Iterative learning based fault detection and estimation in nonlinear systems

Aiming at a class of nonlinear systems that contains faults,a novel iterative learning scheme is applied to fault detection,and a novel algorithm of fault detection and estimation is proposed.This algorithm first constructs residual signals by the output of the practical system and the output of the designed fault tracking estimator,and then uses the residuals and the differencevalue signal of the adjacent two residuals to gradually revise the introduced virtual faults,which can cause the virtual faults to close to the practical faults in systems,thereby achieving the goal of fault detection for systems.This algorithm not only makes full use of the existing valid information of systems and has a faster tracking convergent speed than the proportional-type(P-type) algorithm,but also calculates more simply than the proportional-derivative-type(PD-type) algorithm and avoids the unstable effects of differential operations in the system.The final simulation results prove the validity of the proposed algorithm.     

The further result on global practical tracking for high-order uncertain nonlinear systems

This paper extends the unknown control coefficients with lower and upper constant bounds to the ones which may take arbitrarily large and /or small values.Since the existing methods are no longer applicable and the technical obstacles caused by the extensions are essential,new control design scheme should be exploited to the global practical tracking.By the approaches of Nussbaum-gain and adding a power integrator,the authors successfully propose the design scheme of the adaptive practical tracking controller for the systems.It is shown that the designed controller guarantees that all the closed-loop system states are bounded and the tracking error becomes prescribed arbitrarily small after a finite time.     

Robust fault detection filter and its application in MEMS-based INS/GPS

Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems,it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose,this paper proposes a robust fault-detection filter for linear discrete time-varying systems.The algorithm uses H∞ estimator to minimize the worst possible amplification from disturbances to estimate errors,and H_ index to maximize the minimum effect of faults on the residual output of the filter.This approach is applied to the MEMS-based INS/GPS.And simulation results show that the new algorithm can reduce the effect of unknown disturbances and has a high sensitivity to faults.     

The time interval alignment (IA) policies,boundary and applications with multiple stream arrivals

This paper discusses a class of interval alignment (IA) scheduling policies, which are particularly effective for the systems that do not have Markovian structure. The numerical results show that IA policies effectively smooth part flows, improve performance and decrease average Work-in-Process (WIP) by adding intermediate delays to the system. The boundary of IA policy is proven and the applications of IA policy in the system with multiple stream arrivals have been discussed. With the combination of release policy, it is practical to implement IA to multiple stream arrival system.     

Iterative learning based fault diagnosis for discrete linear uncertain systems

In order to detect and estimate faults in discrete lin-ear time-varying uncertain systems, the discrete iterative learning strategy is applied in fault diagnosis, and a novel fault detection and estimation algorithm is proposed. And the threshold limited technology is adopted in the proposed algorithm. Within the chosen optimal time region, residual signals are used in the proposed algorithm to correct the introduced virtual faults with iterative learning rules, making the virtual faults close to these occurred in practical systems. And the same method is repeated in the rest optimal time regions, thereby reaching the aim of fault diagnosis. The proposed algorithm not only completes fault detection and estimation for discrete linear time-varying uncertain systems, but also improves the reliability of fault detection and decreases the false alarm rate. The final simulation results verify the validity of the proposed algorithm.     

Fast consensus seeking for multi-agent systems

For multi-agent systems based on the local information,the agents automatically converge to a common consensus state and the convergence speed is determined by the algebraic connectivity of the communication network.To study fast consensus seeking problems of multi-agent systems in undirected networks,a consensus protocol is proposed which considers the average information of the agents’ states in a certain time interval,and a consensus convergence criterion for the system is obtained.Based on the frequency-domain analysis and algebra graph theory,it is shown that if the time interval is chosen properly,then requiring the same maximum control effort the proposed protocol reaches consensus faster than the standard consensus protocol.Simulations are provided to demonstrate the effectiveness of these theoretical results.     

Adaptive Stabilization for a Class of Feedforward Systems with Zero-Dynamics

This paper investigates adaptive state feedback stabilization for a class of feedforward nonlinear systems with zero-dynamics,unknown linear growth rate and control coefficient.For design convenience,the state transformation is first introduced and the new system is obtained.Then,the estimation law is constructed for the unknown control coefficient,and the state feedback controller is proposed with a gain updated on-hne.By appropriate choice of the estimation law for the control coefficient and the dynamic gain,the states of the closed-loop system are globally bounded,and the state of the original system converges to zero.Finally,a simulation example is given to illustrate the correctness of the theoretical results.     

Guaranteed cost control for discrete-time networked control systems with random Markov delays

The guaranteed cost control for a class of uncertain discrete-time networked control systems with random delays is addressed.The sensor-to-controller (S-C) and contraller-to-actuator (C-A) random network-induced delays are modeled as two Markov chains.The focus is on the design of a two-mode-dependent guaranteed cost controller,which depends on both the current S-C delay and the most recently available C-A delay.The resulting closed-loop systems are special jump linear systems.Sufficient conditions for existence of guaranteed cost controller and an upper bound of cost function are established based on stochastic Lyapunov-Krasovakii functions and linear matrix inequality (LMI) approach.A simulation example illustrates the effectiveness of the proposed method.     

Adaptive Output-Feedback Stabilization for PDE-ODE Cascaded Systems with Unknown Control Coefficient and Spatially Varying Parameter

This paper investigates the adaptive stabilization for a class of uncertain PDE-ODE cascaded systems. Remarkably, the PDE subsystem allows unknown control coefficient and spatially varying parameter, and only its one boundary value is measurable. This renders the system in question more general and practical, and the control problem more challenging. To solve the problem,an invertible transformation is first introduced to change the system into an observer canonical form,from which a couple of filters are constructed to estimate the unmeasurable states. Then, by adaptive technique and infinite-dimensional backstepping method, an adaptive controller is constructed which guarantees that all states of the resulting closed-loop system are bounded while the original system states converging to zero. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed method.     

Diagnosis of process faults and sensor faults in a class of nonlinear uncertain systems

This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators,each corresponding to a particular fault type.Adaptive thresholds for fault detection and isolation are presented.Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived.A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.     

Infinite-and K-Step Opacity Verification of Discrete-Event Systems Under Nondeterministic Observations

In some practical applications modeled by discrete-event systems(DES), the observations of events may be no longer deterministic due to sensor faults/failures, packet loss, and/or measurement uncertainties. In this context, it is interesting to reconsider the infinite-step opacity(∞-SO) and K-step opacity(K-SO) of a DES under abnormal conditions as mentioned. In this paper, the authors extend the notions of ∞-SO and K-SO defined in the standard setting to the framework of nondeterministic observ...     

Distributed High-Gain Attitude Synchronization Using Rotation Vectors

This paper addresses attitude synchronization problems for systems of multiple rigid-body agents with directed interconnection topologies.Two scenarios which differ in available information are considered.In the first scenario the agents can obtain their rotations and angular velocities relative to an inertial reference frame and transmit these information to their neighbors,while in the second scenario the agents can only obtain their own angular velocities and measure the relative rotations and relative angular velocities of their neighbors.By using rotation vectors and the high gain control,the authors provide torque control laws asymptotically synchronizing the rotations of the system almost globally for the first scenario and with initial rotations of the agents contained in a convex ball of SO(3)for the second scenario.An illustrative example is provided to show the synchronization results for both scenarios.     

Neural network based adaptive sliding mode control of uncertain nonlinear systems

The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activation functions, is used to emulate the equivalent and switching control terms of the classic sliding mode control (SMC). Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. In addition to keeping the stability and robustness properties of the SMC, the neural network-based adaptive sliding mode controller exhibits perfect rejection of faults arising during the system operating. Simulation studies are used to illustrate and clarify the theoretical results.     

Robust H_∞ control for uncertain descriptor systems with state and control delay

1 .INTRODUCTIONTi me delayis commonly encounteredin various en-gineering systems ,which often occursinthe trans-mission of information or material between differ-ent parts of a systemand is frequently a source ofinstability and poor performance[1]. Transporta-tion systems , communications systems , chemicalprocess , power systems are typical examples ofti me-delay systems . In the recent years , muchwork has been devoted to the analysis and synthe-sis of controller for state-delayed system…     

Stability Analysis of Event-Triggered Networked Control Systems with Time-Varying Delay and Packet Loss

Networked control systems(NCSs) are facing a great challenge from the limitation of network communication resources. Event-triggered control(ETC) is often used to reduce the amount of communication while still keeping a satisfactory performance of the system, by transmitting the measurements only when an event-triggered condition is satisfied. However, some network-induced problems would happen inevitably, such as communication delay and packet loss, which can degrade the control performance significantly and can even lead to instability. In this paper, a periodic eventtriggered NCS considering both time-varying delay and packet loss is studied. The system is discretized into a piecewise linear system with uncertainty. Then the model is handled by a polytopic overapproximation method to be more suitable for stability analysis. Finally, stability conditions are obtained and presented in terms of linear matrix inequalities(LMIs). The result is illustrated by a numerical example.     

Design and simulation of fault diagnosis based on NUIO/LMI for satellite attitude control systems

This paper presents a scheme of fault diagnosis for flexible satellites during orbit maneuver. The main contribution of the paper is related to the design of the nonlinear input observer which can avoid false alarm arising from the disturbance from orbit control force. The effects of orbit control force on the fault diagnosis system for satellite attitude control systems, including the disturbing torque caused by the misalignments and the model uncertainty caused by the fuel consumed, are discussed, where standard Luenberger observer cannot work well. Then the nonlinear unknown input observer is proposed to decouple faults from disturbance. Besides, a linear matrix inequality approach is adopted to reduce the effect of nonlinear part and model uncertainties on the observer. The numerical and semi-physical simulation demonstrates the effectiveness of the proposed observer for the fault diagnosis system of the satellite during orbit maneuver.     

Mean-square exponential stability for stochastic time-varying delay systems with Markovian jumping parameters: a delay decomposition approach

The mean-square exponential stability problem is investigated for a class of stochastic time-varying delay systems with Markovian jumping parameters.By decomposing the delay interval into multiple equidistant subintervals,a new delay-dependent and decay-rate-dependent criterion is presented based on constructing a novel Lyapunov functional and employing stochastic analysis technique.Besides,the decay rate has no conventional constraint and can be selected according to different practical conditions.Finally,two numerical examples are provided to show that the obtained result has less conservatism than some existing ones in the literature.     

Consensus of multi-vehicle cooperative attack with stochastic multi-hop time-varying delay and actuator fault

A consensus-distributed fault-tolerant(CDFT)control law is proposed for a class of leader-following multi-vehicle cooperative attack(MVCA)systems in this paper.In particular,the switching communication topologies,stochastic multi-hop timevarying delays,and actuator faults are considered,which may lead to system performance degradation or on certain occasions even cause system instability.Firstly,the estimator of actuator faults for the following vehicle is designed to identify the actuator faults under a fixed topology.Then the CDFT control protocol and trajectory following error are derived by the relevant content of Lyapunov stability theory,the graph theory,and the matrix theory.The CDFT control protocol is proposed in the same manner,where a more realistic scenario is considered,in which the maximum trajectory following error and information on the switching topologies during the cooperative attack are available.Finally,numerical simulation are carried out to indicate that the proposed distributed fault-tolerant(DFT)control law is effective.     

Sliding mode H_∞ control for a class of uncertain nonlinear state-delayed systems

1 .INTRODUCTIONSince ti me delays and uncertainties are frequentlyencounteredin practical engineering,and often re-sult in poor performance or even systeminstabili-ty , much work has been done for the analysis andsynthesis of uncertain ti me-delay systems[1 ~5 ,7 ,8].The sliding mode control (SMC) is regarded as oneof the best approaches for the robust stabilizationof uncertain ti me-delay systems ,because it exhib-its the sliding mode which has anintrinsic propertyof adaptiveness for the…