the system as per human knowledge-based system.The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm(FPA)using concepts of fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.Design/methodology/approach-The fuzzy logic-based parameter adaptation in the FPA is proposed.In addition,type2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics,which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method,and,in reality,the effectiveness of the interval type2 fuzzy inference system(IT2 FIS)has shown to provide improved results as matched to type-1 fuzzy inference system(T1 FIS)in some latest work.Findings-One case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature.For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statitical analysis which validates the advantages of the interval type2 fuzzy FPA.The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.Originality/value-The main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type2 fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.