This paper considers the problem of optimizing the operation of Indirect Adiabatic Cooling (IAC) systems with application to data centers. Optimal operation is achieved when the required cooling demand is satisfied at the minimum energy cost. For this purpose, we design a supervisory control system, where the higher layer determines the optimal set‐points for the local controllers by employing an Extremum

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

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

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled‐data dependence. The extracted knowledge ultimately serves to a decision‐making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black‐box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential

The problem of trajectory tracking of aerial vehicles with four rotors and dynamic parameter uncertainties is addressed in this article. By exploiting the cascade structure of the translational and attitude dynamics of the quadrotor, a nonlinear hierarchical adaptive control is proposed. The attitude control law is designed based on the unit quaternion, therefore, the singularities of the Euler angles

For a dual‐rate sampled‐data stochastic system with additive colored noise, a dual‐rate identification model is obtained by using the polynomial transformation technique, which is suitable for the available dual‐rate measurement data. Based on the obtained model, a maximum likelihood least squares‐based iterative (ML‐LSI) algorithm is presented for identifying the parameters of the dual‐rate sampled‐data

This study examines the fixed‐time adaptive neural network tracking control problem for a class of unknown multi‐input and multi‐output (MIMO) nonlinear pure‐feedback systems. The introduction of the radial basis function resolves uncertain problems of unknown MIMO systems. The mean value theorem is introduced to overcome the controller design problem attributed to the nonaffine structure in pure‐feedback

This article presents an adaptive neural compensation scheme for a class of large‐scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks

This article focuses on a decentralized sampled‐data filter design for a class of large‐scale interconnected systems. Precisely in the addressed system, the inevitable factors such as missing measurements, time‐varying delays, randomly occurring uncertainties, and impulsive effects are taken into consideration. Also, we incorporated the gain perturbations and sensor faults in the proposed filter design

This article introduces a network architecture, called dynoNet, utilizing linear dynamical operators as elementary building blocks. Owing to the dynamical nature of these blocks, dynoNet networks are tailored for sequence modeling and system identification purposes. The back‐propagation behavior of the linear dynamical operator with respect to both its parameters and its input sequence is defined.

A problem frequently encountered in Kalman filtering is the tuning of the noise covariance matrices. Indeed, misspecifying their values can drastically reduce the performance of the Kalman filter. Unfortunately, in most practical cases, noise statistics are not known a priori. This paper focuses on a method relying on subspace model identification theory to determine them accurately. This solution

The problem of robust stabilization for a class of nonlinear large‐scale systems with the energy constraints and time‐varying actuator faults is addressed in this article. In the considered system, the stabilization criteria is achieved via a sensor‐network‐based distributed fault‐tolerant controller. Moreover to limit the consumption of energy by the sensors, the measurement size reduction technique

This paper presents an adaptive fuzzy control scheme for a class of nonstrict‐feedback nonlinear systems with dead zone outputs and prescribed performance. By utilizing the monotonically increasing property of system bounding functions and the Nussbaum function, the design difficulties caused by the nonstrict‐feedback structure and dead zone output are overcome. Combining backstepping technique with

For an industrial control system, controller parameters are important factors that affect the control system performance. This article introduces a controller parameter performance assessment method based on disturbance characteristic variation for a dynamic matrix control system. Assuming that the process model is accurate and the setpoint is constant, disturbance characteristic variation without

Robust methods based on nonlinear influence functions are often used to remove outliers from data. The article describes the design of an algorithm for tracking a moving object in a thermal image using a SURF descriptor and robust Kalman filter. However, given that the main shortfall of robust methods is reduced efficiency, tunable parameters of the robust influence function are used to achieve a balance

In this article, the adaptive finite‐time fault‐tolerant control problem is considered for a class of switched nonlinear systems in nonstrict‐feedback form with actuator fault. The problem of finite‐time fault‐tolerant control is solved by introducing a finite‐time performance function. Meanwhile, the completely unknown nonlinear functions exist in the switched system are identified by the neural networks

This article investigates the problem of event‐trigger based adaptive backstepping control for a class of nonlinear fractional order systems. By introducing an appropriate transformation of frequency distributed model, the fractional‐order indirect Lyapunov method with is obtained. In addition, the event‐triggered adaptive controller is developed by employing the event‐triggered control approach. Meanwhile

The article develops a novel stubborn set‐membership filtering with the dynamic event‐triggered scheme for discrete‐time nonlinear systems with the state‐delays, unknown‐but‐bounded noises as well as abnormal measurements. First, in comparison with traditional event schemes, a dynamic event‐triggered scheme with a time‐varying auxiliary offset variable in the threshold is employed to schedule the access

This paper considers the joint estimation problem of state and unknown measurement noise covariance for nonlinear state‐space models. Using the variational Bayesian inference, the joint posterior distribution of state and measurement noise covariance is approximated by two independent proposal distributions, which is considered as a key idea of the proposed approach. Due to the nonlinearities caused

In this article, we present the basic concepts of fractional calculus and control and synchronization of fractional‐order chaotic satellite system . Existence and uniqueness solutions of fractional‐order satellite system are discussed and local stability of the system at the equilibrium points are studied. The lowest dimension of chaotic attractor of satellite system is 2.88 which is obtained through

Two parameter estimation methods for linear time‐delay systems are proposed based on the frequency responses and the harmonic balance methods. One is the stochastic gradient gradient‐based iterative (SG‐GI) algorithm and the other is the recursive least squares gradient‐based iterative (RLS‐GI) algorithm. These two methods can estimate the unknown parameters and the unknown time delays simultaneously

A fundamental challenge affecting the performance of a system is the undesired effect of noise on the system. Practically, real‐time systems are influenced by Gaussian noise and impulsive noise. Identification of these nonlinear physical systems in the presence of noise offers broader applications than linear system identification. Hence, this article introduces a variable step‐size technique to solve

A novel immersion and invariance (I&I) angular velocity observer is presented for the attitude tracking control of a rigid body with the lack of angular rate. Global exponential convergence of angular velocity estimate errors are guaranteed by an innovative filter design for the estimates' Euclidean norm. The proposed method requires fewer filter states compared with existing I&I angular velocity observer

Modeling and vibration control of a bridge beam system are considered in this article. The beam bridge with both ends fixed can be regarded as an Euler‐Bernoulli beam, which is a typical distributed parameter system. First, the partial differential equations (PDE) model of the bridge was established according to the Hamilton principle. Then, a reasonable distributed control law was designed on the

This article proposes an adaptive prescribed performance tracking control methodology for a class of strict‐feedback Multiple Inputs and Multiple Outputs nonlinear systems. A combination of backstepping technique and the generalized fuzzy hyperbolic model was used in recursive design of adaptive controller. A novel performance constraint function guarantees the tracking control performance. Lyapunov

High fidelity behavior prediction of intelligent agents is critical in many applications, which is challenging due to the stochasticity, heterogeneity, and time‐varying nature of agent behaviors. Prediction models that work for one individual may not be applicable to another. Besides, the prediction model trained on the training set may not generalize to the testing set. These challenges motivate the

In this article, a fault‐tolerant control (FTC) scheme for linear multiagent systems (MASs) subject to time‐varying loss of effectiveness and time‐varying additive actuator faults as well as external disturbance is investigated. The main objective of the proposed FTC approach is to keep the performance of an MAS after the occurrence of actuator faults similar to the healthy one. The envisaged adaptive

In this article, a switched sampled output adaptive observer for a class of switched nonlinearly parameterized systems is designed. Since the switching may occur during the sampling intervals while the sampled output only updates at sampling instants, the asynchronous switching phenomenon arises. Then, a collection of matched and mismatched corrective terms are introduced to deal with the asynchronous

This article concerns the assessment of diagnosis performance of a recently developed secondary protection (SP) applied to the IEEE 16‐machine 68‐bus test system subject to primary protection (PP) misoperations on transmission short circuit faults. A PP may fail to trip or falsely trip a line. Such PP misoperations have been known to be a main culprit of modern day blackouts. The function of the SP

Extinction coefficient (EC), as the key parameter of target intensity model, is assumed constant in classical infrared target tracking (IRTT) methods. However, it is a time‐varying and state‐coupled parameter related to complex atmosphere environment. To this end, this article proposes the problem of IRTT with time‐varying EC identification. Different from the constant EC case whose solution is the

In this article, a class of nonlinear interconnected systems with uncertain time varying parameters (TVPs) is considered. Both the interconnections and the isolated subsystems are nonlinear. The differences between the unknown TVPs and their corresponding nominal values are assumed to be bounded where the nominal value is not required to be known. A dynamical system is proposed and then, the error

In this article, we develop proportional, fractional‐integral, and derivative () controllers for the regulation and tracking problems of nonlinear systems. The analytic results are obtained by extending the passivity‐based approach to include fractional operators. Robustness under parametric uncertainty is dealt with by a combination with an adaptive scheme. It is also shown their robustness under

In this article, the problem of unified filters design including H∞, L2 − L∞, passive, dissipative filters and their reduced‐order ones is addressed for continuous‐time singular Markovian jump systems with discrete and distributed delays. Unlike some existing works, the mixed delays can be fully captured by proposing an extended free‐matrix‐based integral inequality. By considering two cases of distributed

In this article, the synchronization problem for nonlinear hybrid‐coupled complex networks with both coupling and internal self‐feedback delays is studied. An aperiodically intermittent adaptive control is employed for a fraction of nodes to pin the whole network to the synchronization state. Some sufficient conditions for realizing global synchronization are derived based on Halanay inequality and

The noncontinuous behavior of the controlled plant occurring as both positive and negative control directions is observed from the prototyping robotic system. By considering the controlled plant as a class of unknown nonlinear discrete‐time systems, the affine data‐driven model (ADM) is developed by a multi‐input fuzzy rule emulated network (MiFREN) when the property of a continuous function is omitted

In this paper, the problem of fault detection and identification for DC‐DC converters is presented. First, switched systems model and fault model are analyzed based the switched characteristics of the DC‐DC converters, taking the DC‐DC buck converter as an example. According to the switched Lyapunov function technique, a fault detection observer and a bank of linear switched fault identification observers

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state‐space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters

In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time‐delay systems with time‐varying full state constraints and input saturation. To overcome the problem of time‐varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The

In this article, the robust distributed fusion Kalman filtering problems are addressed for the networked mixed uncertain multisensor systems with random one‐step measurement delays, multiplicative noises, and uncertain noise variances. A new augmented state approach with fictitious measurement noises modeled by the first‐order moving average models is presented, by which the original system is transformed

The H∞ filtering problem for interconnected systems is addressed in this paper. In order to facilitate the stability analysis of interconnected systems under the conditions of failed interconnections, a strategy related to switched systems is introduced. Assume that the interconnections among these subsystems disconnect based on the mode‐dependent average dwell time (MDADT), a switching signal is implemented

In this article, we develop a novel method to design a controller for nonlinear systems represented by Takagi‐Sugeno (T‐S) fuzzy model in the presence of unknown dynamics, uncertainties in parameters of nonlinear system and external disturbances. The control law is constituted two segments. The first segment derives from parallel distributed compensation (PDC) procedure, in which each control rule

The cultivation of microalgae in photobioreactors (PBRs) is important in various sectors such as food, bioenergy, pigments, and cosmetics. Productivity optimization can be achieved without the need for a dynamic process model using model‐free extremum seeking control (ESC). This article explores the use of ESC to drive the productivity of a continuous PBR to optimal or suboptimal setpoints. The latter

While adaptive control methods have the capability to suppress the effect of system uncertainties without excessive reliance on dynamical system models, their stability can be adversely affected in the presence of coupled dynamics. Motivated by this standpoint, the contribution of this article is a decoupling approach for model reference adaptive control algorithms. The key feature of the proposed

The prescribed‐time output‐feedback stabilization (ie, regulation of the state and control input to zero within a “prescribed” time picked by the control designer irrespective of the initial state) of a general class of uncertain nonlinear strict‐feedback‐like systems is considered. Unlike prior results, the class of systems considered in this article allows crossproducts of unknown parameters (without

This article investigates mean square consensus of linear multiagent systems with measurement noises based on event‐triggered control. Considering various uncertain factors in the communication environment, multiplicative noises exists in the information that each agent measures from its neighbors. In order to save limited resources and to exclude the Zeno phenomenon, the update of the controller for

This article investigates the problem of event‐triggered control for network descriptor systems with randomly occurring uncertainties and nonlinearities. First, a novel adaptive event‐triggered scheme (AETC) is introduced to save more limited network resource. Second, by considering the network‐induced delay, randomly occurring uncertainties and nonlinearities, and the adaptive transmission scheme

A robust adaptive parameter estimation method, based on the application of a full‐order filter capable of rejecting exogenous disturbances, is proposed in this article. A linear matrix inequality condition is proposed to synthesize the desired robust filter, assuming the presence of a known input control with constraints. The filter uses the output of the system to estimate the desired signal that

This paper introduces a new class of feedback‐based data‐driven extremum seeking algorithms for the solution of model‐free optimization problems in smooth continuous‐time dynamical systems. The novelty of the algorithms lies on the incorporation of memory to store recorded data that enables the use of information‐rich datasets during the optimization process, and allows to dispense with the time‐varying

In this paper, discrete‐time adaptive control of linearly parameterized fully actuated Port‐controlled Hamiltonian systems with parameter uncertainties in energy function is considered. A discrete‐time adaptive interconnection and damping assignment passivity‐based control (IDA‐PBC) method, utilizing the immersion and invariance (I&I) approach, for the considered uncertain Hamiltonian system, is presented

This article addresses the leader‐following neural network adaptive observer‐based control of N tractors connected to n trailers with the prescribed performance specifications. To propose the controller, a change of coordinates and a nonlinear error transformation are used to transform the constrained error dynamics to a new second‐order Euler‐Lagrange unconstrained error dynamics which inherits all

In this study, we present a reinforcement learning (RL)‐based flight control system design method to improve the transient response performance of a closed‐loop reference model (CRM) adaptive control system. The methodology, known as RL‐CRM, relies on the generation of a dynamic adaption strategy by implementing RL on the variable factor in the feedback path gain matrix of the reference model. An actor‐critic

Electrocardiogram (ECG) signal transmission and monitoring plays a paramount role in long‐term cardiac monitoring and analysis to provide remote health care in time, especially for the postoperative people and people in remote areas. The accuracy of ECG signals is of fundamental importance in cardiac diagnosis like R‐peak detection. So we need to incorporate analytical methods in existing healthcare

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, the global fixed‐time synchronization issue is considered for semi‐Markovian switching discontinuous complex‐valued dynamical networks (CVDNs) with hybrid couplings and time‐varying delays, in which CVDNs are not divided into two real value systems, contrary to existing literature. First, a new fixed‐time convergence principle for complex‐valued nonlinear system with semi‐Markovian

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

In this paper, the issue of adaptive neural control is discussed for a class of stochastic nonstrict‐feedback constrained nonlinear systems with input and state unmodeled dynamics. A dynamic signal produced by the first‐order auxiliary system is employed to deal with the dynamical uncertain terms. Radial basis function neural networks are used to reconstruct unknown nonlinear continuous functions.

This paper studies the problem of observer‐based finite time adaptive fault tolerant control for nonaffine nonlinear systems with actuator faults and disturbances. Based on mean value theorem and convex combination method, a adaptive neural observer with virtual control coefficients is designed to estimate the systems states. Then, by using funnel Lyapunov function and backstepping method, a finite

This article is concerned with the adaptive output‐feedback control of switched nonstrict feedback nonlinear systems. By introducing a novel error surface, an adaptive control strategy is proposed for the general case where the nonlinear functions and the control gain functions are unknown, and the states are unmeasurable. The considered switched nonlinear system contains unknown actuator failures

This article studies the optimal filtering and control for wireless networked control systems (WNCSs). In WNCSs, packets may be lost in both control and feedback channels and user datagram protocol is usually used to improve the performance of the real‐time control. Relevant literature indicates that the conventional optimal filtering for such a system cannot be applied in practice due to the complex

This article addresses the identification of finite impulse response systems with binary‐valued observations under packet losses and transmission errors. First, the maximum likelihood function of the available data sequence is derived, based on which the estimation algorithm for the unknown parameter vector is given. Then, by making full use of the statistical properties of communication uncertainty