The analysis result of disturbance-observer-based control (DOBC) for semi-Markovian jump systems (S-MJSs) with time-varying delay and generally uncertain transition rate (TR) is given in this paper. At present, there are still some urgent problems needed to be solved for S-MJSs such that conservative of stability, difficult of obtaining of TR in practical system, and the unexpected transient performance

A new hybrid technique for grid integration of solar photovoltaic system using modified incremental conductance maximum power point tracking algorithm with multi-output converter and multilevel inverter is proposed in the paper. The proposed hybrid technique is the joint execution of improved dolphin echolocation algorithm and gradient boosting decision trees and this way the proposed technique is

This paper proposes a nonlinear coordinated controller for a single machine infinite bus power system. The later consists of a synchronous generator connected to the infinite bus via transmission lines, which are equipped with a static var compensator. The proposed control strategy aims to control simultaneously the excitation system of the synchronous generator and the static var compensator in order

Heat transfer analysis is the one of the most important designing aspects for many engineering systems. The design prospect in the preview of heat transfer focuses on the prediction of heat flux with the help of measured transient temperature data. Thin film gauges are one of the most predominant method for the heat flux prediction especially for short duration transient temperature measurement. Thin

In this paper, the optimal power flow management-based microgrid in hybrid renewable energy sources with hybrid proposed technique is presented. The photovoltaic, wind turbine, fuel cell and battery are also presented. The proposed technique is the combined execution of both spotted hyena optimization and elephant herding optimization. Spotted hyena optimization is utilized to optimize the combination

The present paper aims to design an integrated kinematic/dynamic-based tracking controller for wheeled mobile robots (WMRs) considering motors’ dynamics. By defining a reference WMR, the role of kinematic controller is to not only minimize the posture error which indicates the difference between the reference and actual WMRs, but also to generate a desired path for the actual WMR. The kinematic tracking

Aiming at fault detection in industrial processes with nonlinear or high dimensions, a novel method based on locally linear embedding preserve neighborhood for fault detection is proposed in this paper. Locally linear embedding preserve neighborhood is a feature-mapping method that combines Locally linear embedding and Laplacian eigenmaps algorithms. First, two weight matrices are obtained by the Locally

This paper presented an effective technique for considering optimal scheduling of microgrid (MG) with islanding constraints. The proposed optimal scheduling approach is the combination of both the modified dragonfly algorithm (MDA) and whale optimization algorithm (WOA)-based approach named as (MDAWO). In this work, the searching conduct of the dragonflies is altered by the effective WOA approach.

This paper investigates the fault detection problem of instruments in process industry. Considering the difficulty of fault identification and the problems of multivariable and large computation complexity based on traditional kernel principal component analysis (KPCA), this paper presents a new method for fault detection and identification, which combines the coupling analysis with kernel principal

This paper deals with (i) damping improvement and (ii) energy management of a DC microgrid for improvement of its stability. The direct current (DC) microgrid has a solar-photovoltaic system as a renewable source and fuel cell-battery combination as a backup system to supply power to constant power loads (CPLs). The presence of CPLs in a DC microgrid makes the stability problem more challenging since

This study aims to determine how to deal with the identification from input and output data of switched linear systems (SLSs) with Box and Jenkins models. The identification difficulties of this system are that there exist unknown switched signal, unknown middle variables, and colored noise terms in the identification process. To address these issues, the proposed identification method proceeds in

In this paper, the H∞ control problem for a class of two-dimensional (2-D) linear discrete-time systems with fading measurements is investigated, where the 2-D systems are described by a Roesser model. The Rice fading model is applied to describe the fading phenomenon and the coefficients of the model satisfy the independent identical Gaussian distributions. The main objective of this paper is to design

In this paper, the maximum power point tracking problem of variable-speed wind turbine systems is studied. Both mechanical part and electromagnetic part of the wind energy conversion system are taken into consideration. In view of the different time scales between the mechanical part and electromagnetic part, singular perturbation theory is applied to model the system in order to cope with the stiffness

In this paper, the nonlinear robust H∞ control is investigated for nonlinear course control systems of unmanned surface vessel (USV) with uncertain parameters and external disturbance. Firstly, we suppose that the part or all of the system parameters are unknown but within some ranges, due to the effect of different conditions such as the loading of ship. Then, the course system is modeled as a polynomial

In this paper, we design a novel sliding mode prediction fault-tolerant control algorithm for multi-delays discrete uncertain systems with sensor fault. The global sliding surface is designed to replace the traditional linear sliding surface as a predictive model to ensure the global robustness of the system. For sensor fault and sliding mode buffeting, a power-dependent function reference trajectory

This paper is concerned with the problem that fast-transient response and excellent robustness cannot be satisfied simultaneously in the process of dynamic positioning (DP) for underactuated surface vessel (USV) in shallow water. By combing the improved L1 adaptive control with backstepping method, a novel control scheme is designed, which can ensure a fast adaptation with a guaranteed smooth transient

Synchronization of distributed hydropower units is necessary for ensuring the quality of the electric power produced by renewable sources. In this article, a nonlinear optimal control approach is proposed for stabilization and synchronization of distributed hydropower generators. The dynamic model of the interacting hydropower generation units undergoes approximate linearization with the use of first-order

This paper proposes fault-tolerant control design for uncertain nonlinear systems described under Takagi-Sugeno fuzzy systems with local nonlinear models that satisfy the Lipschitz condition. First, by transforming sensor faults as ‘pseudo-actuator’ faults, an adaptive sliding mode observer is designed in order to simultaneously estimate system states, actuator and sensor faults despite the presence

This paper proposes an event-triggered control for positive Markov jump systems without/with input saturation. First, an event-triggering condition is established in the form of 1-norm for positive Markov jump systems. Under the event-triggering condition, the term related to error signal between the sample state and the actual state is transformed into a form of interval uncertainty. Then, the positivity

This paper studies the problem of finite-time consensus (FTC) for uncertain multiple mechanical systems with unknown backlash nonlinearity and external disturbance. Combining finite-time control technique and graph theory, a distributed adaptive FTC protocol is proposed. Radial basis function neural networks are employed to approximate the unknown functions. If the designed parameters of control algorithms

In this paper, a novel control technique on basis of adaptive immersion and invariance (I&I) theorem and fuzzy systems is proposed to control the brushless direct current motors (BLDCMs) for electric vehicles. The chaotic behaviour of the BDCMs is synchronized with the desired chaotic system. The parameters of the chaotic model are considered to be unknown and are online estimated with tuning rules

Tremor is an uncontrolled trembling movement or shakes, which are defined as an involuntary, rhythmic oscillatory movement of the body. The dominant features of Parkinsonism are the motor task and its frequency. This paper presents studies on the tremor parameter identification to be used for obtaining the frequency as a dynamical feature of the tremor. The method is based on the analysis of time-varying

Due to the concern with energy emergencies, the energy obtained from the sunlight is considered as the most capable conventional resources. Hence, the maximum power point tracking approach is necessary for obtaining the enhanced efficiency from the solar panels. In the case of direct current (DC) application, the output obtained from the photo-voltaic (PV) array cannot be directly connected to the

A smooth polynomial shaped command with an adjustable command time length is proposed for eliminating the residual vibrations of a multi-mode system. The ability of eliminating jerks and vibrational modes, regardless of their number, offers the most advantage of the proposed command. A numerical simulation is conducted to test the command’s effectiveness by eliminating the residual sloshing oscillations

In this paper, a novel method for the design of robust nonlinear observer in the H∞ framework for Lipschitz nonlinear systems is proposed. For this purpose, a new dynamical structure is introduced that ensures the stability of observer error dynamics. Design innovation is the use of dynamic gain in the sliding mode observer. The additional degree of freedom provided by this dynamic formulation is exploited

This paper is associated with the problem of robust stability of discrete-time systems with time-varying delays and finite wordlength nonlinearities. The main contribution of the paper is two-fold. First, this paper presents a new Lyapunov function based on the idea of partitioning the delay interval into subintervals. The approach may be considered as an advancement over the several existing approaches

Application performance of mechanical positioning systems might not coincide with the theory, mainly due to nonlinearities or imperfections of system models. Although it is sometimes possible to ignore these mismatches, systems generally suffer from performance degradation or even instability eventually. Especially, friction force and time delay are two major factors of these undesired effects. Hence

Quantization is a significant technique in network control to save limited bandwidth. In this work, two new multi-lagged-input-based quantized iterative learning control (MLI-QILC) methods are proposed by using output quantization and error quantization, respectively. The multi-lagged-input iterative dynamic linearization method (MLI-IDL) is introduced to build a linear data model of nonlinear systems

A fixed-time sliding mode control (FTSMC) method is proposed for a second-order system with mismatched uncertainties in this paper. A new sliding mode, which is insensitive to the mismatched disturbance, is present to eliminate the effect of mismatched uncertainties by adopting the differentiable nonlinear function, and to obtain the fixed time stability independent of initial conditions by using the

Control charts are commonly applied for monitoring and controlling the performance of the manufacturing process. Usually, control charts are designed based on the main quality characteristics variable. However, there exist numerous other variables which are highly associated with the main variable. Therefore, generalized linear model (GLM)-based control charts were used, which are capable of maintaining

This paper presents an adaptive multi-dimensional Taylor network (MTN) control approach for a class of nonlinear systems with unknown parameters. MTN is employed to identify unknown nonlinear characteristics existing in the system, and then a novel adaptive MTN tracking control method is proposed, via backstepping technique. In the controller design, double adaptive laws are designed and appropriate

Many engineering problems can be modelled as linear periodic time-varying (LPTV) systems, which naturally leads to the need for model order reduction of LPTV systems. This paper investigates a new model order reduction method for discrete LPTV systems. First, the state-space realization in the Fourier-lifted form of discrete LPTV system is constructed by representing periodic matrices in exponentially

In this paper, we are interested in the stabilization of the flow modeled by the Saint-Venant equations. We have solved two problems in this study. The first, we have proved that the operator associated to the Saint-Venant system has a finite number of unstable eigenvalues. Consequently, the system is not exponentially stable on the space L2(Ω)×L2(Ω), but is exponentially stable on a subspace of the

In this paper, the asymptotic stability for chaotic Lur’e systems (CLSs) is studied. A new control method, which involves both state quantizer and control quantizer, is presented. In addition, dynamic parameters of quantizers and controller are designed synchronously to ensure the asymptotic synchronization of the master–slave systems. Moreover, by solving linear matrix inequalities, the corresponding

Non-intrusive load monitoring (NILM) is a critical technique for advanced smart grid management due to the convenience of monitoring and analysing individual appliances’ power consumption in a non-intrusive fashion. Inspired by emerging machine learning technologies, many recent non-intrusive load monitoring studies have adopted artificial neural networks (ANN) to disaggregate appliances’ power from

The measurement of the centroid is of great significance to improve the control performance and reduce the energy consumption of the planetary rover (PR). The uncertainty is an essential indicator of the reliability of centroid measurement results. The purpose of the current study is to evaluate the uncertainty of centroid measurement in the multi-configuration rover. For the measurement of the centroid

This study investigates a parametric approach to design the proportional-integral (PI) controller for a permanent magnet synchronous motor (PMSM). Based on the solutions of the generalized Sylvester equation, the generally parametric expressions of PI controller and right eigenvector matrix are obtained. By using the parametric approach, the closed-loop system is converted into a linear time-invariant

In this paper, a predictor-based fractional disturbance rejection control (PFDRC) scheme is proposed for processes subject to input delay. The proposed scheme can be generally applied to open-loop stable, integrative, and unstable integer-order processes, but it can be particularly utilized for open-loop stable fractional-order systems. A closed-loop reference model is formulated based on Bode’s ideal

This paper proposes a compound control framework for non-affine nonlinear systems facing hysteresis disturbance. The controller consists of linear active disturbance rejection control (LADRC) and backpropagation (BP) neural networks adaptive control. BP neural networks are utilized to arbitrarily approximate the uncertainty nonlinear caused by the deviation of control parameter from its nominal value

Multi-power sources are included in hybrid electrical vehicles, which leads to multi-driving modes co-existing when driving the vehicle. However, the frequent driving mode switching (DMS) will probably need the engine to be started frequently, which can result in extra fuel consumption. So, avoiding unnecessary DMS should be fully considered when designing the control strategy. For solving this problem

This paper presents an integrated nonlinear robust adaptive controller with uncertainty observer for active front wheel steering system and direct yaw moment control system. First, an integrated vehicle chassis control model is established as the nominal model with the additive and multiplicative uncertainties of the system. Secondly, an integrated nonlinear robust adaptive control law with the additive

Two common methods exist for solving indoor autonomous navigation and obstacle-avoidance problems using monocular vision: the traditional simultaneous localization and mapping (SLAM) method, which requires complex hardware, heavy calculations, and is prone to errors in low texture or dynamic environments; and deep-learning algorithms, which use the fully connected layer for classification or regression

Aiming at the unstable performance on fast-moving and deformational target tracking in current kernel correlation filter (KCF), an innovative approach based on heterogeneous features fusion is proposed in this paper. Firstly, a histogram of oriented gradient is utilized to cater for motion state change in complex surveillance background. Combined with a colour-free template as a novel heterogeneous

This paper is concerned with the consensus tracking problem in nonlinear multi-agent systems against external disturbances and multiple actuator faults. The nonlinear dynamics are unknown and the leader’s input is unavailable to any follower. By using finite-time Lyapunov stability theory, a distributed discontinuous protocol is developed. On this basis, a fixed-time control protocol is further designed

In order to improve the dynamic performance and stability of general acceleration slip regulation (ASR) control technology for four-wheel independent drive electric vehicle (4WID EV), an ASR control strategy based on variable gain controller (VGC) is proposed in this paper. First of all, a road identification strategy is designed to identify the current road surface and calculate the optimal slip ratio

In this paper, an online temporal differences (TD) learning approach is proposed to solve the robust control problem for discrete-time Markov jump linear systems (MJLS) subject to completely unknown transition probabilities (TP). The TD learning algorithm consists of two parts: policy evaluation and policy improvement. In the first part, by observing the mode jumping trajectories instead of solving

This paper is concerned with the problem of finite-time dissipative control for networked control systems by hybrid triggered scheme. In order to save network resources, a hybrid triggered scheme is proposed, which consists of time-triggered scheme and event-triggered scheme simultaneously. Firstly, sufficient conditions are derived to guarantee that the closed-loop system is finite-time bounded (FTBD)

A finite iterative algorithm is presented for solving the numerical solutions to the coupled operator matrix equations in Zhang (2017b). In this paper, a new finite iterative algorithm is presented for solving the constraint solutions to the coupled operator matrix equations [∑i=1pA1i(Xi),∑i=1pA2i(Xi),⋯,∑i=1pApi(Xi)]=[M1,M2,⋯,Mp], where the constraint solutions include symmetric solutions, bisymmetric

This paper presents a stabilization control for positive, Takagi-Sugeno fuzzy systems subject to Markov jump parameters. In the continuous-time formulation, the approach guarantees mean-square stability with constraints on the control—the main condition hinges upon linear matrix inequalities. The proposed method’s usefulness is illustrated by a practical-oriented example, which was designed to control

This paper studies a new procedure for robust tracking of nonlinear systems. This procedure is based on the combination of the sliding mode control and the funnel control, which in addition to the robust performance of the closed-loop system in the face of model uncertainties and/or external disturbances also leads to improvement of the characteristics of the transient responses. Using funnel control

In order to realize green manufacturing in the production process of semi-combined marine crankshaft structural parts, good job scheduling and reasonable workshop layout are the key. In traditional method, flexible job shop scheduling problem (FJSP) and the multi-row workshop layout problem (MRWLP) are regarded as separate tasks. However, the separate optimization method ignores the interaction between

Sameh Adaily, Abdelkader Mbarek, Tarek Garna and José Ragot, ‘A new multimodel approach by Laguerre filters on sliding window for nonlinear system identification and control’ (2020). DOI: 10.1177/0142331220908996

A control strategy for a bearingless induction motor (BL-IM) based on the fuzzy dynamic objective function is proposed in this paper. Firstly, based on the discrete mathematical model of the BL-IM, the stator current and flux linkage are predicted according to the given stator current and flux linkage, the objective function of model predictive current control (MPCC) is designed. Secondly, the fuzzy

This paper proposes a convenient power electronic circuitry with a control approach for the flywheel replacement of an induction motor. The proposed control approach is the joined execution of grasshopper optimization algorithm and recurrent neural network based on duty ratio controller and hence the proposed work is named grasshopper optimization with recurrent neural network. The main contribution

Heat transfer and fluid flow play important roles in industrial processes, especially in chemical and thermal processes. Their dynamics are often modelled as high order systems with the type of K/(Ts+1)n, which have slow responses to the set point and the input disturbance. To enhance the tracking and disturbance rejection performance of these systems, a control structure combining the proportional-integral

This paper presents optimal adaptive fuzzy approaches combined by the predictive models for five degrees of freedom vehicle systems having a control force constraint of 1000 N on both front and rear suspensions in order to minimize the road disturbances. First, two separate adaptive fuzzy controllers are designed for the rear and front tires using the singleton fuzzifier, center average defuzzifier

In this paper, the robust control problem is tackled by employing the state-dependent Riccati equation (SDRE) for uncertain systems with unmeasurable states subject to mismatched time-varying disturbances. The proposed observer-based robust (OBR) controller is applied to two highly nonlinear, coupled and large robotic systems: namely a manipulator presenting joint flexibility due to deformation of

The novelty of this paper is the usage of a time-varying sliding surface with a fractional-order sliding mode controller. The objective of the controller is to allow the system states to move to the sliding surface and remain on it so as to ensure the asymptotic stability of the closed-loop system. The Lyapunov stability method is adopted to verify the stability of the controller. Firstly, by using

In this study, we consider the problem of designing functional interval observers for a class of singular fractional-order systems. The goal of this work is to design not a full state interval observer for singular fractional-order systems, but to design an observer for state functions of this kind of systems. Conditions for the existence of such functional interval observers are given and an effective

In this study, an anti-windup reconfigurable control method is developed for dynamic positioning vessel in the presence of thruster faults and input saturation. The designed reconfiguration block acting as a virtual thruster aims at hiding the faults from the nominal controller. Also, it is added into the closed-loop system between the nominal controller and the dynamic positioning system. A thruster