This article is concerned with the reliable H ∞ control problem against actuator failures for discrete two‐dimensional (2‐D) switched systems with state delays and actuator faults described by the second Fornasini‐Marchesini (FM) state‐space model. By resorting to the average dwell time (ADT) approach, also by constructing an appropriate Lyapunov‐Krasovskii functional and using the Wirtinger inequality

An integrated fault estimation/fault‐tolerant control (FTC) scheme is developed in this article for nonlinear Lipschitz systems in the presence of external disturbances and actuator failures. To address this problem, coupled uncertainties between the observer error dynamics and the control system are considered, which is conveniently ignored in control approaches based on the separation principle.

We present a Newton‐based extremum seeking algorithm for maximizing higher derivatives of unknown maps in the presence of time‐varying delays. Dealing with time‐varying delays has impact in the predictor design in terms of the transport PDE with variable convection speed functions, the backstepping transformation as well as the conditions imposed on the delay. First, the delay can grow at a rate strictly

This article considers the design of interval functional observers to estimate a linear function of the state vector of time‐delay systems subject to both input and output additive disturbances. Two novel functional observers are proposed and designed such that they bound the set of all admissible values of a linear function of the state vector at each instant of time. By contrast to interval observers

In this paper, we consider a global regulation problem for a class of feedforward nonlinear systems. The key features of our considered system are identified by the presence of uncertain time‐varying parameters associated with main diagonal states and input and an unknown time‐varying delay in the input. Moreover, the growth rates of nonlinearity and the input‐delay are only known to be finite. To

This article concentrates on an adaptive finite‐time fault‐tolerant fuzzy tracking control problem for nonstrict feedback nonlinear systems with input quantization and full‐state constraints. By utilizing the fuzzy logic systems and less adjustable parameters method, the unknown nonlinear functions are addressed in each step process. In addition, a dynamic surface control technique combined with fuzzy

In this article, an observer‐based adaptive boundary iterative learning control law is developed for a class of two‐link rigid‐flexible manipulator with input backlash, the unknown external disturbance, and the endpoint constraint. To tackle the backlash nonlinearities and ensure the vibration suppression, the disturbance observers based upon the iterative learning conception are considered in the

This study investigates the consensus problem of multiple 3‐DOF laboratory helicopters modeled with system nonlinearity, uncertainty, and actuator faults. The simultaneous additives and partial loss of effectiveness actuator faults are considered. The fault detection hierarchy, the healthy control hierarchy, and the fault‐tolerant control hierarchy constitute the hierarchical structure of multihelicopter

This article is concerned about an adaptive dynamic surface control (DSC) of output constrained stochastic nonlinear systems with unknown control directions and unmodeled dynamics. Nonlinear mapping‐based backstepping control design is presented for stochastic nonlinear systems with output constraint. The explosion of complexity exists in tradition backstepping method is avoided by using the DSC technique

This article deals with the problem of robust output feedback control design for a class of switched systems with uncertainties and random time‐varying delay. Our purpose is focused on designing a full order dynamic output feedback controller and an appropriate switching rule to ensure the exponential mean square stability of the resulting closed‐loop switching system with an l 2−l ∞ performance level

This article studies the high angle of attack (AOA) maneuver control based on an improved prescribed performance method, that is, switched prescribed performance control (SPP). Different from traditional prescribed performance control, multiple performance functions are considered in the SPP, which can appropriately adjust the output performance constraints. Furthermore, based on the SPP, an adjustable

Fault detection and diagnosis (FDD) plays an essential role in identifying and isolating various faults in a system. In general, fault detection is attained by monitoring the extent of matching between the actual operating condition and an analytical model prediction. This process aids in achieving enhanced performance, and for operating the system within the acceptable bounds. In this article, a neural

The article addresses the problem of nonlinear system identification with particular focusing on Wiener models. The proposed input injection methodology allows for identification of a working system—without stopping its usual operation, production processes, and so on. The only interferences are the slight random injections added to the input signal, which—by assumption—do not disturb the overall system's

In this article, we investigate the dynamical behavior of a class of delayed fuzzy Cohen‐Grossberg neural networks (FCGNNs) with discontinuous activation functions subject to time delays and fuzzy terms. By using the inequality analysis technique and the M‐matrix theory, sufficient and proper conditions are given in order to establish the existence, convergence, and global exponential stability of

This article develops the modified extended Kalman filter based recursive estimation algorithms for Wiener nonlinear systems with process noise and measurement noise. The prior estimate of the linear block output is computed based on the auxiliary model, and the posterior estimate is updated by designing a modified extended Kalman filter. A multi‐innovation gradient algorithm and a recursive least

In this article, we consider extremum seeking problems for a general class of nonlinear dynamic control systems. The main result of the article is a broad family of control laws which optimize the steady‐state performance of the system. We prove practical asymptotic stability of the optimal steady‐state and, moreover, propose sufficient conditions for the asymptotic stability in the sense of Lyapunov

In this article, a novel fuzzy adaptive finite‐time nonsmooth controller is developed to handle the finite‐time tracking problem for a class of uncertain nonlinear systems. Different from traditional fuzzy adaptive approximation methods, proposed method contains only one adaptive parameter, no matter how many states there are in the system. By constructing a new Lyapunov function with prescribed performance

This article studies the adaptive model predictive control with extended state observers (ESO) to deal with multiple unmanned aerial vehicles formation flight in presence of external disturbances and system uncertainties. Specifically, to deal with the mismatch of predictive model caused by external disturbances and system uncertainties, ESOs are introduced to estimate the lumped disturbances, where

This paper considers the position and attitude tracking control of a quadrotor with inertia parameter uncertainty. With the aid of the cascade structure of the dynamics of the system, an immersion and invariance observer is proposed to estimate the unknown mass of the system first. Secondly, a saturation controller is designed for the thrust force. Thirdly, a virtual controller is proposed for the

Discrete‐time adaptive control algorithms can be executed directly in embedded code unlike their continuous‐time counterparts, which require discretization. However, their designs predicated on quadratic Lyapunov‐based frameworks are quite intricate due to the resulting complexity in the Lyapunov difference expressions. Therefore, a wide array of available continuous‐time results addressing transient

This article investigates an adaptive fuzzy tracking control problem for a class of nontriangular form systems with asymmetric time‐varying full state constraints. Unknown functions are approximated by the fuzzy logic systems. A domination approach is employed to tackle the nontriangular form structure. Time‐varying asymmetric barrier Lyapunov functions (ABLFs) are adopted to ensure full‐state constraints

This article proposes an extremum‐seeking control design that achieves finite‐time stability of the optimum of an unknown measured cost function. The finite‐time extremum‐seeking control technique is shown to achieve finite‐time practical stability of the optimum of the cost function. The main characteristic of the proposed extremum seeking control approach is that the corresponding target averaged

A filtered adaptive constrained sampled‐data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation

The special issue presents results of the current research on moving horizon estimation for linear and nonlinear systems. The special issue includes six papers with two main types of contributions, that is, those with new theoretical developments and those focused on practical applications such as fault diagnosis, outlier accommodation, and field monitoring. Notably, these two types of contribution

This article introduces a new nonlinear observer for state estimation of linear time invariant systems. The proposed observer contains a (nonlinear) cubic term to enhance observer response. Unlike previously proposed observers, the cubic observer has nonlinear estimation error dynamics. Convergence criteria, performance advantages, and observer‐based feedback control with cubic observers are addressed

We present a generalization of the scalar gradient extremum seeking (ES) algorithm, which maximizes static maps in the presence of infinite‐dimensional dynamics described by parabolic partial differential equations (PDEs). The PDE dynamics contains reaction‐advection‐diffusion (RAD) like terms. Basically, the effects of the PDE dynamics in the additive dither signals are canceled out using the trajectory

Single trial estimation of event‐related potential (ERP) components is an open research topic in neuroscience. In this article, we have proposed a method to improve the performance of spatiotemporal filtering by decreasing its dependency to prior estimates of ERP components. For this purpose, we have used a mixture of Gaussian kernels instead of a raw prior signal, and the parameters of the Gaussian

This article is concerned with the parameter identification problem of nonlinear dynamic responses for the linear time‐invariant system by means of an impulse excitation signal and discrete observation data. Using the impulse signal as the input, the impulse response experiment is carried out and the dynamical moving sampling is designed to generate the measured data for deriving new identification

A stochastic average gradient (SAG) algorithm is proposed for multirate (MR) finite impulse response (FIR) models with varying time delays in this article. The time delays at each sampling instant are computed through the self‐organizing maps technique, and then the parameters are estimated by using the SAG algorithm. Considering that the SAG algorithm updates the parameters using all the directions

Conventional closed‐form solution to the optimal control problem using optimal control theory is only available under the assumption that there are known system dynamics/models described as differential equations. Without such models, reinforcement learning (RL) as a candidate technique has been successfully applied to iteratively solve the optimal control problem for unknown or varying systems. For

This article addresses the passivity analysis and asynchronous feedback passification problems for a class of discrete‐time switched systems with dwell time constraint. By exploiting dwell time‐dependent storage functions, a state‐dependent switching strategy obeying a dwell time constraint is constructed, and the solvability conditions for asynchronous feedback passification are developed in the form

In this article, the analysis and design problems of H∞ filtering for a class of discrete‐time switched singular systems with time‐varying delay under an arbitrary switching signal are investigated. The main attention is focused on the design of a linear mode‐dependent filter guaranteeing the regularity, causality, and asymptotic stability of the resulting filtering error system with a prescribed H∞

This article investigates the sensor attack detection and isolation problems for cyber‐physical systems under attacked situation. To begin with, an overall system is constructed for the network of dynamic system and all the issues are dealt with for the overall system instead of every subsystem. Then, we prove that the preconditions which are made on the original subsystem can be transferred on to

This article studies control and performance enforcement for a class of uncertain dynamical systems that consist of actuated and unactuated portions physically interconnected to each other. The proposed approach stabilizes the overall interconnected system in the presence of unknown physical interconnections as well as system uncertainties. Performance guarantees are enforced, individually, on the

This paper is concerned with distributed data‐driven observer design problem. The existing data‐driven observers rely on a common assumption that all the information about the system, and the calculations based upon this information are centralized. Therefore the resulting algorithms cannot be applied to the distributed systems in which each local observer receives only a part of the output signal

In this study, an adaptive output feedback control with prescribed performance is proposed for unknown pure feedback nonlinear systems with external disturbances and unmeasured states. A novel prescribed performance function is developed and incorporated into an output error transformation to achieve tracking control with prescribed performance. To handle the unknown non‐affine nonlinearities and avoid

In this work, a fuzzy adaptive two‐bits‐triggered control is investigated for the nonlinear uncertain systems with input saturation and output constraint. The considered systems are more widespread. Without sufficient transmission resources, how to resolve the constraint issues while guarantee the control performance is difficult and challenging. Then, hyperbolic tangent function and barrier Lyapunov

This article investigates the issue of adaptive finite‐time tracking control for a category of output‐constrained nonlinear systems in a non‐strict‐feedback form. First, by utilizing the structural characteristics of radial basis function neural networks (RBF NNs), a backstepping design method is extended from strict‐feedback systems to a kind of more general systems, and NNs are employed to approximate

The problem of real‐time frequency estimation of nonstationary multi‐harmonic signals is important in many applications. In this paper, we propose a novel multi‐frequency tracker based on a state‐space representation of the signal with Cartesian filters and the second‐order central divided difference filter (CDDF), which improves the performance of the extended Kalman filter (EKF) by using Stirling's

A class of discrete‐time random processes arising in engineering and econometrics applications consists of a linear state‐space model whose parameters are modulated by the state of a finite‐state Markov chain. Typical filtering approaches are collapsing methods, which approximate filtered distributions by mixtures of Gaussians, each Gaussian corresponding to one possibility of the recent history of

This article focuses on the consensus problem of leader‐following fractional‐order multi‐agent systems (MASs) with general linear and Lipschitz nonlinear dynamics. First, the distributed adaptive protocols for linear and nonlinear fractional‐order MASs are constructed, respectively. We allow the control coupling gains to be time varying for each agent. Moreover, the adaptive modification schemes for

An observer‐based adaptive fuzzy backstepping approach is proposed for nonlinear systems with respect to fractional‐order differential equations, unmatched uncertainties, unmeasured states, and actuator faults. The approximation capability of fuzzy logic system and minimal learning parameter approaches are applied to identify uncertain functions in a simultaneous manner. For estimating the unavailable

In this article, the problem of asynchronous adaptive dynamic output feedback sliding mode control (SMC) for a class of Takagi‐Sugeno (T‐S) fuzzy Markovian jump systems (MJSs) with actuator faults is investigated. The asynchronous dynamic output feedback control strategy is employed, as the nonsynchronization phenomenon of jump modes exists between the plant and the controller. A novel asynchronous

Heterogeneous sensor networks (HSN) find a wide range of applications in the field of military and civilian environments, where sensor nodes are utilized to estimate the position of a target with both dynamics and control input being unknown for the purposes of tracking. In the HSN, nodes are considered active depending upon their ability to sense the target output while the others are taken passive

An electrocardiogram (ECG) signal is a record of the electrical activities of heart muscle and is used clinically to diagnose heart diseases. An ECG signal should be presented as clear as possible to support accurate decisions made by doctors. This article proposes different combinations of combined adaptive algorithms to derive different noise‐cancelling structures to remove (denoise) different kinds

In this article, an adaptive algorithm is proposed for online velocity estimation of the autonomous mobile robots (AMRs) without positioning data received from a Global Positioning System (GPS) module or other means for odometry. Unlike the popular Kalman and particle filters that use the measurements on vectors of global (or local) position and acceleration of a mobile robot, the proposed adaptive

This study outlines the problem of active fault‐tolerant control for delayed discrete‐time switched systems. Using switched proportional‐integral observer and multiple Lyapunov‐Krasovski function, less conservative sufficient conditions are established to design a robust fault estimation (FE) algorithm via linear matrix inequality form. Afterward, a fault‐tolerant performance is realized based on this

This article considers the identification problem of the jump Markov autoregressive exogenous (JMARX) systems with unknown invariant time‐delay under the framework of recursive expectation‐maximization (REM) algorithm. In this article, a recursive Q‐function is formulated for the JMARX systems, based on which the recursive sufficient statistics are obtained. Then, the parameter vectors, variance, transition

This article addresses the combined estimation issues of parameters and states for multivariable systems in the state‐space form disturbed by colored noises. By utilizing the Kalman filtering principle and the coupling identification concept, we derive a Kalman filtering based partially coupled recursive generalized extended least squares (KF‐PC‐RGELS) algorithm to jointly estimate the parameters and

This article studies the robust adaptive tracking control problem of nontriangular nonlinear systems that are affected by multiple state delays rather than the input‐delay. Different from the related studies, the considered systems involve input dead‐zone and various uncertainties arising in the control coefficients, structure parameters, time delays, and disturbances. A new adaptive control strategy

This article investigates the stabilization of chained‐form nonholonomic systems with strong drifts, multidisturbances, and unknown constant parameters. The disturbances include the matched disturbance with bounded variation and the unknown time‐varying unmatched disturbance. A nonlinear disturbance observer is skillfully constructed to evaluate the matched disturbance and a disturbance estimation

Recently proposed adaptive dynamic programming (ADP) tracking controllers assume that the reference trajectory follows time‐invariant exo‐system dynamics—an assumption that does not hold for many applications. In order to overcome this limitation, we propose a new Q‐function that explicitly incorporates a parametrized approximation of the reference trajectory. This allows learning to track a general

In this work, we consider economic model predictive control of nonlinear networked control systems subject to external disturbances and communication delays in both sensor‐to‐controller and controller‐to‐actuator channels. The problem is addressed in the framework of the min‐max model predictive control. First, a delay compensation strategy is proposed to minimize the impact of communication delays

Small faults (some weak faults with a tiny magnitude) are difficult to detect and may cause severe problems leading to degrading the system performance. This paper proposes an approach to estimate, detect, and isolate small faults in uncertain nonlinear systems subjected to model uncertainties, disturbances, and measurement noise. A robust observer is developed to alleviate the lack of full state measurement

The finite‐time tracking control problem with the output‐constraint property of robotic manipulators subjected to system uncertainties is addressed. Specifically, the radial basis function neural network is employed to compensate for system uncertainties. The finite‐time stability theorem is used for the backstepping design process, by which the limit of the settling time is set. A funnel boundary

Taking advantage of an adaptive Taylor series approximator, this research seeks to address a two‐loop robust controller for electrically‐driven differential drive wheeled mobile robots. A fictitious current signal is designed in the outer loop such that the good tracking performance as well as the asymptotic stability of system will be achieved. Also, the error of currents will be minimized by an actual

We consider the problem of optimal feedback control of an unknown, noisy, time‐varying, dynamic system that is initialized repeatedly. Examples include a robotic manipulator which must perform the same motion, such as assisting a human, repeatedly and accelerating cavities in particle accelerators which are turned on for a fraction of a second with given initial conditions and vary slowly due to temperature

In this article, we present a proximity‐based formulation for moving horizon estimation (MHE) of a class of constrained discrete‐time nonlinear systems. The cost function of the proposed estimator includes a convex stage cost as well as a Bregman distance for the a priori estimate. This rather general formulation of the cost function allows for a flexible design of the estimator depending on the setting

In this work, we consider the monitoring of the absorption column of a typical post‐combustion capture plant within a distributed framework. The column is decomposed into a few subsystems, and a distributed moving horizon state estimator network is designed to estimate the state of the entire column. A state predictor is also designed for each subsystem to approximate the future evolution of the subsystem

This paper develops a sampling-based approach to implicit dual control. Implicit dual control methods synthesize stochastic control policies by systematically approximating the stochastic dynamic programming equations of Bellman, in contrast to explicit dual control methods that artificially induce probing into the control law by modifying the cost function to include a term that rewards learning.