This article investigates the leader following of underactuated surface vessels that operate in the presence of environmental disturbances, model uncertainties, and actuator saturation. What makes the design of controller challenging is that the sway cannot be directly controlled. Furthermore, the actuator is formulated with magnitude saturation and rate saturation. To express the effect of magnitude

In the postcapture stage, relative motion could exist between the target and the robot end-effector, which is called unfirm capture . Unmodeled and time-varying dynamic and kinematic coupling in unfirm capture cases obstructs the estimation of target inertia properties and relative motion states. To solve this problem, vision navigation information and general dynamic equations are combined to compensate

This article concerns the event-triggered fuzzy filter design for Takagi-Sugeno (T-S) fuzzy systems subject to deception attacks under the stochastic multiple time-varying delays. A sequence of random variables, which are mutually independent but obey the Bernoulli distribution, is introduced to account for the randomly occurring communication delays. In order to efficiently utilize limited network

This article presents a new method of fault detection for the two-stage chemical reactor system. The process can be carried out effectively in the presence of the time-delay and the unknown inputs and the parameter uncertainties by using the observer-based method technique. In order to detect the actuator fault, a novel unknown input observer is employed as the residual generator. Multi-objective optimization

In this article, we develop the adaptive error feedback regulator design for one-dimensional heat equation with a nonlocal term and disturbances which are located all the channels. First, we construct a transformation to transform the original system into the first auxiliary system, and in this system the measurable tracking error becomes output, both the disturbances located at the in-domain and the

In the framework of asynchronous control, finite-time stabilization and finite-time bounded stabilization of linear time-varying (LTV) switched systems are investigated. A necessary and sufficient condition for finite-time stability (FTS) of LTV switched systems is proposed based on differential matrix inequalities (DMIs). Moreover, we extend the FTS result to the case of finite-time boundedness (FTB)

1 INTRODUCTION Real-world systems have to operate in uncertain and changing environments, thus the necessity to design feedback controllers which can adapt to such uncertainties. Controllers which are designed to satisfy this goal are called adaptive controllers. We can classify adaptive control into three main subclasses, for example, Reference : Classical model-based adaptive control, which mainly

Classical discrete-time adaptive controllers typically provide asymptotic stabilization and tracking; usually the affect of the noise is at best bounded-input bounded-output. Recently we have shown that if you design a discrete-time adaptive controller in just the right way, then in a variety of situations you not only obtain exponential stability, but also a bounded gain on the noise in every p−norm

In this work, an adaptive feedback linearized model predictive control (AFLMPC) scheme is proposed to compensate system uncertainty for a class of nonlinear multi-input multi-output system. Initially, a feedback linearization technique is used to transform the nonlinear dynamics into an exact linear model, thereafter, a model predictive control scheme is designed to obtain the desired tracking performance

The consensus problem for multiagent systems (MASs) with semi-Markov jumping parameters under the influence of disturbances is investigated in this article. In the first part of this article, an extended dissipative approach is used for the consensus of MASs with semi-Markovian jumping parameters and external disturbances via nonfragile controller with randomly occurring gain fluctuations. Besides

In the network environment, the single time-triggered scheme wastes limited bandwidth resources due to all the sampled data are transmitted to the networks, and the single event-triggered scheme may increase system error because of ignoring factors such as changes in network utilization. To reduce the design conservatism, this paper is concerned with the hybrid-triggered L1 fault detection filter design

The trajectory tracking control problem for a class of nonlinear systems with uncertain parameters is considered in this article. A new adaptive finite-time tracking control is designed based on the adaptive backstepping method via the command filters. The command filter mechanism can avoid the calculation of partial derivatives and solve the “explosion of complexity” in the backstepping design. The

In this article, the issue of adaptive finite-time dynamic surface control (DSC) is discussed for a class of parameterized nonlinear systems with full state constraints. Using the property of logarithmic function, a one-to-one nonlinear mapping is constructed to transform a constrained system into an unconstrained system with the same structure. The nonlinear filter is constructed to replace the first-order

This article studies the adaptive tracking control problem for a class of uncertain nonlinear systems with unmodeled dynamics and disturbances. First, a fuzzy state observer is established to estimate unmeasurable states. To overcome the problem of calculating explosion caused by the repeated differentiation of the virtual control signals, the command filter with a compensation mechanism is applied

This article is concerned with the distributed H∞ resilient state estimation problem for a class of nonlinear systems with randomly occurring communication delays and missing measurements in sensor networks. A novel sensor model is proposed, in which two Bernoulli distributed white sequences are introduced to describe the random communication delay and missing measurements in a unified framework. Meanwhile

The article discusses the adaptive fixed-time control problems for the stochastic pure-feedback nonlinear systems. Different from the existing results, the priori information of unknown virtual control coefficients (UVCC) is no longer needed in this article, which is realized by emplying the bound estimation method and well-defined smooth functions. A novel semi-global practical fixed-time stability

We propose a new reinforcement learning method in the framework of Recursive Least Squares-Temporal Difference (RLS-TD). Instead of using the standard mechanism of eligibility traces (resulting in RLS-TD()), we propose to use the forgetting factor commonly used in gradient-based or least-square estimation, and we show that it has a similar role as eligibility traces. An instrumental variable perspective

This paper proposes a new adaptive sliding mode control approach via output feedback for a class of nonlinear systems. The sliding-mode based controller can deal with parametric uncertainties and (un)matched disturbances with unknown upper bounds. Finite-time convergence of the tracking error to a predefined neighborhood of the origin of the closed-loop system is proved with guaranteed transient and

In this article, a novel cable-drogue docking system is proposed between an autonomous underwater vehicle (AUV) and one mobile underwater platform, to increase the docking safety and reduce the negative influences of turbulences around the platform shell on the AUV. The mathematical model of the cable-drogue system and an radial basis function neural network (RBFNN)-based Q-learning proportional-i

In this article, an adaptive prescribed performance controller is developed for hydraulic system with uncertainties. An extraordinary feature is that better prescribed performance control can be achieved by compensating the uncertainties including parameter uncertainties and disturbances. For this reason, the transformation of system output error is realized by a prescribed performance function, which

In this paper, the adaptive fuzzy controller design problem is investigated for a class of switched nonlinear systems in nonstrict feedback form, in which the unknown functions are considered and are approximated. Moreover, the system states are constrained in corresponding compact. By using Barrier Lypunov function method and backstepping technique, the adaptive fuzzy controller is designed such that

We present a certainty equivalence‐based adaptive boundary control scheme with a regulation‐triggered batch least‐squares identifier, for a heterodirectional transport partial differential equation‐ordinary differential equation (PDE‐ODE) system where the transport speeds of both transport PDEs are unknown. We use a nominal controller which is fed piecewise‐constant parameter estimates from an event‐triggered

This article presents a control scheme for flexible joint robots which has uncertain parameters based on adaptive fuzzy compensation. Considering the unknown parameters, the proposed state feedback control approach utilizes measured variables to establish a cascade structure that is based on simplified dynamics. After reducing the number of fuzzy rules, the adaptive fuzzy logic system is added as compensation

In this presented work, a systematic adaptive stabilization control strategy is proposed for nonholonomic system with parametric uncertainties and full‐state constraints. To facilitate the handling of state constraints, the original constrained nonholonomic system is converted into a new unconstrained system by state‐dependent function transformations including discontinuous state scalings. The adaptive

Many dynamic processes in practice have nonlinear characteristics and must be described by using nonlinear models. It remains to be a challenging problem to build the models of such nonlinear systems and to estimate their parameters. This article studies the parameter estimation problem for a class of Hammerstein‐Wiener nonlinear systems based on non‐uniform sampling. By means of the auxiliary model

In this article, we address the problems of flux and speed observer design for voltage‐fed induction motors with unknown rotor resistance and load torque. The only measured signals are stator current and control voltage. Invoking the recently reported Dynamic Regressor Extension and Mixing‐Based Adaptive Observer (DREMBAO), we provide the first global solution to this problem. The proposed DREMBAO

Steer‐by‐wire (SBW) systems are considered as one of the most significant innovations among the technologies developed for advanced driver‐assistance systems and autonomous vehicles. The main control challenge in a SBW system is to follow the steering commands in the face of parametric uncertainties and external disturbances; crucially, perturbations in inertial parameters and damping forces give rise

In this work, a nonlinear proportional and integral controller is presented for multiple‐input multiple‐output (MIMO) unknown nonlinear systems in normal form with unknown disturbances. The proposed control laws utilize nonlinear PI gains with trigonometric terms along with neural network (NN) approximators in order to account for both unknown nonlinearities and control directions. A proper selection

This article considers the parameter estimation for a fractional‐order nonlinear finite impulse response system with colored noise. For the fractional‐order systems, the challenge and difficulty are to identify the order and parameters of the systems simultaneously under colored noise disturbances. In order to reduce the problem of redundant parameter estimation, the output form of the system can be

Several cooperative driving strategies proposed in literature, sometimes known as cooperative adaptive cruise control strategies, assume that both relative spacing and relative velocity with preceding vehicle are available from on‐board sensors (laser or radar). Alternatively, these strategies assume communication of both velocity states and acceleration inputs from preceding vehicle. However, in practice

This paper focuses on the adaptive fuzzy event‐triggered consensus control problem for multi‐agent systems (MAS) with prescribed performance and input quantization. Based on a prescribed performance function and an input quantization decomposition method, a new adaptive fuzzy event‐triggered consensus protocol is presented. The instances in the event‐triggered mechanism are triggered only when the

This paper studies the problem of parameter estimation for the multifrequency sine signals, which have multiple characteristic parameters such as the amplitudes, phases, and frequencies. It is noted that the signal output is nonlinear with respect to the phase and frequency parameters while it is linear with respect to the amplitude parameters. This feature inspires us to separate all of the characteristic

In this article, the weighted couple‐group consensus is studied for a kind of discrete heterogeneous multiagent systems with time delays. Based on self‐adaptive controller and cooperative–competitive relation, a novel weighted couple‐group protocol is proposed for this system without satisfying the in‐degree balance of the vertex. By applying complex frequency method, matrix analysis and graph algebraic

In view of the result and performance of control are affected by the existence of input constraints and requirements, adaptive multi‐dimensional Taylor network (MTN) funnel control problem is studied for a class of nonlinear systems with asymmetric input saturation in this paper. Firstly, the effect of asymmetric input saturation can overcome by introducing the Gaussian error function, namely, the

This article studies the adaptive fuzzy finite‐time quantized control problem of stochastic nonlinear nonstrict‐feedback systems with full state constraints. During the control design process, fuzzy logic systems are used to identify the unknown nonlinear functions, integral barrier Lyapunov functions are employed to solve the state constrained problem. In the frame of backstepping design, an adaptive

This article addresses the issue of delay‐dependent H∞ filtering design for TakagiŮSugeno fuzzy time‐varying delay systems using the input–output approach. A three‐term approximation model has been used to transform the original system into two interconnected subsystems. Since the nonquadratic Lyapunov–Krasovskii functional requires to deal with the membership function's (MF) time derivative, upper‐bound

In this article, an autonomous carrier landing problem of an aircraft is addressed by developing an autonomous carrier landing system (ACLS) composed of previewable guidance and control systems. In the guidance system, an appropriate touchdown point is estimated by predicting the seakeeping motion of the deck by unscented Kalman filtering technique, which is then utilized to adjust the reference glide

This article reports the development, stability analysis, and experimental evaluation of a novel adaptive identification (AID) algorithm for underwater vehicles (UVs) for on‐line estimation of plant parameters (hydrodynamic mass, quadratic drag, righting moment, and buoyancy parameters) that enter linearly into 6 degree‐of‐freedom (6‐DOF) second‐order rigid‐body UV plant dynamic models. The reported

In this paper, the parameter estimation issue of Wiener system with random time delay and missing output data is studied. The linear part of Wiener system is described by Finite Impulse Response (FIR) model. The mathematical formula of the Expectation Maximum algorithm to identify Wiener‐FIR system that contains the random time delay and the nonlinear output data in missing completely at random mechanism

This article presents a generalized learning observer (GLO) design for the simultaneous estimation of states and actuator faults for polytopic quasi‐linear parameter varying systems. The proposed approach is based on the use of a GLO, which generalized the existing results on the proportional‐integral observers. Conditions of existence and stability of the observer are given through the stability analysis

This article concerns the estimation and tracking control problems for Takagi–Sugeno systems with disturbances and norm bounded uncertainties in presence of sensor and actuator faults (SAF). First, we propose a robust fuzzy observer (RFO) design method to estimate both state and SAF for the considered class of the nonlinear systems. Then, this RFO‐based fault tolerant tracking control is developed

The paper is devoted to the asymptotic output consensus for a class of uncertain nonlinear multi‐agent systems. The disturbance that the system suffered is said to be “atypical" since, unlike the related literature, it is unnecessarily continuously differentiable (e.g., sawtooth wave), and even permitted to be discontinuous (e.g., square wave), despite requiring it to be of unknown integer multiples

This article considers a distributed Kalman filtering problem for linear system contaminated by complex multi‐channel random uncertain parameter in which a number of nodes cooperative without central coordination to estimate a common state based on local measurements and data received from neighbors. We propose an approach to eliminate this error propagation. The proposed local filters are guaranteed

This article investigates the event‐triggered Kalman consensus filtering (ET‐KCF) problem for distributed sensor networks with intermittent observations. First, a novel ET consensus filtering structure is designed for sensor networks with intermittent observations. With the proposed consensus filtering structure, a new ET mechanism that is more efficient than the existed ones is designed to schedule

We present an extremum seeking (ES)‐based robust observer design for thermal‐fluid systems, pursuing an application to efficient energy management in buildings. The model is originally described by Boussinesq equations which is given by a system of two coupled partial differential equations (PDEs) for the velocity field and temperature profile constrained to incompressible flow. Using proper orthogonal

This article deals with the issue of input‐to‐state stabilization for recurrent neural networks with delay and external disturbance. The goal is to design a suitable weight‐learning law to make the considered network input‐to‐state stable with a predefined ‐gain. Based on the solution of linear matrix inequalities, two schemes for the desired learning law are presented via using decay‐rate‐dependent

The mirror‐modified filtered‐x least mean squares (MMFxLMS ) algorithm is a variation of the FxLMS algorithm with online secondary path modeling that cannot diverge due to secondary path modeling errors. However, problems may occur when the ambient noise is not limited due to insufficient modeling power. This work shows that under a frequency domain analysis without ambient noise, the MMFxLMS algorithm

In this paper we address the problem of distributed state estimation of continuous‐ and discrete‐time stable, LTI systems. The classical observer canonical form representation of the system dynamics is used to identify the observable states for each node (agent). The main novelty of our contribution is to obviate the need of the asymptotically (or finite‐time) local Luenberger observers. Instead, following

In this article, a decentralized optimal tracking control strategy is proposed for a class of nonlinear systems with tracking error constraints by utilizing adaptive dynamic programming (ADP). It should be noted that ADP technology cannot be directly used to solve decentralized optimal tracking problem of large‐scale interconnected nonlinear system with nonzero equilibrium points, since that an infinite

In this article, the fuzzy adaptive finite‐time consensus tracking control problem for nonstrict feedback nonlinear multiagent systems with full‐state constraints is studied. The finite‐time control based on command filtered backstepping is proposed to guarantee the finite‐time convergence and eliminate the explosion of complexity problem caused by backstepping process, and the errors in the filtering

In this article, based on partial differential equations (PDEs), the flexible manipulator system with both dead‐zone input and state constraints is studied. The dynamic model of the flexible manipulator system is described by PDEs. The parameters of the dead‐zone input are unknown, and the state constraint problem is also considered. An adaptive approach is proposed to offset the effects caused by

This work presents an adaptive saturation compensation scheme for the strict-feedback uncertain systems with unknown control coefficient and input saturation. An adaptive saturation dynamic filter that does not require the a priori information of the completely unknown control coefficient is incorporated to correct position errors online to reduce the saturation effect. A Nussbaum-type function is

This article analyzes the integral sliding mode control (ISMC) problem for the nonlinear stochastic system by employing the fuzzy approach. Firstly, the Takagi-Sugeno (T-S) fuzzy stochastic model with unknown nonlinear function and external disturbance has been developed. Based on the fuzzy model, an observer-based integral sliding mode fuzzy controller is derived under the event-triggered scheme (ETS)

This article studies the finite‐time output regulation problem for nonlinear strict‐feedback systems with completely unknown control directions and unknown functions. First, according to the necessary conditions for the solvability of the output regulation problem, the output regulation problem of nonlinear strict‐feedback systems and the external system is transformed into a stabilization problem

This article presents a continuous dynamical system model learning methodology that can be used to generate reference trajectories for the autonomous systems to follow, such that these trajectories are invariant to a given closed set and uniformly ultimately bounded with respect to an equilibrium point inside the closed set. The autonomous system dynamics are approximated using extreme learning machines

The paper considers a block-oriented nonlinear Hammerstein system that consists of a linear block with real-valued time-varying unknown coefficients and a pure time delay, preceded by the static nonlinearity. The joint tracking of linear block coefficients and the time delay while processing observation samples is under consideration. The difficulty of the tracking process consists in the initial nonconvexity

In this article, by using singular perturbation theory, reinforcement learning (RL), and Takagi–Sugeno (T-S) fuzzy methods, a RL-fuzzy-based composite suboptimal control method is proposed for nonlinear slow-fast coupled systems (SFCSs) with unknown slow dynamics. First, the SFCSs is decomposed into slow and fast subsystems and the original optimal control problem is reduced to two subproblems. Then

The scope of this research is a problem of parameters identification of a linear time-invariant plant, which (1) input signal is not frequency-rich, (2) is subjected to initial conditions and external disturbances. The memory regressor extension (MRE) scheme, in which a specially derived differential equation is used as a filter, is applied to solve the above-stated problem. Such a filter allows us

The tracking control problem for a class of partial state constrained nonlinear system is studied in this article. The system is divided into two semistrict feedback nonlinear subsystems, one is state constrained and the other is state free. By means of state transformation, the state constraint problem is transformed into the bounded problem of the transformed function. Compared with the barrier Lyapunov

Resilience literally is the ability to readily recover from illness, depression, or adversity. Control system resilience is the system's ability to accommodate its faults, disturbances, and uncertainties, to recover its desired performance. Resilient control is to increase control system resilience for performance guarantees in the presence of uncertain faults (such as actuator and sensor failures