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In this paper, the guaranteed cost fault-tolerant control problem for unknown multi-input continuous nonlinear systems with loss of actuator effectiveness faults is investigated using the adaptive dynamic programming algorithm. Initially, by modifying the cost function to account for actuator faults, the problem is transformed into an optimal control problem of the nominal system. Subsequently, by using an existing policy iteration (PI) algorithm to solve the corresponding optimal control problem, a guaranteed cost controller is constructed approximately. Furthermore, a rigorous proof is given to show the convergence of the aforementioned PI algorithm while taking the neural network approximation errors into consideration. Finally, simulation examples are provided to show the effectiveness of the proposed approach.

This paper studies the problem of robust adaptive fuzzy fault-tolerant tracking control for a class of nonaffine nonlinear systems with mismatched parameter uncertainties, external disturbances and actuator faults. Without using complicated backstepping technique, a direct adaptive fuzzy tracking control approach is used to achieve the fault-tolerant control objective. First, to overcome the obstacle for the nonaffine nonlinear term with actuator faults, a nonaffine compensation term is constructed to eliminate the effect of the nonaffine fault parameters. Then, based on the implicit function theorem and the mean value theorem, a novel design scheme that converts the nonaffine system into the corresponding affine system is developed, and two effective fuzzy logic systems, which are introduced to approximate the appropriate nonlinear functions, are constructed to compensate the effect on mismatched parameter uncertainty and disturbance, respectively. Furthermore, with the help of Lyapunov stability analysis, it is also proved that all the closed-loop system error signals are uniformly ultimately bounded. Finally, a numerical example is given to verify the efficiency of the presented adaptive fuzzy fault-tolerant tracking design approach.

This paper studies the simultaneous fault detection and robust control problem for discrete-time switched systems. A switching law and output feedback-based controller/detectors are designed to meet control and detection objectives. In state-dependent switching framework, the proposed switching law uses only the partial measurable states of the closed-loop switched system, which is easy to design and realize. Under the switching law, some regions in which each subsystem is activated are first constructed. Sufficient conditions are then provided such that the sensitivity to faults and robustness to unknown inputs are guaranteed in these regions, and not necessarily everywhere. Thus, the closed-loop system is with the detection and robust performances even if all subsystems are without them, which reduces the performance requirements for each subsystem in time-dependent switching framework. A solution of the considered problem is obtained via linear matrix inequalities. Finally, an example is given to show the effectiveness of the proposed method.

This paper studies the adaptive fuzzy fault-tolerant control (FTC) problem for a class of nonlinear systems with mismatched uncertainties and actuator faults. Two control schemes are designed to compensate for the actuator faults including outage, stuck and loss of effectiveness. The fuzzy logic systems are applied to approximate the bound of unknown nonlinear functions without knowing the information about the upper bound of mismatched uncertainties. By using projection modification algorithm and the improved adaptation law with $$\sigma $$ -modification, the adaptive fuzzy FTC scheme is designed. It is shown that the system states can converge asymptotically to zero even in the presence of actuator faults. However, the chattering phenomenon may occur. To overcome the undesirable chattering phenomenon, a continuous-state feedback control strategy is adopted for the control design so that the required assumption can be removed. It is shown that all the signals in the resulting closed-loop system are semi-globally uniformly ultimately bounded. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control methods.

This paper investigates the $$L_{2}$$ -gain analysis and control problem for switched systems with actuator saturation. A minimal dwell time constraint is first introduced, which avoids possible arbitrarily fast switching. Then, to satisfy the mentioned constraint, a switching strategy depending only on a lower bound of the dwell time and partial measurable states of the closed-loop system is developed in output feedback framework, which extends previous results in state feedback framework. Further, under the proposed switching strategy, time-varying hull controllable regions and saturated output feedback controllers working on them are constructed such that the closed-loop system has a prescribed $$L_{2}$$ -gain. Meanwhile, the states of the system starting from the origin will remain inside a time-varying ellipsoid determined by a discretized Lyapunov matrix function. In addition, the resulting ellipsoid is also proven to be between two time-invariant ellipsoids. A solution of the considered problem is given via a linear matrix inequality formulation. Finally, an example is exploited to illustrate the effectiveness of the theoretical results.

This paper is concerned with the fault detection (FD) problem for a class of linear discrete-time switched systems in finite-frequency domain. The fault detection filters (FDFs) with switching mechanism are utilized to generate residual to detect fault. Different from the existing FD schemes based on the arbitrary switching or average dwell time switching method, a novel scheme is presented, where the states of the FDFs are used to construct not only the residual but also the switching law. This guarantees that the overall switched system is asymptotically stable and with the fault sensitive performance and disturbance attenuation performance in the low-, middle-, and high-frequency domain, respectively. A solution of the considered problem is given via linear matrix inequalities. Finally, a numerical example is presented to show the advantage of the proposed method.

This article investigates the problem of fault diagnosis (FD) for a class of nonlinear state-feedback control systems subject to parameter uncertainties. The considered nonlinear systems are described by T–S fuzzy models with local nonlinear parts and uncertain grades of membership. First, a general actuator fault model is proposed, which considers bias faults and gain faults. Then, a switching technique is introduced to address the unknown membership functions, external disturbances, faults, and their coupling. Furthermore, an adaptive FD observer design method combined with the switching technique is proposed to estimate the occurred actuator fault. It is noted that the obtained fault errors converge exponentially to zero. Finally, a numerical example of NSV reentry dynamic model is given to confirm the effectiveness of the new results.

This paper presents a study on the problem of designing non-fragile H∞ controllers with sparse structures for linear continuous-time systems. A new algorithm is proposed to define and further design sparse structured controllers. Firstly, sparse structures are specified from a given fully parameterized H∞ controller. Then, a three-step design procedure for non-fragile dynamic output feedback H∞ controllers with the sparse structures is provided. The resulting designs guarantee that the closed-loop system is asymptotically stable and the H∞ performance from the disturbance to the regulated output is less than a prescribed level. A numerical example is given to illustrate the design methods.

This paper studies the fault tolerant control problem for a class of uncertain chaotic systems via sliding mode control. Both actuator faults and saturation are considered. Under an actuator redundancy assumption, an important lemma is first given and proved to find a lower bound of fault information and saturation degree. Then an adaptive sliding mode controller is designed to guarantee locally asymptotical stability of synchronization error. Compared with existing literature, an obvious relationship between actuator fault information and stability region is revealed. An improved strategy is also proposed to reduce conservativeness when estimating stability region. Finally, a model of Chua’s circuit systems is used to demonstrate these results.

This paper deals with H-infinity filtering of discrete-time systems with polytopic uncertainties. The uncertain parameters are supposed to reside in a polytope. By using the parameter-dependent Lyapunov function approach and introducing some slack matrix variables, a new sufficient condition for the H-infinity filter design is presented in terms of solutions to a set of linear matrix inequalities (LMIs). In contrast to the existing results for H-infinity filter design, the main advantage of the proposed design method is the reduced conservativeness. An example is provided to demonstrate the effectiveness of the proposed method.

This paper utilizes the adaptive technique to design a class of active synchronizing masterslave large scale systems against imperfect actuators and networked interconnections with bias faults and signal attenuations, respectively. Without the requirement of knowledge of eventual faulty factors of bias-actuators on systems, and attenuation factors of connected networks, an adaptive mechanism is designed to estimate each unknown faulty factor on-line for constructing a class of distributed adaptive controllers. Then based on the adaptive adjustment parameters and Lyapunov stability theory, Lyapunov functions are addressed to prove that the proposed adaptive master-slave large-scale system can be guaranteed to be asymptotic synchronization with the improper actuator and faulty transmitted signals. Finally, a multiple vehicle large-scale system is used to verify the efficiency of the method.

This paper is concerned with the robust quantized feedback stabilization problem for a class of uncertain nonlinear large-scale systems with dead-zone nonlinearity in actuator devices. It is assumed that state signals of each subsystem are quantized and the quantized state signals are transmitted over a digital channel to the controller side. Combined with a proposed discrete on-line adjustment policy of quantization parameters, a decentralized sliding mode quantized feedback control scheme is developed to tackle parameter uncertainties and dead-zone input nonlinearity simultaneously, and ensure that the system trajectory of each subsystem converges to the corresponding desired sliding manifold. Finally, an example is given to verify the validity of the theoretical result.

This paper addresses the fault detection and isolation (FDI) problem for linear time-invariant (LTI) systems under feedback control. Considered all the possible actuator stuck faults, the closed-loop systems are modeled via multiple models, i.e., fault-free model and faulty models. A fault detection observer and a bank of fault isolation observers are designed by using adaptive estimation techniques. The explicit fault detectability and isolability conditions are derived for determining the class of faults that are detectable and isolable. An F-18 aircraft model is employed to illustrate the effectiveness of the proposed FDI approach.

This paper studies the fault tolerant control (FTC) problem for a class of polynomial nonlinear discrete-time systems with guaranteed H∞ performance in the presence of actuator faults. The concerned fault is considered as a multi-model of the typical aberration in actuators’ effectiveness. A quadratic-like polynomial Lyapunov function is presented for the H∞ specification. The main contribution of this paper is that the effect of the nonlinear terms appear in FTC analysis is described as an index in order to transform the controller design into a semi-definite programming (SDP). A numerical example is given to verify the applicability of this new approach for the nonlinear FTC synthesis.

The problems of stability analysis and controllers design for discrete-time linear systems subject to state saturation nonlinearities are investigated in this paper. Both full state saturation and partial state saturation are considered. It is well known to all that the controller design problem under state saturation is very difficult and complex to deal with. In order to overcome the difficulty, a new and tractable system is constructed, and it can be proved that the constructed system is with the same domain of attraction as the original system. With the aid of this property, to estimate the domain of attraction of the original system, an LMI-based method is presented for estimating the domain of attraction of the origin for the new constructed system under state saturation. Further, two optimization algorithms are developed for constructing dynamic output-feedback controllers and state feedback controllers, respectively, which guarantee that the domain of attraction of the origin for the closed-loop system is as ‘large’ as possible. An example is provided to demonstrate the effectiveness of the new method.

The non-fragile dynamic output feedback H∞ controller design problem is investigated. The controller to be designed is assumed to be with additive gain variations. A two-step procedure is proposed to develop sufficient conditions for the non-fragile H∞ controller design by employing the structured vertex separator. A comparison between the proposed and the existing controller design methods is provided, and a numerical example is carried out to support the theoretical findings.

This paper presents a novel control method for accommodating actuator faults in a class of multiple-input multiple-output (MIMO) nonlinear uncertain systems. The designed control scheme can tolerate both the time-varying lock-in-place and loss of effectiveness actuator faults. In each subsystem of the considered MIMO system, the controller is obtained from a backstepping procedure; an adaptive fuzzy approximator with minimal learning parameterization is employed to approximate the package of unknown nonlinear functions in each design step. Additional control effort is taken to deal with the approximation error and external disturbance together. It is proven that the closed-loop stability and desired tracking performance can be guaranteed by the proposed control scheme. An example is used to show the effectiveness of the designed controller.

This paper is concerned with the problem of H-infinity filtering for discrete-time switched linear systems under arbitrary switching laws. New sufficient conditions for the solvability of the problem are given via switched quadratic Lyapunov functions. Based on Finsler’s lemma, two sets of slack variables with special structure are introduced to provide extra degrees of freedom in optimizing the guaranteed H-infinity performance. Compared to the existing methods, the proposed one has better performances and less conservatism. An example is given to illustrate its effectiveness.

In this paper, indirect adaptive state feedback control schemes are developed to solve the robust fault-tolerant control (FTC) design problem of actuator fault and perturbation compensations for linear time-invariant systems. A more general and practical model of actuator faults is presented. While both eventual faults on actuators and perturbations are unknown, the adaptive schemes are addressed to estimate the lower and upper bounds of actuator-stuck faults and perturbations online, as well as to estimate control effectiveness on actuators. Thus, on the basis of the information from adaptive schemes, an adaptive robust state feed-back controller is designed to compensate the effects of faults and perturbations automatically. According to Lyapunov stability theory, it is shown that the robust adaptive closed-loop systems can be ensured to be asymptotically stable under the influence of actuator faults and bounded perturbations. An example is provided to further illustrate the fault compensation effectiveness.

This paper investigates the observer-based H-infinity control problem for networked control systems (NCSs) with random packet dropouts. A general packet dropout model with multiple independent stochastic variables in the multiple channels case is adopted to describe the data missing in the limited communication channels. With the consideration of the sensor-to-controller and controller-to-actuator packet dropouts at the same time, a new method is proposed based on a separation lemma to design an observer-based H-infinity controller, which exponentially stabilizes the closed-loop system in the sense of mean square and also achieves a prescribed H-infinity disturbance attenuation level. A numerical example is given to illustrate the effectiveness of the proposed control method.

In this paper, stability of discrete-time linear systems subject to actuator saturation is analyzed by combining the saturation-dependent Lyapunov function method with Finsler’s lemma. New stability test conditions are proposed in the enlarged space containing both the state and its time difference which allow extra degree of freedom and lead to less conservative estimation of the domain of attraction. Furthermore, based on this result, a useful lemma and an iterative LMI-based optimization algorithm are also developed to maximize an estimation of domain of attraction. A numerical example illustrates the effectiveness of the proposed methods.

This paper considers the problem of static output feedback (SOF) control for discrete-time switched linear systems under arbitrary switching. By the aid of switched quadratic Lyapunov functions combined with Finsler’s lemma, new sufficient conditions for SOF stabilization are obtained which guarantee a γ-performance of the closed-loop switched systems subject to input disturbances. The proposed method can work successfully in situations where the existing ones fail. Three examples are given to illustrate its effectiveness.

The problem of H∞ output feedback control for discrete-time systems is investigated in this paper. The main contribution is to provide a uniform framework for generating sufficient linear matrix inequality conditions. Those conditions are classified into two parallel parts based on the way of slack variable selection. Moreover, it is shown that the existing result is a special case of the new conditions by taking few of the additional free matrix parameters to be zero. This directly leads to more flexibility and less conservativeness in the H∞ output feedback control design. Numerical examples are carried out for illustration.

This paper studies the problems of H-infinity performance optimization and controller design for continuous-time NCSs with both sensor-to-controller and controller-to-actuator communication constraints (limited communication channels). By taking the derivative character of network-induced delay into full consideration and defining new Lyapunov functions, linear matrix inequalities (LMIs)-based H-infinity performance optimization and controller design are presented for NCSs with limited communication channels. If there do not exist any constraints on the communication channels, the proposed design methods are also applicable. The merit of the proposed methods lies in their less conservativeness, which is achieved by avoiding the utilization of bounding inequalities for cross products of vectors. The simulation results illustrate the merit and effectiveness of the proposed H-infinity controller design for NCSs with limited communication channels.

This paper studies the problem of H∞ model reference tracking control for continuous time networked control systems (NCSs) with communication constraints. By using the continuous Jensen inequality, linear matrix inequality (LMI)-based H∞ model reference tracking controller design for nominal NCSs with controller-to-actuator communication constraints is presented, and a new method is proposed to design H∞ model reference tracking controllers for NCSs with both controller-toactuator and sensor-to-controller communication constraints. The results are also extended to NCSs with norm-bounded parameter uncertainties. The merits of the proposed methods lie in their less computational complexity and less conservatism, which are achieved by adopting continuous Jensen inequality and proposing new controller design methods, respectively. The simulation results illustrate the effectiveness of the proposed H∞ model reference tracking controller design for NCSs with communication constraints.

This paper studies the robust stabilization problem of switched discrete-time linear systems subject to actuator saturation. New switched saturation-dependent Lyapunov functions are exploited to design a robust stabilizing state feedback controller that maximizes an estimation of the domain of attraction. The design problem of controller (coefficient matrices) is then reduced to an optimization problem with linear matrix inequality (LMI) constraints. A numerical example is given to show the effectiveness of the proposed method.

This paper presents an adaptive method to solve the robust fault-tolerant control (FTC) problem for a class of large scale systems against actuator failures and lossy interconnection links. In terms of the special distributed architectures, the adaptation laws are proposed to estimate the unknown eventual faults of actuators and interconnections, constant external disturbances, and controller parameters on-line. Then a class of distributed state feedback controllers are constructed for automatically compensating the fault and disturbance effects on systems based on the information from adaptive schemes. On the basis of Lyapunov stability theory, it shows that the resulting adaptive closed-loop large-scale system can be guaranteed to be asymptotically stable in the presence of uncertain faults of actuators and interconnections, and constant disturbances. The proposed design technique is finally evaluated in the light of a simulation example.

In this paper, direct adaptive-state feedback control schemes are developed to solve the robust tracking and model matching control problem for a class of distributed large scale systems with actuator faults, faulty and perturbed interconnection links, and external disturbances. The adaptation laws are proposed to update the controller parameters on-line when all the eventual faults, the upper bounds of perturbations and disturbances are assumed to be unknown. Then a class of distributed state feedback controllers is constructed to automatically compensate the fault, perturbation and disturbance effects based on the information from adaptive schemes. The proposed distributed adaptive tracking controller can ensure that the resulting adaptive closed-loop large-scale system is stable and the tracking error decreases asymptotically to zero in the presence of uncertain faults of actuators and interconnections, perturbations in interconnection channels, and disturbances. The proposed adaptive design technique is finally evaluated in the light of a simulation example.

Slack variables approach is an important technique for tackling the delay-dependent stability problem for systems with time-varying delay. In this paper, a new delay-dependent stability criterion is presented without introducing any slack variable. The technique is based on a simply integral inequality. The result is shown to be equivalent to some existing ones but includes the least number of variables. Thus, redundant selection and computation can be avoided so that the computational burden can be largely reduced. Numerical examples are given to illustrate the effectiveness of the proposed stability conditions.

This paper studies the problem of designing adaptive fault-tolerant controllers for linear time-invariant systems with actuator saturation. New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updating automatically to compensate the fault effects on systems. The designs are developed in the framework of linear matrix inequality (LMI) approach, which can enlarge the domain of attraction of closed-loop systems in the cases of actuator saturation and actuator failures. Two examples are given to illustrate the effectiveness of the design method.

A class of unknown nonlinear systems subject to uncertain actuator faults and external disturbances will be studied in this paper with the help of fuzzy approximation theory. Using backstepping technique, a novel adaptive fuzzy control approach is proposed to accommodate the uncertain actuator faults during operation and deal with the external disturbances though the systems cannot be linearized by feedback. The considered faults are modeled as both loss of effectiveness and lock-in-place (stuck at some unknown place). It is proved that the proposed control scheme can guarantee all signals of the closed-loop system to be semi-globally uniformly ultimately bounded and the tracking error between the system output and the reference signal converge to a small neighborhood of zero, though the nonlinear functions of the controlled system as well as the actuator faults and the external disturbances are all unknown. Simulation results demonstrate the effectiveness of the control approach.

This paper considers the state feedback control synthesis problem for linear continuous-time systems with small gain specifications in mixed frequency ranges. A new method for designing the state feedback controllers is developed in the framework of linear matrix inequality (LMI) approach. Finally, the effectiveness of the proposed method in comparison with the available result is illustrated via an application to insulin pumps.

This paper presents a study on the problem of non-fragile state feedback H-infinity controller design for linear discrete-time systems with quantized signals. The quantizers considered here are dynamic and time-varying. With the consideration of controller gain variations and quantized signals at the same time, a new non-fragile H-infinity control strategy is proposed with updating quantizer’s parameters, such that the quantized closed-loop system is asymptotically stable and with a prescribed H-infinity performance bound. An example is presented to illustrate the effectiveness of the proposed control strategy.

This paper studies the problem of designing adaptive fault-tolerant H-infinity controllers for linear time-invariant systems with actuator saturation. The disturbance tolerance ability of the closed-loop system is measured by an optimal index. The notion of an adaptive H-infinity performance index is proposed to describe the disturbance attenuation performances of closed-loop systems. New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updated automatically to compensate for the fault effects on systems. The designs are developed in the framework of the linear matrix inequality (LMI) approach, which can guarantee the disturbance tolerance ability and adaptive H-infinity performances of closed-loop systems in the cases of actuator saturation and actuator failures. An example is given to illustrate the efficiency of the design method.

In this paper, a fuzzy Lyapunov approach is presented for stability analysis and state feedback H∞ controller design for T-S fuzzy systems. A new stability condition is obtained by relaxing the ones derived in previous papers. Then, a set of LMI-based sufficient conditions which can guarantee the existence of state feedback H∞ controller for T-S fuzzy systems is proposed. In comparison with the existing literature, the proposed approach not only provides more relaxed stability conditions but also ensures better H∞ performance. The effectiveness of the proposed approach is shown through two numerical examples.

This paper presents a linear matrix inequality (LMI) approach to solve the fault-tolerant control (FTC) problem of actuator faults. The range of actuator faults is considered as a parameter region and subdivided into several subregions to achieve a certain desired performance specification. Based on the integral quadratic constraint (IQC) approach, a passive fault-tolerant controller for the whole fault region and multiple fault-tolerant controllers for each fault subregion are designed for guaranteeing stability and improving performance of the FTC system, respectively. According to the estimation of parameters by FDI process, the corresponding subregion controller is chosen for the stability and optimal performance of closed-loop systems when the fault occurs. The case of incorrect estimation is also considered by comparing the performance index between the switched controller and the passive fault-tolerant controller. The proposed design technique is finally evaluated in the light of a simulation example.

A dynamic output feedback controller design approach based on cone complementary linearisation procedure is proposed for linear time-invariant (LTI) systems with actuator saturation. First, the estimation of the domain of attraction is given. Then, a design method to find a larger estimation of the domain of attraction is presented. In the process of design, nonconvex conditions are obtained, so a cone complementary linearisation procedure is exploited to solve the nonconvex feasibility problem. Two examples are given to illustrate the efficiency of the design method.