Search

The primary focus of this paper is to investigate the leader–follower consensus problem of multi-agent systems (MASs) with discrete and distributed delays in complex domains. We propose a new hybrid consensus protocol that incorporates a continuous-time protocol based on the communication topology of follower agents, along with an event-triggered pinning impulsive control (ETPIC) protocol. Using the Lyapunov functional method in complex domains, we establish delay-dependent sufficient conditions for leader–follower consensus of delayed complex-valued MASs. Our results demonstrate that the proposed hybrid protocol can ensure leader–follower consensus even when the size of discrete and distributed delays exceeds the length of intervals between two consecutive triggering instants. Furthermore, we prove that the Zeno phenomenon can be excluded under the proposed control protocol. In particular, as a special case, we derive the leader–follower consensus result for delay-free complex-valued MASs based on a reduced hybrid control protocol. Two numerical examples are presented to validate the effectiveness of the proposed control scheme. • This paper studies leader–follower consensus problem of multi-agent systems with discrete and distributed delays in the complex field. • It employs a hybrid consensus protocol with both continuous control and event-triggered pinning impulsive control. • Criteria on leader–follower consensus are derived based on the proposed protocols. • The pinning mechanism reduces transmission redundancy under leader-following structure. • Zeno phenomenon can be excluded under the proposed control protocol. [ABSTRACT FROM AUTHOR]

The primary focus of this paper centers on investigating unconstrained distributed optimization problems over undirected or directed graphs. One noteworthy departure from current distributed optimization algorithms in the continuous-time domain is the integration of nabla fractional calculus, which augments algorithmic performance by reducing iterative complexity. Through rigorous analysis, this paper demonstrates that the two algorithms presented converge at the Mittag–Leffler rate to the precise solution of a distributed optimization problem over a connected undirected graph or a connected balanced directed graph with strongly convex and smooth objective functions. The research findings provide valuable insights into the potential utility of nabla fractional calculus in distributed optimization problems, highlighting the possibility of enhancing the efficiency and effectiveness of distributed optimization algorithms. • Nabla fractional distributed optimization algorithm for undirected graphs. • Nabla fractional distributed optimization algorithm for directed graphs. • Convergence analysis via nabla fractional order system theory. [ABSTRACT FROM AUTHOR]

This paper addresses the stochastic communication protocol (SCP) based controller design problem for discrete delayed system with stochastic uncertainty and Markovian packet dropouts. This issue is frequently occurred in networked control system where the packet dropouts bring obstacle for controller design. Especially, the controller terms are not allowed to be transformed directly into actuator side under the SCP. Thus, the traditional approaches are not effective to solve this design issue. In this paper, a novel sliding mode control (SMC) mechanism is given to handle the influences caused by packet dropouts, time-varying delay and SCP. A protocol-based controller is designed to guarantee that the closed-loop system is mean-square asymptotically stable with satisfactory H ∞ performance. Moreover, an optimization algorithm is further provided to compute the protocol-based gain matrix. Finally, a simulation example is proposed to verify the effectiveness of the presented protocol-based SMC design procedure. [ABSTRACT FROM AUTHOR]

This paper proposes a cooperative target allocation method for efficiently utilizing air-sea heterogeneous unmanned vehicles to counter saturation attacks by low-cost UAVs. Specifically, a bilevel model that combines the advantages of heuristic algorithms and the coalition formation game (CFG) is constructed by integrating unmanned vehicles' motion and attack attributes. The upper layer model aims to utilize the advantages of the heuristic algorithm to generate a feasible target allocation scheme in a shorter time. A genetic algorithm constrained by inheritance conditions (GAC) is proposed to solve the problem of the low efficiency of traditional genetic algorithms in solving the upper model. The lower layer model is established based on a coalition formation game, which aims to continuously and stably optimize the target allocation scheme. A search method based on mobile players is designed to form a stable coalition structure faster when the number of unmanned vehicles is enormous. Simulation results show the feasibility and superiority of the algorithm proposed in this paper in dealing with allocation tasks of different complexity. [ABSTRACT FROM AUTHOR]

This paper studies the dynamic output feedback (OF) control problem for unmanned aerial vehicles (UAVs) with limited network bandwidth by a genetic-algorithm-assisted design approach. In order to make full use of the limited network bandwidth, only partial measurement information is transmitted to the controller via the sensor-to-controller network. Round-Robin protocol is introduced to administrate the transmission rule. Sufficient conditions are presented to make sure that the closed-loop UAV system is exponentially stable with the required L 2 -gain performance. However, due to the nonlinear coupling terms of the dynamic OF controller parameters and some redundant variables in the system modeling, the established conditions are non-convex and difficult to be solved. Fortunately, genetic algorithms (GA) show good performance in solving optimization problem with nonlinear and non-convex constraints. Therefore, this paper skillfully combines GA with linear matrix inequality techniques to solve the established conditions. Finally, all the dynamic OF controller parameters and the minimal L 2 -gain can be obtained simultaneously. At the end of this paper, an UAV networked control example and a numerical example are performed to verify the effectiveness and superiorities of our method. [ABSTRACT FROM AUTHOR]

This paper proposes a novel procedure for discretizing uncertain time-invariant continuous-time linear systems in polytopic domains. The approach is based on multistep method theory and involves mixing models obtained with different multiples of a fixed step-size (sampling time), thereby increasing data availability. An optimization procedure is employed to determine the coefficients that minimize the residual discretization error, and then these coefficients are combined to construct an augmented structure for the discrete-time system. The discretization error is computed using a grid search and incorporated into the discrete-time system formulation. Using the resulting discrete-time system, a state feedback methodology is applied to synthesize digital controllers capable of stabilizing the original continuous-time system. The paper presents two sufficient Linear Matrix Inequality (LMI)-based conditions for designing robust controllers specific to the proposed structure. The first condition utilizes a constant Lyapunov function, while the second condition employs a parameter-dependent Lyapunov function. In both cases, the proposed conditions guarantee asymptotic stability for the continuous-time system in closed-loop. A numerical experiment is conducted to illustrate the validity and effectiveness of the proposed method. • Discretizatizing continuous-time time-invariant uncertain systems is an open problem. • Considering delayed steps in the discretization can provide more information. • Suitable discrete-time control design procedures are presented. [ABSTRACT FROM AUTHOR]

To solve the ship course control problem with nonlinear terms, input saturation, and complex noise, this paper proposes a saturated ship course control method with complex noise based on generalized fuzzy hyperbolic model (GFHM). Due to the characteristics of fewer identification parameters, GFHM can simplify the complexity of traditional ship fuzzy models. GFHM is more suitable for multi-variable nonlinear systems such as ships of which variables are limited and difficult to measure. Furthermore, to deal with the input rudder angle saturation problem caused by the limited capability to compensate the shipboard equipment controller, an auxiliary system is proposed. And the complex noise in the navigation environment is described by the random process. Then, a new type of ship fuzzy course controller is designed based on the theoretical framework of random differential equations (RDEs) and it is proved that the ship course system under the proposed GFHM-based controller is noise-to-state stable in probability (NSS-P) and the state is an asymptotic gain in probability (AG-P). The simulation results show that the proposed algorithm in this paper can effectively control the ship's course. [ABSTRACT FROM AUTHOR]

Concentrated on the marine surface vessel (MSV) with input saturation, model uncertainties and unknown disturbances, this paper proposes the error-constrained line-of-sight guidance-based prescribed performance dual event-triggered path following control (ECLOS-PPDETPFC) strategy which applies the dual relative threshold event-triggered mechanism (ETM) to both guidance and controller of the MSV path following. We apply the prescribed performance function (PPF) as the bounds of asymmetric modified barrier Lyapunov function (AMBLF) to construct the prescribed performance asymmetric modified barrier Lyapunov function (PPAMBLF). In guidance, event-triggered error-constrained line-of-sight (ETECLOS) is constructed by relative threshold ETM and AMBLF to reduce the calculation pressure and keep position errors within the constraint range; In controller, prescribed performance event-triggered path following control (PPETPFC) is based on the relative threshold ETM and PPAMBLF, which makes the heading error meet the prescribed performance requirements, while reducing the loss of actuator. At the same time, the adaptive auxiliary systems are used to compensate the influence of input saturation, radial basis function neural networks (RBFNNs) and adaptive laws are used to approximate the model uncertainties and composite disturbances. According to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded (SGUUB) and the Zeno phenomenon is avoided. Finally, the comparative experiment shows the effectiveness and superiority of the designed control strategy. • This paper proposes the error-constrained line-of-sight guidance-based prescribed performance dual event-triggered path following control (ETECLOS-PPETPFC) strategy. • This control strategy applies the dual relative threshold event-triggered mechanism (ETM) to both guidance and controller of the MSV path following, which can reduce controller calculation pressure and actuator loss. • This control strategy can reduce the update frequency of guidance heading angle and controller. • This control strategy can not only constrain the errors of MSV position, but also make the heading error meet the prescribed performance requirements. [ABSTRACT FROM AUTHOR]

This paper proposed an Immersion and Invariance (I&I) adaptive fault-tolerant safe control scheme for a class of safety-critical (SC) systems with parametric faults. The scheme combines I&I Adaptive Control Lyapunov Function (I&I aCLF) with I&I Adaptive Control Barrier Function (I&I aCBF) to shape the transient performance of constrained states. Forward invariance of a safe set is achieved through online parameter adaptation, and the parameter convergence is guaranteed through I&I adaptation law. The conservatism is reduced by both shaping transient performance and ensuring parameters convergence. A SC controller guaranteeing stability and safety is obtained by solving an optimization problem with safety constrain, and an analytical solution is provided to facilitate the calculation and execution of the SC controller. A numerical simulation is carried out to illustrate the effectiveness of the proposed method. • This paper presents I&I aCLF and I&I aCBF, which are used to design controllers for ensuring the stability and safety of nonlinear systems with parametric faults. • The proposed controller provides less conservatism and improves the transient performance of constrained states. The parameter convergence is guaranteed by the proposed adaptation law. • To facilitate the calculation and execution of the controller, an analytical controller for a class of SC systems with parametric faults is given. [ABSTRACT FROM AUTHOR]

To capture the underlying dynamics of the COVID-19 pandemic, we develop a stochastic SEIABR compartmental model, where the concentration of coronaviruses in the environment is considered. This paper is the first attempt to introduce the Black-Karasinski process as the random fluctuations in the modeling of epidemic transmission, and it is shown that Black-Karasinski process is a both mathematically and biologically reasonable assumption compared with existing stochastic modeling methods. We first obtain two critical values R 0 S and R 0 E related to the basic reproduction number R 0 of deterministic system. It is theoretically proved that (i) if R 0 S > 1 , the stochastic model has a stationary distribution ℓ (·) , which implies the long-term persistence of COVID-19; (ii) the disease will go extinct exponentially when R 0 E < 1 ; (iii) R 0 S = R 0 E = R 0 if there is no environmental noise in COVID-19 transmission. Then, we study the local stability of the endemic equilibrium P * of deterministic system under R 0 > 1. By developing an important lemma for solving the relevant Fokker-Planck equation, an approximate expression of probability density function of the distribution ℓ (·) around P * is further derived. Finally, several numerical examples are performed to substantiate our theoretical results. It should be mentioned that the techniques and methods of analysis in this paper can be applied to other complex high-dimensional stochastic epidemic systems. [ABSTRACT FROM AUTHOR]

This paper focuses on the robust sliding mode passive control (SMPC) problem for uncertain Markovian jump discrete systems under the finite time setting. For the considered model, the phenomenon of stochastic communication delays (SCDs) is depicted via some Bernoulli distributed stochastic variables, which involve inaccurate occurrence probability information. In view of initial condition, a common form of sliding surface is chosen. Further, the sliding motion equation can be given for the original system. Our aim of this paper is to propose some potential sufficient criteria for finite-time boundedness and passive requirement of the sliding motion. With the same objective, a comprehensive reaching condition is also utilized to construct the robust sliding mode passive controller such that the controlled system can be kept remain in a region of the sliding surface thereafter. Finally, an example is given to show the usefulness of our proposed scheme here. [ABSTRACT FROM AUTHOR]

• For the fast-varying delay, an improved analytical method based on Lyapunov-Krasovskii (LK) functionals is given by introducing and proving a new lemma, which is not only independent of the upper bound of time-varying delay, but also independent of the derivative of the time-varying delay. Hence, the developed analytical method greatly expands the application range of the LK functional. • For unknown nonconstant control coefficients, an output feedback control strategy based on the compensated system is proposed. As an intermediate link, the adaptive fuzzy system is introduced into the controller indirectly by the compensation system, so as to avoid the algebraic-loop problem. Hence, the cooperative design of the compensation system, the state observer and the controller is one of the innovations in this paper. • Considering the problems of state immeasurability and time-varying delay comprehensively, an adaptive fuzzy output-feedback control law is proposed based on an improved average dwell time, which relaxes the constraints between the LK functional of each subsystem in switched large-scale interconnected nonlinear systems. In this paper, an adaptive fuzzy decentralized output-feedback control is developed for the uncertain switched large-scale interconnected nonlinear system, which contains fast time-varying delays and unknown nonconstant control coefficients. By introducing and proving a new lemma, an improved analysis method is given based on the Lyapunov-Krasovskii (LK) functional, and it gets rid of the dependence of LK functional design on the bound of the derivative of the delay. Immeasurable states are estimated by co-designing the decentralized state observer and the innovative compensation system, which eliminates a widely adopted but strict assumption that the unknown control coefficient must be constant. By comprehensively designing the state observer, the compensation system and LK functionals, a novel adaptive fuzzy decentralized output-feedback control law is proposed, and stability of the closed-loop system is guaranteed theoretically based on an improved average dwell time. Finally, the effectiveness is further verified by complete simulation experiments. [ABSTRACT FROM AUTHOR]

The fixed-time tracking control issue is investigated for a class of high-order nonlinear delayed systems subject to mismatched disturbances in this paper. Wherein, the fuzzy logic system is applied in dealing with the nonlinear functions and the power integrator technique is appropriately introduced to address the high-order terms in the considered system. Different from the conventional methods of using the Lyapunov-Krasovskii functional approach to cope with the delayed terms in the previous work, the adaptive backstepping method is utilized in this paper. The main purpose of the addressed control problem is to design a suitable adaptive fuzzy fixed-time controller such that the closed-loop system is stable and guaranteed to be bounded in a fixed-time interval. Subsequently, the specific control law is deduced through the inductive method, and the upper bound on the settling time for the fixed-time control is given. Finally, the simulation examples are given to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• A fixed-time unknown observer is devised to estimate the matched/mismatched unknowns simultaneously within a fixed time. • By using an auxiliary function, a nonsingular fixed-time control framework is proposed without using any piecewise function. • The EMG signals are incorporated into the proposed fixed-time control framework and improves the tracking performance. [Display omitted] In this paper, a fixed-time personalized variable gain control (FTPGC) scheme is developed for a class of teleoperation systems. Efforts in this paper seek to improve the tracking performance under different operation intentions for teleoperation systems in the presence of time varying delays and uncertainties. By virtue of nonsmooth analysis, a fixed-time unknown observer (FUO) is firstly devised for the teleoperation systems such that the matched/mismatched unknowns can be observed within a fixed time. Meanwhile, with the help of an auxiliary function, a novel nonsingular fixed-time control framework is subsequently constructed without using any piecewise continuous switching functions. Moreover, the FUO and a variable gain involving electromyographic are incorporated into the fixed-time control framework, and thereby resulting the FTPGC scheme to improve trajectory tracking performance in the presence of unknowns and different operation intentions. The fixed-time stability of the entire FTPGC scheme is derived by rigorously theoretical analysis. Finally, comprehensive experiments and comparisons are conducted to demonstrate the effectiveness and feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

• Almost sure stability is studied for a semi-Markov system with/without asynchronous controller. • A new stochastic Lyapunov function is established based on the random switching time and a newly segment bounded function. • Improved sufficient conditions are proved by the ergodicity of semi-Markov process, which improve known results on stability. • Conditional probability is introduced to solve the asynchronous problem between the system and the controller. • The converge rate of the system is optimized due to the introduction a newly segment bounded function. The purpose of this paper is to study almost sure exponential stability (ASES) of a class of semi-Markov jump systems with/without asynchronous controller. Based on the stationary distribution and ergodicity of semi-Markov switching process, sufficient stability conditions of semi-Markov jump systems are established firstly, which significantly improved some known results. Then, the sufficient conditions of ASES for semi-Markov jump systems with asynchronous controller is investigated. To be pointed out that the stochastic Lyapunov function constructed in this paper is new, which couples the switching points of semi-Markov process and a newly defined segment bounded function. Finally, two examples are given to show the superiority of our conclusions. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive fixed-time tracking control problem for a class of stochastic nonlinear systems with constrained states and input saturation. By utilizing a barrier Lyapunov function (BLF), the issue caused by constrained states is settled. Simultaneously, a smooth function is constructed to approximate input saturation and the unknown nonlinear function is approximated by neural networks (NNs). In view of the fixed-time tracking control problem of stochastic nonlinear systems, a fixed-time stability lemma for stochastic nonlinear systems has been established and proved. Under the designed controller, the closed-loop system is semi-globally fixed-time stable in probability (SGFSP), and all the states are constrained within a compact set. Moreover, the controlled system in this paper achieves equilibrium within a fixed-time internal. Lastly, the presented method is verified by a simulation example. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with the dynamic feedback design for linear systems with input disturbance. We propose a new approach to design dynamic feedback such that the disturbance in the control channel can be compensated effectively. An interesting characteristic about the disturbance robustness of dynamic feedback is found. Thanks to this interesting characteristic, we just need to consider the disturbance-free system to make the dynamic feedback design. This fact is well validated by several dynamic feedback laws proposed in this paper. Our results are available for the regular linear system with harmonic disturbance. Moreover, the stabilization of an unstable heat equation with general periodic disturbance is also investigated. In order to validate the theoretical results visually, some numerical simulations are given to show the effectiveness of the proposed dynamic feedback. [ABSTRACT FROM AUTHOR]

This paper presents a complete control architecture for the implementation of adaptive sliding controllers (ASMC) in quadrotors. Aiming into presenting a control solution for real-world scenarios, this paper presents a comparative study evaluating the advantages and disadvantages of the three most common methods to implement adaptive sliding mode controllers in quadrotors. Namely, two of the compared methods aim to reduce the SMC gains to ones that keep the tracking errors inside a user-defined bound, while the third method consists of obtaining the minimal SMC gain which permits the sliding mode to exist. To inspect the compared methods in realistic and harsh conditions, the three controllers are tested far from quasi-static motion and under severe disturbances. The quadrotor was subjected to disturbances such as stabilization under intermittent wind, landing precisely subject to wind-gusts, high-speed trajectory tracking while carrying an unmodeled suspended payload with a center-of-mass offset, and trajectory tracking with a damaged propeller. The performance of the analyzed adaptive sliding mode controllers was also compared to the industrial standard PID controller. Our experimental analysis demonstrates that, in face of such disturbances, one of the analyzed adaptive sliding mode controllers excels when compared to the others, and every ASMC excels when compared to the PID. [ABSTRACT FROM AUTHOR]

This paper discusses a distributed time-varying convex optimization problem that agents have different Hessian matrices with inequality constraints. The objective is to minimize the sum of local time-varying objective functions of agents constrained by time-varying inequalities. Under the condition of undirected connected graph, a distributed continuous time consistency algorithm is designed based on average consensus estimator, sign function and log-barrier penalty function. The main idea of the algorithm proposed in this paper is to use the estimator to estimate the global information, make the state of agents reach consensus and achieve gradient descent to track the optimal solution. Theoretical findings show that all agents can reach an agreement, the proposed algorithm can track the optimal solution of the time-varying optimization problem. The effectiveness of the theoretical results is verified through a numerical examples. [ABSTRACT FROM AUTHOR]

This paper studies the mirror descent algorithm for distributed optimization, where the underlying digraph is assumed to be weight-unbalanced. Within this framework, a novel distributed mirror descent algorithm based on gradient weighting technique is developed. Theoretically, different from the existing works, which prove that the function value corresponding to the estimates converge to the optimal value of the optimization problem, this paper proves that (1) the proposed algorithm can achieve exact convergence of the estimates to the solution of the optimization problem; and (2) the algorithm has a convergence rate O (1 T) with a given time horizon T. Further, taking into account the fact that the cost functions in many significant optimization problems are dynamic, the distributed online optimization based on the proposed algorithm is studied. Especially, it is shown that the individual regret of the proposed algorithm is bounded by O (T). Finally, the theoretical results are verified through some simulation examples. [ABSTRACT FROM AUTHOR]

Quantum coherent feedback based on waveguide quantum electrodynamics plays important roles in quantum devices design and quantum information processing. In this paper, we study the coherent dynamics of the quantum network composed of two separated resonators coupling to a waveguide. Using the dynamical feedback equation in Markovian regime, we obtain the analytical solutions to the output states for the two photons incident from the same or different directions of the waveguide. The two- photon scattering properties are analyzed based on the analytical expressions. It is found that the output states of the two photons can be controlled well by the phase induced by the single photon propagating between the two separated resonators. The results given in this paper are helpful in designing quantum devices at few-photon level. [ABSTRACT FROM AUTHOR]

In this paper, in order to obtain a smaller estimation of settling time, reduce chattering caused by sign function and improve network communication efficiency, the fixed-time (FXT) synchronization of delayed BAM neural networks is analyzed based on some new FXT stability results and non-chattering quantized controllers. Firstly, by comprehensively discussing the conditions of power laws in differential inequalities, a new FXT stability lemma is presented and a smaller upper bound of settling time is estimated. Then, unlike previous controllers with sign functions, a non-chattering quantized state feedback control and a non-chattering quantized pinning control are designed, and some sufficient conditions are derived to ensure FXT synchronization of the established system. Finally, two numerical simulations are given to verify the effectiveness of the theoretical results. The results show that compared with the previous researches, this paper provides a smaller upper bound. However, the convergence time of the uncontrolled nodes is indirectly affected by the coupling of the controlled nodes and is much longer than the estimated upper bound. [ABSTRACT FROM AUTHOR]

• Firstly, compared with the homogeneous system, the more general heterogeneous coupled neural network model is studied here. By processing the heterogeneous terms, the mean-square quasi-synchronization problem under the influence of stochastic disturbance is solved. • Secondly, on the basis of discussing the influence of communication time-delay, this paper also considers various time-delays such as distributed time-delay, transmission time-delay. According to the existing conclusions of time-delay systems, we extend it to heterogeneous CNNs, and obtain a sufficient condition for time-invariant delay. • Finally, in the reaction-diffusion environment, compared with the conventional controller, a more advantageous boundary controller is designed. At the same time, the corresponding boundary control under mixed boundary conditions is proposed, and the final system is uniformly ultimately bounded. In this paper, the quasi-synchronization problem of heterogeneous stochastic coupled neural networks (HSCNNs) is discussed. The effects of the mixed time-varying delay and diffusion phenomenon on the system are considered separately in time and space. Moreover, different from the previous distributed control, boundary control is introduced to realize network synchronization. This not only reduces the space cost of the controller, but also makes it easier to implement. Thus, the mean-square quasi-synchronization of HSCNNs is guaranteed by using matrix inequality and stochastic analysis tools. In addition to focusing on systems with Neumann boundary conditions, we briefly investigate HSCNNs with time-invariant delays and mixed boundary conditions respectively, and provide sufficient conditions to achieve the desired performance. Finally, the correctness of the conclusion is verified by several examples. [ABSTRACT FROM AUTHOR]

This paper aims at rejuvenating the two rank correlation coefficients, Spearman's footrule (SF) and Gini's gamma (GG), which were forgotten in the literature for a long time due to lack of knowledge concerning their statistical properties. Under the common bivariate normal model, we establish the asymptotic analytical expressions of the mean and variance of SF and GG, and investigate the performances of SF and GG from the aspects of biased effect, approximate variance and asymptotic relative efficiency (ARE). Moreover, we further study the robustness of SF and GG under contaminated normal models. In order to get a deeper understanding of their performances, we also compare SF and GG with Kendall's tau (KT) and Spearman's rho (SR), the most widely used rank correlation coefficients, in terms of bias and mean square error (MSE) under both the normal and contaminated normal models. Finally we show an application of SF and GG in the field of signal processing through the example of time-delay estimation. Simulation results indicate that SF and GG outperform SR and KT in some cases. The new findings discovered in this paper enable SF and GG to play complementary roles to KT and SR in practice. [ABSTRACT FROM AUTHOR]

• Convolutional code is widely used in communication systems. • NFSR is the main component of the convolutional decoder. • STP is a new mathematical tool with a wide range of applications. • NFSR can be modeled very well with STP, enabling the discussion in mathematics. The nonlinear feedback shift register (NFSR) is the main component of the convolutional decoder. This paper provides a novel method for investigating the driven stability of NFSRs with input via semi-tensor product (STP). By using the STP method, a backward state transition matrix, as well as a backward NFSR, is constructed. Backward NFSRs can help to find the predecessors of any states so that an algorithm for the global stability of autonomous NFSRs is designed. On this basis, two algorithms are proposed for the driven stability of NFSRs with input, and they have lower computational complexity than the existing methods. Meanwhile, some numerical examples are presented to support the results of this paper. Finally, the relationship between stability and connectedness is discussed fully, which derives some interesting results. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of non-fragile guaranteed cost control (GCC) for networked nonlinear Markov jump systems subject to multiple cyber-attacks, which are characterized by Takagi–Sugeno (T–S) fuzzy model with time-varying delay. Specifically, a variety of cyber-attacks, including deception attacks and Denial-of-Service (DoS) attacks, are considered, which occur in the forward and feedback communication links, respectively. To achieve stochastic stability under guaranteed cost function (GCF), the paper proposes a Lyapunov–Krasovskii (L–K) function approach. The approach derives sufficient conditions for stochastic stability, and obtains non-fragile controller gains and the uniform upper bound of the GCF using linear matrix inequalities (LMIs) technique. Finally, the effectiveness of the proposed algorithm is evaluated by simulation experiment. [ABSTRACT FROM AUTHOR]

In this paper, the stabilization is studied for a complex dynamic model which involves nonlinearities, uncertainty, and Lévy noises. This paper also discusses the controller discretization and presents a new algorithm to obtain the upper bound for the sample interval through which the exponential stability of the discrete system can still be guaranteed. Firstly, an integral sliding surface is designed to obtain the sliding mode dynamics for the considered stochastic Lévy process. By using Lyapunov theory, generalized Itô formula and some inequality techniques, the exponential stability is proved in the sense of mean square for sliding mode dynamics. The reachability of the sliding mode surface is also ensured by designing a sliding mode control law. Secondly, the continuous-time controller is discretized from the point of control cost, and the squared difference is analyzed for the states before and after the discretization. Different from those classical stochastic differential equations driven by Brownian motions, the noise is supposed to be Lévy type and the squared difference is analyzed in different cases. Furthermore, we obtain the largest sampling interval through which the discretized controller can still stabilize the Lévy process driven stochastic system. Finally, a simulation for a drill bit system is given to demonstrate the results under the algorithms. [ABSTRACT FROM AUTHOR]

The current parking trajectory planning algorithms based on geometric connections or formulation of optimization problems in automatic parking systems have strict requirements on the starting position, lower planning efficiency and discontinuous curvature of the reference trajectory. In order to solve these problems, a hierarchical planning algorithm which is combined with nonlinear optimization and the improved RRT* algorithm (Rapidly-exploring Random Tree Star) with Reeds-Shepp curve is proposed in this paper. First, the improved RRT*RS algorithm with the rapid repulsion-straddle experiment is designed for enhancing the efficiency of path planning. Second, because of the shortcomings of the Reeds-Shepp curve that can meet the minimum turning radius but not realize the continuous curvature of the path, a nonlinear optimization problem based on convex-set obstacle constraints is formulated and solved. Finally, simulation results show that the proposed parking trajectory planning algorithm in this paper can plan an effective parking trajectory with continuous curvature in different starting positions and multiple parking scenarios. [ABSTRACT FROM AUTHOR]

This paper proposes a matrix-based flipping method for improving the robustness of Boolean networks (BNs). The robustness considered in this paper is to find a flip matrix such that the output of a given BN with the flip matrix is unaffected by disturbances, in which case the output of the given BN is said to be flipping-based robust. Firstly, a necessary and sufficient condition is presented to determine whether the output of a given BN is identity matrix flipping-based robust. Then a novel flipping method based on the Hamming distance is provided to find the flip matrix and realize that the output of a given BN is flipping-based robust. Finally, a biological example is used to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, some techniques are proposed to determine the smallest perturbation that causes the loss of a structural property for a linear system with coefficients depending polynomially on a vector of parameters. In the case that the interest lies on a single structural property, the analysis is carried out using directly the state-space description of the system, whereas, in the case that the interest is to characterize either the pair (reachability and observability) or the pair (stabilizability and detectability), the analysis is carried out using the transfer matrix of the plant. Examples of application of the proposed methods are reported all throughout the paper to illustrate and validate the theoretical results. [ABSTRACT FROM AUTHOR]

This paper focuses on the stability problem and the design method of PI-type H ∞ controller for load frequency control (LFC) of power systems with multiple time-varying delays (MTD). In the existing researches, the model of LFC system with time delays is not accurate enough since it is established based on the assumption that the time delays are all the same. This paper proposes a novel model of multi-area LFC system with MTD. Both the stability analysis and controller design in this paper are based on the improved model to ensure the applicability of the proposed method in general. First, a novel Lyapunov-Krasovskii functional (LKF) containing delay-product-type term (DPT) is constructed and auxiliary function-based integral inequality (AFBII) is utilized to handle the integral term of the derivative of LKF. Then, an improved reciprocally convex inequality is proposed to obtain the less conservative stability criteria in terms of linear matrix inequalities (LMIs). Next, an effective H ∞ controller design method is developed based on the proposed stability criteria. Finally, simulation experiments are done to illustrate the superiority of proposed criteria and effectiveness of proposed design method. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of controlling a wave energy converter (WEC) susceptible to faults in its braking subsystems, characterized through nonlinear damping. By considering the necessity of robust trajectory tracking related to the sea waves for maximizing the converted energy, one aims to preserve such a trajectory in the presence of faults to avoid physical damage in the structure of the WEC. To achieve this objective, this paper proposes a fault-tolerant control (FTC) that combines two systems: (i) a novel nonlinear servocompensator (NSC) and (ii) a fault diagnosis subsystem (FD). The NSC is based on a variable structure control that generalizes the internal model principle for robust tracking. The reference signal is computed from real-time measurements of the irregular sea waves. The FD subsystem estimates the faults related to the wear of the brakes via an unknown input observer. Due to its independent performance from the FD, the global scheme can be considered as a passive FTC. By considering the faulty model of a WEC based on the Archimedes wave swing prototype, theoretical formulation and the convergence proof are given for the NSC and the FD. The performance of the proposed design is verified with numerical simulations of the WEC with the incidence of irregular sea waves under different fault scenarios in the upper and lower brakes. [ABSTRACT FROM AUTHOR]

In this paper, the measurement outlier-resistant target tracking problem is investigated in wireless sensor networks (WSNs) with energy harvesting constraints. Each WSN node can acquire energy stochastically from surroundings. No matter whether the WSN node acquires energy or not, the WSN node's measurement can be transmitted if the energy amount of the WSN node is greater than zero. In such a case, the sensor energy-induced missing measurement (SE-IMM) phenomenon may occur. The objective of this paper is to develop a solution for the considered target tracking problem by devising the filter including a saturation constraint such that, in the simultaneous presence of outliers and the SE-IMM phenomenon, the tracking performance can meet the given performance index. Firstly, the relation between the energy level of the WSN node and its probability distribution is computed recursively. Then, an upper bound of the tracking error covariance is derived which is minimized by appropriately choosing the filter parameter. Finally, the feasibility of the proposed target tracking scheme is validated by conducting a set of comparative experiments and the relationship between the energy of the WSN node and the tracking performance is also disclosed. [ABSTRACT FROM AUTHOR]

The study aims to solve the problem of real time tracking and precise landing of unmanned aerial vehicle (UAV) during unmanned surface vehicle (USV) navigation. In this paper, a UAV-USV cooperative tracking and landing control strategy based on nonlinear model predictive control (NMPC) is proposed. Firstly, the UAV-USV heterogeneous intelligent body collaborative system is constructed based on the mathematical model of UAV and USV; secondly, the tracking controller is designed based on NMPC algorithm to ensure that the UAV can track the USV in real time; finally, a UAV-USV cooperative landing control strategy is proposed to realize the heave motion of the USV to the peak vertex, thus, the UAV completes the precise landing with the minimum impact. As the simulation experimental results show, the UAV-USV cooperative tracking and landing control scheme proposed in this paper can provide effective solution against real time tracking and accurate landing of UAV during the navigation of USV. [ABSTRACT FROM AUTHOR]

This paper presents a decentralized navigation method with a leader robot guiding a robotic swarm and considers the possible occurrence of a failure. Multi-robot systems have attracted attention in part because they can maintain their performance as a swarm even when some robots fail. Such systems are also expected to work well in environments where a disaster has occurred, given that the chance of robot crashes is high in such situations. Therefore, it is important to design a navigation method that considers the possibility of failures so that the surviving robots in a swarm will not be impaired because of failed robots. In this paper, we design connectivity maintenance and a repair method for swarm robots in which each robot utilizes only local information. We then prove that the proposed method ensures the swarm follows the movement of a leader robot and reconstructs connectivity in the case one of the robots fails. Finally, we present experimental and numerical results confirming the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we consider the discrete memory-less three-way degraded broadcast channel (3WDBC). The main contribution of this paper is in characterizing the capacity region of the discrete memoryless 3WDBC. To end up with this goal, we first develop the achievable region. Then, an outer bound to the capacity region is also derived. Next, the achievable region is shown to meet the outer bound such that the capacity is achieved. After that, the 3WDBC is shown to encompass many well-known multi-user networks such as (i) broadcast channel, (ii) multiple access channel, (iii) two-way channel, and (iv) relay channel. Further, the achievable capacity region is then extended to the additive Gaussian noise channel. Specifically, superposition encoding is employed at each user such that a given user can appropriately allocate its power to broadcast to the other two users. In this direction, two design criteria are theoretically presented and numerically investigated to show the range that the power allocation factor at each user may have. [ABSTRACT FROM AUTHOR]

This paper investigates the prescribed-time containment control problem for multi-agent systems with high-order nonlinear dynamics under a directed communication topology. Firstly, in view of the fact that only some follower agents can directly access the state information of multiple leader agents, a prescribed-time distributed observer is put forward to estimate the convex hull spanned by these leaders. Then, with the help of the distributed observer, a novel containment control method is developed for each follower based on a time-varying scaling function, so that all followers can converge to the convex hull spanned by the states of multiple leaders within a prescribed time. The comparison with the finite-time and fixed-time control methods differs in that the convergence time of the method proposed in this paper is independent of the initial conditions and control parameters and can be arbitrarily preassigned according to actual needs. Finally, an example is given to demonstrate the usefulness of the prescribed-time containment control method. [ABSTRACT FROM AUTHOR]

In this paper, the finite-time control and bumpless transfer control are investigated for switched systems under asynchronously switching. First, a class of dynamic output feedback controllers are designed to stabilize the switched system with measurable system outputs. Considering the improvement of transient performance, the bumpless transfer control and finite-time control are further studied in the controller design. To avoid the control bumps, a practical filter is introduced to make the control signal smoother and continuous. Furthermore, to derive a finite-time bounded system state over short-time intervals, the finite-time analysis is considered in managing the switching process with the average dwell time. New criteria are proposed to analyze the finite-time stability and finite-time boundedness for the closed-loop system and solvable conditions are newly proposed to optimize the controller gain. Finally, the superiorities of the proposed method are validated through an application to a boost converter. [ABSTRACT FROM AUTHOR]