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This study is concerned with the finite-time observer (FTO) design for a class of singular systems subject to unknown inputs in both the state and the output equations. First, in order to overcome the restriction of the classical FTO method, two different non-singular auxiliary dynamic systems, which are simultaneously equivalent to the original singular system, are constructed to act as the new reference systems for the sub-observers' design. Second, based on the observer matching condition and strong observability condition, it is proven that an FTO can be designed where the observer parameters are given by an algebraic method. Also, in order to present a systematical method to compute the observer parameters, an alternative linear matrix inequality method is proposed. The advantages of the FTO over the conventional asymptotic convergence observer are discussed and numerical examples are given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study is concerned with the finite‐time observer (FTO) design for a class of singular systems subject to unknown inputs in both the state and the output equations. First, in order to overcome the restriction of the classical FTO method, two different non‐singular auxiliary dynamic systems, which are simultaneously equivalent to the original singular system, are constructed to act as the new reference systems for the sub‐observers' design. Second, based on the observer matching condition and strong observability condition, it is proven that an FTO can be designed where the observer parameters are given by an algebraic method. Also, in order to present a systematical method to compute the observer parameters, an alternative linear matrix inequality method is proposed. The advantages of the FTO over the conventional asymptotic convergence observer are discussed and numerical examples are given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of fault detection filter design for discrete-time polynomial fuzzy systems with faults and unknown disturbances. The frequency ranges of the faults and the disturbances are assumed to be known beforehand and to reside in low, middle or high frequency ranges. Thus, the proposed filter is designed in the finite frequency range to overcome the conservatism generated by those designed in the full frequency domain. Being of polynomial fuzzy structure, the proposed filter combines the H − / H ∞ performances in order to ensure the best robustness to the disturbance and the best sensitivity to the fault. Design conditions are derived in Sum Of Squares formulations that can be easily solved via available software tools. Two illustrative examples are introduced to demonstrate the effectiveness of the proposed method and a comparative study with LMI method is also provided. [ABSTRACT FROM AUTHOR]

The main goal of this work was to identify the areas that are most susceptible to desertification in a part of the Algerian steppe, and to quantitatively assess the key factors that contribute to this desertification. In total, 139 desertified zones were mapped using field surveys and photo-interpretation. We selected 16 spectral and geomorphic predictive factors, which a priori play a significant role in desertification. They were mainly derived from Landsat 8 imagery and Shuttle Radar Topographic Mission digital elevation model (SRTM DEM). Some factors, such as the topographic position index (TPI) and curvature, were used for the first time in this kind of study. For this purpose, we adapted the logistic regression algorithm for desertification susceptibility mapping, which has been widely used for landslide susceptibility mapping. The logistic model was evaluated using the area under the receiver operating characteristic (ROC) curve. The model accuracy was 87.8%. We estimated the model uncertainties using a bootstrap method. Our analysis suggests that the predictive model is robust and stable. Our results indicate that land cover factors, including normalized difference vegetation index (NDVI) and rangeland classes, play a major role in determining desertification occurrence, while geomorphological factors have a limited impact. The predictive map shows that 44.57% of the area is classified as highly to very highly susceptible to desertification. The developed approach can be used to assess desertification in areas with similar characteristics and to guide possible actions to combat desertification. [ABSTRACT FROM AUTHOR]

In this study, the authors present a new approach for the design of distributed state estimation and fault detection and isolation (FDI) filters for a class of linear parameter-varying multi-agent systems, where the state-space representations of the agents are not identical. The developed formulation for the FDI offers a distributed filter design method, in which each agent uses sensor measurements both locally and from the neighbouring agents. Each FDI filter is in the ‘unknown input observer’ form which are designed so that their outputs, i.e. residual signals, are: (i) robust with respect to the external disturbance inputs and (ii) sensitive with respect to the fault signals. Moreover, it is shown that using the proposed methodology each agent is able to estimate not only its own states, but also states of its nearest neighbours in the presence of external disturbances and faults. Finally, a numerical example is given to illustrate the efficacy of the main results of the paper. [ABSTRACT FROM AUTHOR]

In this study, the authors present a new approach for the design of distributed state estimation and fault detection and isolation (FDI) filters for a class of linear parameter‐varying multi‐agent systems, where the state‐space representations of the agents are not identical. The developed formulation for the FDI offers a distributed filter design method, in which each agent uses sensor measurements both locally and from the neighbouring agents. Each FDI filter is in the 'unknown input observer' form which are designed so that their outputs, i.e. residual signals, are: (i) robust with respect to the external disturbance inputs and (ii) sensitive with respect to the fault signals. Moreover, it is shown that using the proposed methodology each agent is able to estimate not only its own states, but also states of its nearest neighbours in the presence of external disturbances and faults. Finally, a numerical example is given to illustrate the efficacy of the main results of the paper. [ABSTRACT FROM AUTHOR]

This paper provides a detailed analysis of the output voltage/current tracking control of a PWM DCDC converter that has been modeled as a Markov jump system. In order to achieve that, a dynamic sensorless strategy is proposed to perform active disturbance rejection control. As a convex optimization problem, a novel reformulation of the problem is provided to compute optimal control. Accordingly, necessary less conservative conditions are established via Linear Matrix Inequalities. First, a sensorless active disturbance rejection design is proposed. Then, to carry out the control process, a robust dynamic observer–predictive controller approach is introduced. Meanwhile, the PWM DC-DC switching power converters are examined as discrete-time Markovian switching systems. Considering that the system is subject to modeling uncertainties, time delays, and load variations as external disturbances, and by taking partial input saturation into account, the Lyapunov–Krasovskii function is used to construct the required feasibility frame and less conservative stability conditions. As a result, the proposed design provides an efficient control strategy with disturbance rejection and time-delay compensation capabilities and maintains robust performance with respect to constraints. Finally, a PWM DC-DC power converter simulation study is performed in different scenarios, and the obtained results are illustrated in detail to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this work, a new methodology for the structuring of multiple model estimation schemas is developed. The proposed filter is applied to the estimation and detection of active mode in dynamic systems. The discrete-time Markovian switching systems represented by several linear models, associated with a particular operating mode, are studied. Therefore, the main idea of this work is the subdivision of the models set to some subsets in order to improve the detection and estimation performances. Each subset is associated with sub-estimators based on models of the subset. In order to compute the global estimate and subset probabilities, a global estimator is proposed. Theoretical developments based on a hierarchical decision, leading to more efficiency in detection and state estimation, are proposed. Naturally, these results can be used for fault detection and isolation, using the activation probabilities of operating modes. These results are applied to detect switches in the centre of gravity for vehicle roll dynamics. [ABSTRACT FROM AUTHOR]

This study deals with the design of a robust fault estimation and fault‐tolerant control for vehicle lateral dynamics subject to external disturbance and unknown sensor faults. Firstly, a descriptor state and fault observer is designed to achieve the system state and sensor fault estimates simultaneously. Secondly, based on the information of on‐line fault estimates, a robust fault‐tolerant controller based on static output‐feedback controller (SOFC) design approach is developed. To provide linear matrix inequalities of less conservatism, the results are conducted in the non‐quadratic framework dealing with unmeasurable premise variables case. Simulation results show the effectiveness of the proposed control approach when the vehicle road adhesion conditions change and the sideslip angle is unavailable for measurement. [ABSTRACT FROM AUTHOR]

Abstract: In this note, a robust fault detection observer is designed for a T–S (Takagi–Sugeno) fuzzy model with sensor faults and unknown bounded disturbances. The method applies the technique of descriptor systems by considering sensor faults as an auxiliary state variable. The idea is to formulate the robust fault detection observer design as an problem. Based on nonquadratic Lyapunov functions, a solution of the considered problem is then given via a Linear Matrix Inequality ( ) formulation. An example is proposed to illustrate the design conditions. [Copyright &y& Elsevier]

Abstract: This paper discusses the possibility of using evolutionary algorithms for the reconstruction of chaotic systems. The main aim of this work is to show that evolutionary algorithms are capable of the reconstruction of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data and a predefined set of basic mathematical “objects”. Algorithm SOMA and differential evolution were used in reported experiments here. Systems selected for numerical experiments here is the well-known Lorenz system, Simplest Quadratic Flow, Double Sroll, Damped Driven Pendulum and Nosé—Hoover oscillator. For each algorithm repeated simulations were done, totaling 20 simulations. According to obtained results it can be stated that evolutionary reconstruction is an alternative and promising way as to how to identify chaotic systems. [Copyright &y& Elsevier]

Abstract: This paper concerns the bounded real lemma for discrete-time descriptor systems. A new formulation of the bounded real lemma for these systems is given. It extends the recent results presented in and gives necessary and sufficient conditions in strict (linear matrix inequality) which is more suitable for the control design than those presented in . An application to the control design is given. A numerical example is presented to show the applicability of our approach. [Copyright &y& Elsevier]

A robust observer design is proposed for Takagi-Sugeno fuzzy neutral models with unknown inputs. The model consists of a mixed neutral and discrete delay, and the disturbances are imposed on both state and output signals. Delay-dependent sufficient conditions for the design of an unknown input T-S observer with time delays are given in terms of linear matrix inequalities. Some relaxations are introduced by using intermediate variables. A numerical example is given to illustrate the effectiveness of the given results. [ABSTRACT FROM AUTHOR]

This paper proposes novel necessary and sufficient strict linear matrix inequalities (LMI s) , to characterize admissibility of singular fractional-order linear continuous-time systems with the fractional derivative of order α belonging to 1 ≤ α < 2. Then, the problem of the bounded real lemma corresponding to the H ∞ norm computation is addressed involving additional variables. Necessary and sufficient conditions are established via a set of LMI s that can be effectively used to design H ∞ controllers. Based on the corresponding bounded real lemma, a state feedback control with a prescribed H ∞ performance index for the underlying systems is proposed. Finally, numerical examples are provided to show effectiveness of the given results. [ABSTRACT FROM AUTHOR]

Abstract: In the paper from Shaocheng Tong and Hiong Li [Observer-based robust fuzzy control of nonlinear systems with parametric uncertainties, Fuzzy Sets and Systems (131) (2002) 165–184], a method to design an observer-based robust fuzzy control of uncertain fuzzy models is proposed. However, the results obtained are not correct. This note intends to circumvent these problems by modifying the result proposed in the aforementioned paper. [Copyright &y& Elsevier]

This paper solves the problem of distributed adaptive event-triggered optimal control for six-rotor unmanned aerial vehicles under compound false data injection attacks and lumped disturbances by using the adaptive dynamic programming algorithm. Two types of triggers are introduced, one for achieving intermittent communication between unmanned aerial vehicles and the other for acting on the electronic speed data transmission network of each unmanned aerial vehicle to address bandwidth limitations. Additionally, the design of all triggers takes into consideration the adverse effects of introducing the event-triggered mechanism on system performance, and all trigger mechanisms do not display Zeno phenomena. Then, to guarantee the robustness of the unmanned aerial vehicle systems, a novel performance index function that considers attack information is designed, and a distributed disturbance observer is also designed. Moreover, on account of finding the Hamilton–Jacobi–Bellman partial differential equation more efficiently, an intelligent learning control algorithm applying identifier-critic neural networks is proposed. Using the Lyapunov stability analysis method, the proposed disturbance-observer-based optimal cooperative control scheme can guarantee that all signals in the swarm systems are bounded and the consensus control objective is achieved. Finally, some relevant simulation verification diagrams are given to test the effectiveness of the designed control scheme. [ABSTRACT FROM AUTHOR]

This paper is concerned with prescribed-time functional unknown input observer (PTFUIO) design for linear descriptor systems. First, by constructing two identical asymptotic convergence functional observers, a new PTFUIO is developed which can achieve an exact estimation within an arbitrarily prescribed time, where both the estimation accuracy and the convergence time pre-definition are independent of the initial conditions of the original system. Also, the necessary and sufficient conditions for the existence of such the PTFUIO are given in terms of the original system matrices which are easy to examine. Finally, numerical simulations are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a new fuzzy output feedback control design for autonomous vehicle steering under actuator saturation, unavailability of the sideslip angle measurement, unknown road curvature, and lateral wind force. To take into account the actuator constraint, the saturation effect is transformed into dead-zone nonlinearity. A static output controller based on non-compensation parallel distributed technic and a Takagi-Sugeno (T-S) model of vehicle lateral dynamics is proposed to consider the unavailability of some vehicle states. To avoid the problem of imposing bounds on membership functions time derivatives resulting from the use of the fuzzy Lyapunov approach, a proper integral structure based on the non-quadratic Lyapunov approach is investigated. The mixed H 2 / H ∞ stabilization conditions of the augmented closed-loop system are expressed in terms of linear matrix inequalities (LMIs). Finally, the robustness and the advantages of the proposed approaches are demonstrated through different tests. [ABSTRACT FROM AUTHOR]

This paper is concerned with the fixed-time observer (FTO) design for discrete-time singular systems subject to unknown inputs. Firstly, the observer matching condition (OMC) and the strongly observability condition (SOC) are given. Then, a new FTO design framework with a reduced-order is given which is free from the influences of the unknown inputs. It is proven that the SOC together with the OMC guarantees the existence of a FTO which is able to provide an exact state estimation in an arbitrarily pre-defined time step. Another advantage of the FTO is that both the estimation accuracy and the convergence time step can be guaranteed regardless of whatever the initial values of the observer are. Finally, a numerical simulation validates the effectiveness of the proposed result. [ABSTRACT FROM AUTHOR]

This paper presents a novel maximum power point tracking control for a stand-alone photovoltaic (PV) system based on a robust polynomial static output feedback control law subject to input saturation. In detail, a DC/DC boost converter is used to regulate the load and extract the maximum power from the photovoltaic panel. First, a polynomial fuzzy model is used to represent the photovoltaic system. Then, as this control method is based on a reference model, a regression plane is used to generate the desired trajectory representing the optimal dynamics where the PV system supplies maximum power. Then, in order to reduce the number of required sensors, a polynomial output feedback controller was developed, in which the problem of converter performance degradation resulting from duty cycle saturation was avoided by using a saturated control approach. The controller gains have been obtained by solving a sum-of-squares optimization problem, where the H ∞ performance criterion is applied to guarantee the stability of the closed-loop system while achieving an optimal rejection level of external disturbances. To evaluate the performance of the suggested controller, a number of simulations and comparisons were carried out in MATLAB/Simulink environment and under various scenarios of weather conditions. [ABSTRACT FROM AUTHOR]

This article discusses the finite‐time H∞$$ {H}_{\infty } $$ control problem for a type of discrete‐time semi‐Markov jump systems (SMJSs) with partial unavailable information. A mode‐dependent resilient state feedback control strategy and the incomplete semi‐Markov kernel (SMK) method are applied to stabilize the obtained closed‐loop systems to protect against additive disturbances that can easily occur in the controller. By considering the upper and lower thresholds of sojourn time for each mode, the number of jumps of SMJSs is effectively estimated and new finite‐time bounded related criteria are established, which cover the general case of some previous studies and are more practical in depicting systems. Besides, the H∞$$ {H}_{\infty } $$ performance is further discussed and optimization problems are presented to achieve better closed‐loop performance. At last, a simulation example and a practical example are exhibited to reveal the validity of our raised control strategies and theoretical results. [ABSTRACT FROM AUTHOR]

This article proposes a method for designing robust controller laws for a class of uncertain nonlinear parameter varying (NLPV) descriptor systems under input saturation and external disturbances. Both static and dynamic output feedback controllers are proposed. To synthesize the fuzzy controllers, the stability conditions are derived using polytopic parameter‐dependent (PD) nonquadratic Lyapunov functions with respect to the given saturation constraint on the control input. First, the designed conditions are established in terms of linear matrix inequalities (LMIs) and L2 gain performance is used to attenuate the effect of the external disturbance signals. Then, the estimation of the largest domain of attraction (DoA) for the system is formulated and solved as an optimization problem. Two examples are used to illustrate the effectiveness of the proposed design methods. [ABSTRACT FROM AUTHOR]

Summary: This paper studies the problem of adaptive fuzzy asymptotic tracking control for multiple input multiple output nonlinear systems in nonstrict‐feedback form. Full state constraints, input quantization, and unknown control direction are simultaneously considered in the systems. By using the fuzzy logic systems, the unknown nonlinear functions are identified. A modified partition of variables is introduced to handle the difficulty caused by nonstrict‐feedback structure. In each step of the backstepping design, the symmetric barrier Lyapunov functions are designed to avoid the breach of the state constraints, and the issues of overparametrization and unknown control direction are settled via introducing two compensation functions and the property of Nussbaum function, respectively. Furthermore, an adaptive fuzzy asymptotic tracking control strategy is raised. Based on Lyapunov stability analysis, the developed control strategy can effectually ensure that all the system variables are bounded, and the tracking errors asymptotically converge to zero. Eventually, simulation results are supplied to verify the feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper presents an H∞ static output-feedback control of electrical power steering (EPS) subject to actuator saturation. It deals with different practical problems in designing control of EPS systems, such as unavailability for measurement of the sideslip angle, friction effect, disturbances and the assist motor input current optimization. In order to guarantee good and stable driving, the nonlinear model of the EPS combined with bicycle model of electrical vehicles is used. Firstly, a new Takagi-Sugeno model is established, then using a fuzzy Lyapunov function, an H∞ static output-feedback is designed in terms of linear matrix inequalities. Finally, the proposed control schemes are applied to an EPS system. Simulation results and comparison with previous works show the effectiveness of the proposed control methods. [ABSTRACT FROM AUTHOR]

This paper tries to model power systems accompanied with a series of faults in the form of switched impulsive Hamiltonian systems (SIHSs) with multiple equilibria (ME) and unstable subsystems (US), and then analyze long-term stability issues of the power systems from the viewpoint of mathematics. According to the complex phenomena of switching actions of stages and generators, impulses of state, and existence of multiple equilibria, this paper first introduces an SIHS with ME and US to formulate a switching impulsive power system composed of an active generator, a standby generator, and an infinite load. Then, based on special system structures, a unique compact region containing all ME is determined, and novel stability concepts ofregion stability (RS),asymptotic region stability (ARS), andexponential region stability (ERS)are defined for such SIHS with respect to the region. Third, based on the introduced stability concepts, this paper proposes a necessary and sufficient condition of RS and ARS and a sufficient condition of ERS for the power system with respect to the region via the maximum energy function method. Finally, numerical simulations are carried out for a power system to show the effectiveness and practicality of the obained novel results. [ABSTRACT FROM AUTHOR]

This paper is concerned with the stabilization problem for continuous‐time periodic piecewise time‐varying uncertain systems with time‐varying delay, actuator failures and external disturbances. Specifically, the actuator failure consists of both unknown actuator partial failure and actuator bias failure. Based on multiple threshold values, in this work, a fault‐alarm based hybrid control protocol is developed, which is used to switch between robust and reliable controllers accurately and timely by eliminating false alarms. To be precise, a set of sufficient stability criteria is established in the form of linear matrix inequalities (LMIs) by considering an appropriate Lyapunov‐Krasovskii functional with time‐varying periodic piecewise positive‐definite matrices. Furthermore, the desired time‐varying robust and reliable controller gain matrices can be reckoned based on developed LMI‐based constraints. Eventually, two numerical examples are presented, which include the mass‐spring damper systems, to show the superiority and practicability of the designed controller. [ABSTRACT FROM AUTHOR]

This paper presents a robust intelligent controller to be applied to a class of nonholonomic electrically driven mobile robots. This class of robotic systems has an inherent sensitivity to high degree time-varying parametric uncertainties, unmodeled dynamics, and external disturbances. Furthermore, the effects of coupling terms between the mechanical subsystem and the electrical subsystem may cause severe degradations due to the time-varying variations of DC motors and mechanical structure components around their nominal values. To overcome the effects of all these quantities, the robust adaptive neural network tracking controller developed here introduces adaptive laws to estimate a local upper bound of each subsystem of the nonholonomic mobile robot, then, these laws are used on-line as controller gain parameters in order to robustly improve the transient response of the closed-loop system and reduce conservative, in the sense that the local upper bounds to characterize the corresponding uncertainties dynamics for each subsystem, initially computed based on the worse-case scenario, are not updated during the effective control of the mobile robot. In fact, even if more data become available, then they are avoided when estimating local upper bounds, and hence, the level of uncertainty is considerably decreased. According to the universal approximation theorem and the Lyapunov stability theory, the proposed intelligent controller guarantees global stability in the sense that all the states and signals of the closed-loop system, and the trajectory tracking errors are all bounded. Simulation results on two typical examples of nonholonomic electrically driven mobile robots show the effectiveness and robustness of the proposed controller. [ABSTRACT FROM AUTHOR]

Controlling motions for spar wind turbines (SWT) is necessary for reliable power production. In this paper, a control design is developed and its efficacy is demonstrated through the application to wind turbines installed on spar. SWT is expected to generate rated power under stochastic wind and wave loads. The controller design is derived from the quadratic regulator algorithm, which involves changing the dynamics of the system matrices (which are state dependent) of wind turbine. Three turbulent wind velocities are chosen at which the controller algorithm is working for turbines operational region. The ensemble average is used to eliminate statistical uncertainty, since the loads are stochastic. Illustrations through the generated power, torque and rotor speed show that the proposed controller (i.e., nonlinear quadratic one) works better than the existing baseline algorithm. More specifically, the achieved generated power through the proposed method is 29% higher than conventional one for 21 m/s stochastic wind field scenario. Along with controlling the desired variables, this algorithm also maintains the motions of platforms and forces at base of tower. Also, the ensemble means and the maxima of responses are closer to reference values with considerably lower standard-deviation. • A new coupled non-linear state space model of spar wind turbine is formulated. • Proposed a controller technique and shown its applicability in spar wind turbine. • Obtained the optimized power, generator torque and rotor speed of wind turbine. • Investigated the ensemble standard deviation for the constant power output is shown. [ABSTRACT FROM AUTHOR]

This paper presents a novel observer-based robust fault predictive control (OBRFPC) approach for a wind turbine time-delay system subject to constraints, actuator/sensor faults, and external disturbances. The proposed approach is based on an augmented state-space representation that contains state-space variables and estimation errors. The proposed augmented representation is then used to synthesize a robust predictive controller. In addition, an observer is developed and used to estimate both state variables and actuator/sensor faults. To ensure that the proposed approach has disturbance rejection capabilities, the disturbance estimates were merged with the prediction model. In addition, the disturbance rejection capabilities and fault tolerance were insured by formulating the control process as an optimization problem subject to constraints in terms of linear matrix inequalities (LMIs). As a result, the controller gains are acquired by solving an LMI problem to guarantee input-to-state stability in the presence of sensor and actuator faults. A simulation example is conducted on a nonlinear wind turbine (1 MW) model with 3 blades, a horizontal axis, and upwind variable speed subject to actuator/sensor faults in the pitch system. The results demonstrate the ability of the proposed method in dealing with nonlinear systems subject to external disturbances and keeping the control performance acceptable in the presence of actuator/sensor faults. [ABSTRACT FROM AUTHOR]

This paper focuses on mixed H 2 / H ∞ fuzzy maximum power point tracking (MPPT) of photovoltaic (PV) system under asymmetric saturation and variations in climatic conditions. To maximize the power from the PV panel array, the DC–DC boost converter is controlled by its duty ratio which is practically saturated between 0 and 1. MPPT based on conventional control presents the problems of oscillations around maximum power point (MPP) and divergence under rapid climatic changes. In order to attenuate the effect of atmospheric condition variation and take into account asymmetric saturation of the duty ratio, we propose a novel robust saturated controller based on both H 2 / H ∞ performances and Takagi-Sugeno (T-S) representation of PV-boost nonlinear system. Within this approach, the nonlinear PV-boost system and its reference are first described by T-S fuzzy models. Second, the saturation effect is represented by a polytopic model. Then, a fuzzy integral state feedback controller is designed to achieve stable MPPT control. Based on Lyapunov function, the mixed H 2 / H ∞ stabilization conditions are derived in terms of linear matrix inequalities (LMIs). The optimization of the attraction domain of closed-loop system is solved as a convex optimization problem in LMI terms. Finally, the efficiency of the proposed controller under irradiance and temperature variations is demonstrated through the simulation results. The comparison with some existing controllers shows an improvement of MPPT control performance in terms of power extraction. [ABSTRACT FROM AUTHOR]

This paper considers the problem of finite-time H ∞ control for switched systems under a dynamic event-triggered mechanism. In order to avoid frequent switching phenomenon and exclude Zeno behavior, discrete state information is used to construct a state-dependent switching law and a dynamic event-triggered mechanism. The event-triggered condition only needs to be detected at the sampled instants, so the data transmission pressure is greatly relieved. By introducing a delay-dependent Lyapunov function with the internal dynamic variable, a criterion is established to achieve the finite-time H ∞ performance. A set of dynamic event-triggered controllers and a state-dependent switching law are co-designed to reach desired behavior. An application example of the switched RLC system is offered to demonstrate the advantages of the acquired method. [ABSTRACT FROM AUTHOR]

This article is concerned with further studies on state estimation of discrete‐time nonlinear parameter varying systems with the help of an efficient multiinstant switching observer. First, a pair of variable weights for different sampling instants are introduced and thus more featured switching modes for the applied observer are produced by updating and utilizing all the varying elements that vary upon time. Second, an individual designing condition of the developed multiinstant switching observer for each switching mode is derived by considering the specific information of the updated varying elements, respectively. Indeed, the whole obtained result is less conservative than the previous ones. Finally, some comparative simulations are provided in order to illustrate the advantage and benefit of the developed results. [ABSTRACT FROM AUTHOR]

In this paper, a robust fault-tolerant model predictive control (RFTPC) approach is proposed for discrete-time linear systems subject to sensor and actuator faults, disturbances, and input constraints. In this approach, a virtual observer is first considered to improve the observation accuracy as well as reduce fault effects on the system. Then, a real observer is established based on the proposed virtual observer, since the performance of virtual observers is limited due to the presence of unmeasurable information in the system. Based on the estimated information obtained by the observers, a robust fault-tolerant model predictive control is synthesized and used to control discrete-time systems subject to sensor and actuator faults, disturbances, and input constraints. Additionally, an optimized cost function is employed in the RFTPC design to guarantee robust stability as well as the rejection of bounded disturbances for the discrete-time system with sensor and actuator faults. Furthermore, a linear matrix inequality (LMI) approach is used to propose sufficient stability conditions that ensure and guarantee the robust stability of the whole closed-loop system composed of the states and the estimation error of the system dynamics. As a result, the entire control problem is formulated as an LMI problem, and the gains of both observer and robust fault-tolerant model predictive controller are obtained by solving the linear matrix inequalities (LMIs). Finally, the efficiency of the proposed RFTPC controller is tested by simulating a numerical example where the simulation results demonstrate the applicability of the proposed method in dealing with linear systems subject to faults in both actuators and sensors. [ABSTRACT FROM AUTHOR]

This study deals with the multiple Lyapunov functions approach for the robust leader‐following consensus of one‐sided Lipschitz (OSL) multiagents, connected via switching topologies under external disturbances. Disturbances have been accounted for followers, connected via a directed graph with a spanning tree from the leader root. The authors stipulate two consensus protocols, based on the absence or existence of norm‐bounded reference input to the leader, and provide matrix inequalities for designing the parameters of consensus controllers. In the presence of L2 bounded disturbances, the proposed protocol ensures H∞ consensus criterion for minimisation of the effect of disturbances to the consensus error between the leader and followers. A remedy for striking robustness against external perturbations has been provided in the present work in contrast to the conventional consensus schemes on OSL agents. Switching OSL mobile agents and aircraft carriers consisting of a leader and five followers have been simulated in the existence of reference input and disturbances to demonstrate the empirical proficiency of the consensus protocol schemes. [ABSTRACT FROM AUTHOR]

Summary: The problem of robust fault estimation (FE) for a class of nonlinear systems in discrete‐time domain is studied via proposing a comprehensive partition‐based switching scheme. Both enhancement factors and attenuation factors are designed synchronously for accomplishing a comprehensive partition of the entire space spanned by the considered normalized fuzzy weighting functions. Thanks to the proposed comprehensive partition‐based switching scheme, six subspaces would be obtained by identifying the real‐time permutation order of the underlying parameters. Therefore, a novel fuzzy FE observer with six kinds of switching modes can be on‐line implemented. As a result, the robust H∞ performance index can be enhanced since much more information is employed than those reported results. Finally, simulation comparisons over the existing results are provided to show the obtained advantages of the article. [ABSTRACT FROM AUTHOR]

This paper applies an input-based triggering approach to investigate the secure consensus problem in multiagent systems under denial-of-service (DoS) attacks. The DoS attacks are based on the time-sequence fashion and occur aperiodically in an unknown attack strategy, which can usually damage the control channels executed by an intelligent adversary. A novel event-triggered control scheme on the basis of the relative interagent state is developed under the DoS attacks, by designing a link-based estimator to estimate the relative interagent state between intermitted communication instead of the absolute state. Compared with most of the existing work on the design of the triggering condition related to the state measurement error, the proposed triggering condition is designed based on the control input signal from the view of privacy protection, which can avoid continuous sampling for every agent. Besides, the attack frequency and attack duration of DoS attacks are analyzed and the secure consensus is reachable provided that the attack frequency and attack duration satisfy some certain conditions under the proposed control algorithm. “Zeno phenomenon” does not exhibit by proving that there exist different positive lower bounds corresponding to different link-based triggering conditions. Finally, the effectiveness of the proposed algorithm is verified by a numerical example. [ABSTRACT FROM AUTHOR]