This article proposes a local input-to-state stability (LISS) analysis as a practical stability analysis approach. In existing LISS analysis approaches, a region including a state trajectory is not specified, and the decrement of a Lyapunov function must be guaranteed in the entire domain of the system state. This reduces the advantage of LISS by limiting the state region, and limits the class of systems

In this article, we investigate the stabilization control problem of a flexible marine riser system with a failed and bounded control action and time-varying boundary constraints. The considered system is modeled as a distributed parameter system dominated by a partial differential equation. The involved problems are extended to some more general conditions. The saturation and failures of the actuator

Solving nonlinear model predictive control problems in real time is still an important challenge despite of recent advances in computing hardware, optimization algorithms and tailored implementations. This challenge is even greater when uncertainty is present due to disturbances, unknown parameters or measurement and estimation errors. To enable the application of advanced control schemes to fast systems

Careful timing of nonpharmaceutical interventions such as social distancing may avoid high “second waves” of infections of COVID-19. This article asks what should be the timing of a set of K complete-lockdowns of prespecified lengths (such as two weeks) so as to minimize the peak of the infective compartment. Perhaps surprisingly, it is possible to give an explicit and easily computable rule for when

In this article we consider the -stabilization of nth-order linear time-invariant dynamical systems using multiplicity-induced-dominancy-based controller design in the presence of delays in the input or the output channels. A sufficient condition is given for the dominancy of a real root with multiplicity at least and at least n using an integral factorization of the corresponding characteristic function

This article focuses on the identification of switched nonlinear systems, which are characterized as a collection of nonlinear dynamical systems. Each nonlinear subsystem is activated by a discrete-valued variable (switching signal). Specifically, we consider the continuous-time switched nonlinear systems in the state-space form in our article. The identification of switched nonlinear systems amounts

This article investigates the robust fault tolerant control strategy for a rigid satellite attitude system with external disturbance and actuator fault while the predesigned output constraint is taken into consideration. Based on the interval observer technique, an identical faulty signal reconstruction is first realized by utilizing pure mathematical calculation. Then, to guarantee the desired output

This article involves an adaptive robust barrier-based control of a three-dimensional riser system subject to system uncertainties and output constraints. A barrier-based Lyapunov function and a dynamical online update technique are merged to develop new adaptive robust control schemes for dampening the vibration, compensating for parametric uncertainties, and dealing with the constraints in the system

The support vector machine has been widely used in binary classification applications because of the simplicity of its implementation. This article proposes an online identification method based on the support vector machine in the field of parameter identification. By substituting the constraint item into the original criterion function to form a new criterion function about the weight vector and

This article concerns the output feedback tracking control problem for a class of single-input-single-output (SISO) nonlinear systems in a semistrict feedback form, which possesses both matched and mismatched uncertainties, including parametric uncertainties and unknown nonlinear disturbances. An active disturbance rejection adaptive output feedback control scheme is proposed via backstepping method

In this article, an event-triggered adaptive tracking control scheme is proposed for uncertain nonlinear systems with the predefined time-varying output constraint requirements by using barrier Lyapunov function (BLF) method. One of the significant novelties in the proposed design procedure is that the event-triggered control strategy is first designed jointly with nonlinear systems under the predefined

This article is concerned with the issue of event-triggered based adaptive tracking control for a class of nonlinear uncertain system with input hysteresis. The radial basis function of neural networks (RBFNNs) is utilized to compensate the uncertain parts, where approximation errors are combined into the approximation system. Then, consider such method may extend the developed the weight vector of

This article addresses the parametric identification of block-structured nonlinear systems in a general form, characterized by the feedback interconnection of a multivariable linear system and a static multivariate nonlinear map. We assume that both the input and the output collected data are affected by bounded noise, which casts the problem in the context of set-membership (SM) errors-in-variables

While model predictive control (MPC) methods have proven their efficacy when applied to systems with safety specifications and physical limitations, their performance heavily relies on an accurate prediction model. As a consequence, a significant effort in the design of MPC controllers is dedicated to the modeling part and often requires advanced physical expertise. In order to facilitate the controller

This paper is intended to investigate the problem of event-triggered feedback control for time-varying delays singular jump systems based on sampled observer and exponential detector. By virtue of the designed event-triggered control strategies, the state estimate signals are transmitted to the controller under the networked communication environment and aperiodic sampling scheme. The driving threshold

In this article, a new nonsmooth Kalman filtering (KF) method is proposed for noise suppression of the compound sandwich with backlash and dead zone. Based on the characteristics of the system, a nonsmooth stochastic state-space equation is constructed. Then, nonsmooth KF is developed to adapt the nonsmooth stochastic state space model. The filter can switch automatically among different operating

In this article, a novel sensitivity minimization approach is proposed to optimize the performance of proportional-integral (PI) dynamic average consensus (DAC) algorithms subject to measurement noises and model uncertainties. Network sensitivity and complementary sensitivity functions are defined to characterize the effects of the reference signals and measurement noises on the tracking error, respectively

We study the application of a data-enabled predictive control (DeePC) algorithm for position control of real-world nano-quadcopters. The DeePC algorithm is a finite-horizon, optimal control method that uses input/output measurements from the system to predict future trajectories without the need for system identification or state estimation. The algorithm predicts future trajectories of the quadcopter

In this work, an adaptive iterative learning control (AILC) method is designed for a class of parametric discrete-time nonlinear systems with random initial condition, unknown time-varying input gain and multiple time-iteration-varying factors including multiple unknown time-iteration-varying parameters and unknown time-iteration-varying external disturbance. The iteration-varying factors can be generated

This article is intended to deal with the problem of asynchronous admissibility and fault detection (FD) for time-varying delay implicit Markovian switching systems (IMSSs) under hidden Markovian model (HMM) mechanism. The fundamental purpose is to design asynchronous FD filter such that the implicit Markovian switching residual system is stochastically admissible (including regular, impulse-free,

The problem of resilient control of linear cyber-physical systems with cyber-attacked sensor measurements and actuator commands is studied in this article. Online reconstruction of unknown cyber-attacks is accomplished by an adaptive sliding mode observer with a novel injection term in the form of a dynamically extended equivalent control. Then, the attacked/corrupted sensor's measurements and the

In this article, an event-triggered constrained optimal tracking control algorithm using integral reinforcement learning (IRL) is developed. First, the constrained optimal tracking control problem is transformed into an optimal regulation problem by employing an augmented system with a discounted value function. Then, IRL is introduced to solve the Hamilton-Jacobi-Bellman equation, where the drift

This paper presents an output-feedback repetitive control method for a class of systems with nonlinearities, unknown state-dependent uncertainties, and external disturbances. An additive-state-decomposition approach is used to decompose the system under study into a primary linear periodic system in charge of repetitive-control tracking task and a secondary linearized system in charge of robustly stabilization

This article designs an optimal observer-based output feedback control for traffic breakdown to dissolve traffic congestion using the backstepping method and optimization. The linearized Aw–Rascle–Zhang model is used to represent the congested traffic dynamics resulting from traffic breakdown. Based on the factors leading to traffic breakdown, we take into account the boundary conditions consisting

Proportional–integral–derivative (PID) control is the most widely used in industrial control, robot control, and other fields. However, traditional PID control is not competent when the system cannot be accurately modeled and the operating environment is variable in real time. To tackle these problems, we propose a self-adaptive model-free SAC-PID control approach based on reinforcement learning for

This paper studies the optimal event-triggered control for constrained-input discrete-time switched nonlinear systems. Firstly, the optimal time-triggered control problem is analyzed based on the necessary optimality condition. Secondly, the optimal event-triggered control problem is presented, and the optimal results are presented based on the periodic time-triggered ones, and an event-triggered integer-mixed

Recent developments in quantitative feedback theory (QFT) lead to feedforward design problems with both magnitude and phase constraints. In these cases, manual feedforward tuning becomes much more challenging and time consuming than the traditional prefilter shaping taking place on the Bode plot. This article presents a general procedure for the automatic synthesis of such elements. Feedforward bounds

In this paper, an event-triggered adaptive neural output feedback control scheme is developed for a class of uncertain discrete-time strict-feedback nonlinear systems subject to immeasurable system states and network resource limitation. An i-step ahead predictor is synthesized to obtain the future signal of the reference orbit. By combining the neural observer and the variable substitution technology

In this article, the problem of output-feedback stabilization for a class of stochastic high-order nonlinear systems with stochastic inverse dynamics and multidelay is studied. In the control scheme, an output-feedback controller with a reduced-order observer is designed to globally stabilize the whole system. Different from the classical literature on stochastic upper-triangular systems, a high-gain-based

In this paper, a new value iteration (VI) based method is proposed to solve the H∞ control problem of continuous-time linear systems. The problem is transformed into solving a nonlinear differential equation, and the local stability of its solution is proved. Then a VI based iteration scheme for getting the approximation of the H∞ optimal controller is proposed. Compared with the existing results,

This article focus on the finite-time control for a class of stochastic continuous nonlinear systems suffered from unknown control coefficients and unmeasured stochastic inverse dynamics. Based on the modified homogeneous domination and adding a power integrator approach, the finite-time controller is constructed to assure the global finite-time stability in probability of stochastic continuous nonlinear

In this paper, a stabilization scheme for a class of continuous-time nonlinear Markov jump systems is investigated by sampled-data control mechanism. This stabilization scheme is given in the form of a discrete-time state feedback controller which is designed based on the approximate discrete-time model (ADTM) of the original continuous-time system via the discrete-time design method. During the process

This article is concerned with robust stability for linear impulsive delay systems with polytope uncertainties. For the linear impulsive delay systems without uncertainties, the stability is addressed by employing a Lyapunov-Krasovskii-like functional, which is comprised of a Lyapunov-Krasovskii functional and an auxiliary functional. By introducing integrals of the state, an augmented Lyapunov-Krasovskii-like

In this article, passivity-based sampled-data control for Markovian jump systems (MJSs) with stochastic sampling is conducted by virtue of the looped-functional approach. First, based on the input delay approach, the MJS under stochastic sampled-data control is modeled as a time-varying continuous-time system with a random variable. Second, a time-dependent looped-functional is developed, which only

This article studies the trajectory tracking of nonholonomic mobile robots by using geometric control methods, with extension to consensus tracking and formation tracking. Different from the system model given in the Euclidean space, we establish the dynamics of mobile robots on the tangent bundle of the Lie group, which is a global and unique description independent of local coordinates. Firstly,

In this paper, the finite-time asymmetric bipartite consensus problem of multi-agent systems with signed digraph is considered. Firstly, an asymmetric index is introduced to describe a desired output relationship of the agents in terms of quantity. Based on the information of the agent's communication and the index, a novel iterative learning control protocol is proposed. By establishing the input

In this article, we considered the fixed-time stability (FXT) of a type of discontinuous dynamical system. First, we introduced some new FXT stability results via variable substitutions and using inequality techniques, which are more accurately estimate the upper bound of settling time (ST). Then, based on the established results and using the differential inclusion theory, we investigated the FXT

For industrial batch processes subject to time-varying uncertainties and nonrepetitive disturbances, this article proposes a robust static output feedback (SOF) based iterative learning control (ILC) design with a finite-frequency-range two-dimensional (2D) performance specification. An important advantage of the proposed design lies in its simple structure and easy implementation, with no need to

Sampled-data output consensus problem has been firstly considered within co-design framework where control gains and sampling periods are incorporated together. In construction of co-designed controllers, we firstly introduce a scaled coordinate transformation for the original system in the continuous-time domain. Then design of sampled-data controllers with absolute/relative damping and stability

This paper considers the performance-guaranteed event-triggered adaptive asymptotic tracking control problem for nonstrict feedback nonlinear systems with uncertain external disturbances. More precisely, the upper bounds of control gain function in stability analysis are eliminated by establishing Lyapunov function with lower bounds of control coefficients. Compared with the previous guaranteed performance

This article presents an event-triggered approach to security control for networked systems by using hybrid attack model. Stochastic deception attacks, replay attacks, and denial of service attacks are assumed to occur in the communication network. The main contribution of the article is that an event-triggered control strategy is presented to stabilize the networked systems based on the hybrid attacks

This paper investigates the stability of a linear finite-dimensional system interconnected to a single delay operator. From robust approaches, to derive delay-dependent frequency tests, a characterization of the delay behavior is required. Based on approximation methods, one describes the transported signal by lumped parameters. More precisely, by the use of the first Fourier–Legendre polynomials coefficients

A novel quantization-based switched second-order sliding mode control design is considered for nonlinear uncertain systems. A new quantization strategy associated with state-space partition is utilized to accommodate the control amplitude to different uncertainty levels then the conservatism of the control gain is thus attenuated. Investigating each quantized region, it is obtained that all regions

This article studies output sign-consensus of heterogeneous multiagent systems, that is, outputs of all agents will eventually have the same sign. Both fixed and switching signed graphs are treated. To remove the restriction that every follower node needs to know the dynamics of the leader node, a distributed observer is maintained by each follower node, such that the state and dynamics of the leader

This paper presents a novel practical fixed-time parameter identification algorithm and a composite learning based practical fixed-time adaptive dynamic surface control (DSC) scheme for nonlinear strict-feedback systems subject to linear-in-parameters uncertainties. The convergence of conventional parameter estimation algorithms often requires a restrictive prerequisite termed persistent excitation

This paper investigates the problem of designing a decentralized static output feedback control for a class of large-scale interconnected discrete-time systems with quantized signals and time-varying actuator faults wherein the control input is quantized by means of logarithmic quantizer to avoid chattering. Based on Lyapunov stability theory together with the improved reciprocally convex approach

This article presents a new event-triggering based design of sliding mode control (SMC) for the control of a dynamical system against external perturbations. This triggering mechanism aims to generate a sparser sampling pattern than the existing one while achieving the minimum resource utilization. The triggering mechanism employs scalar dynamics, hence it is called the dynamic event-triggering mechanism

This study is systematically devoted to the problem of dynamic output feedback control for bipartite consensus of multiagent systems in the presence of Markov switching topologies. The main purpose of this study is to develop a dynamic output feedback controller with gain fluctuations such that the considered multiagent system achieves bipartite consensus. Notably, the interaction among agents of the

This article mainly deals with observer-based H∞ control problem for a stochastic Korteweg–de Vries–Burgers equation under point or averaged measurements. Due to the nonlinearity of the stochastic partial differential equations, special emphases are given to computation complexity. By constructing an appropriate Lyapunov functional, we derive sufficient conditions in terms of linear matrix inequalities

Spatially interconnected systems (SISs) are formed by a chain of subsystems or units with the same or similar structure, all of which directly interact with their neighbors. For robust tracking of SISs subject to both polytopic uncertainty and external disturbances, a PD-type iterative learning control (ILC) algorithm integrated with real-time output feedback is proposed in the absence of accurate

For solving the additive and multiplicative sensor faults in the constrained system with unknown but bounded noise, the constrained zonotopic Kalman filter-based additive sensor fault estimator and multiplicative sensor fault estimator are designed, respectively. In the fault estimation process, the states of the system are contained in the zonotopic sets estimated by the constrained zonotopic Kalman

This article investigates the parameter estimation problems of Hammerstein-Wiener nonlinear systems with non-uniform sampling. The over-parameterization identification model for the Hammerstein-Wiener nonlinear systems is established from the non-uniformly sampled input-output data. By applying the gradient search principle, we derive an over-parameterization forgetting factor stochastic gradient algorithm

The present manuscript addresses the problem of designing a procedure for constructing the null controllable Region (the set of states from where stabilization is achievable subject to constraints). To this end, a controllability minimum principle based computationally tractable approach for constructing the null controllable region is presented. Simulation results are used to illustrate the computation

In this paper, an adaptive output feedback tracking for a class of uncertain nonlinear systems with input and output quantization is investigated. A new controller structure is introduced in which a modified output quantizer is proposed so that its first-order derivative exists, and an observer is designed with quantized input and output as its input signals. Then, with dynamic surface control as a

The sliding mode control (SMC) problem for a class of discrete-time networked switched systems under the coding-decoding communication protocol (CDCP) is studied in this note. In the networked control systems, the CDCP is adopted to improve the efficiency and security of data transmission. First, based on the uniform quantization method, the criteria to ensure the detectability of the system are given

This article proposes a hybrid search (involving the performance level and a positive scalar variable in sequence) based method for synthesis of linear time-invariant (LTI) static output feedback (SOF) controllers for a class of linear systems with norm-bounded time-varying parametric uncertainties. Using an available extended linear matrix inequality (LMI) formulation of bounded real lemma, a new

In the paper under consideration,1 Remark 6 should be corrected as follows. Equation (99) must be replaced with (106) The term in (101), (102), and (104) must be replaced with (107) which is similar to the matrix found in previous work.2 Accordingly, is defined as (108) where and correspond to the first lines of matrix , and , are additional matrix variables. The authors apologize for the mistakes

For linear parameter varying (LPV) systems with unknown system states, this article investigates an interval state estimation-based robust model predictive control algorithm. Two interval state estimation approaches, including interval observer systems and zonotope-based box computations, are considered to estimate the upper and lower bounds of system states. The on-line interval estimation error boxes

This article investigates the delay-dependent stability and stabilization problems for stochastic time-delay systems (STDSs) governed by the Poisson process and Brownian motion. First, this article exploits the decomposition of semimartingale to transform STDSs governed by the Poisson process and Brownian motion into STDSs governed by martingales, and then one can use effective properties and tools

This study aims to investigate the problem of event-triggered adaptive leaderless consensus control for a class of nonlinear multi-agent systems with unknown backlash-like hysteresis. Combining adaptive backstepping and event-triggered control techniques, a distributed event-triggered adaptive leaderless consensus controller is designed to compensate for the effects of unknown backlash-like hysteresis