This paper presents an adaptive model predictive control (MPC) method based on disturbance observer (DOB) to improve the disturbance rejection performance of the image-based visual servoing (IBVS) system. The proposed control method is developed based on the depth-independent interaction matrix, which can simultaneously handle unknown camera intrinsic and extrinsic parameters, unknown depth parameters

This paper aims to compare two strategies for damping low-frequency electromechanical oscillations in multi-machine power systems through Static Synchronous Compensators (STATCOM) with a multi-band controller. STATCOM is represented by a controllable voltage source behind an impedance and the multi-band controller acts as a power oscillation damper that modulates parameters of the voltage source in

The information on data packet loss occurrences in a networked control system (NCS) is useful for improving the control performance and detecting communication failures or cyber-attacks. This study considers the simultaneous estimation of the plant state and packet loss occurrences at each time step. After formulation of the problem, two solutions are proposed. In the first one, an input–output representation

Kalman filter and its different variants are commonly used as optimal methods for fault detection in various types of system components. In this paper, a newly introduced type of aforementioned filters, called modal Kalman filter, is extended and utilized in order to state estimation of nonlinear systems, for sensor fault detection purposes in a class of nonlinear certain systems. This method, in contrast

Due to the emerging applications of ultra-high precision scanning in many engineering fields, dynamical tracking of desired reference trajectories for nano-stages has attracted a lot of significant research. An adaptive integral sliding mode control (AISMC) framework in combination with frequency-shaped optimization and hysteresis observer is proposed to improve tracking performance of piezoelectric

This work is focused on optimal control of mechanical compression refrigeration systems. A reduced-order state-space model based on the moving boundary approach is proposed for the canonical cycle, which eases the controller design. The optimal cycle (that satisfying the cooling demand while maximizing efficiency) is defined by three variables, but only two inputs are available, therefore the controllability

This paper presents an adaptation of the Active Disturbance Rejection Control (ADRC) method within the fractional calculus context. This ADRC version is characterized by a single active cancellation of the lumped effects of all the unmodeled dynamics, external disturbances and parameter uncertainty associated with the linear model of commensurate fractional order. This methodology proposes suitable

This paper addresses a missile-target interception guidance process considering acceleration saturation and target maneuver as a constrained nonlinear tracking issue. A dynamic auxiliary system is designed for compensating the effects of constrained input, and external disturbances are counteracted through designing a nonlinear disturbance observer (NDO). The feedforward+feedback composite architecture

Regarding a class of multi-input and multi-output (MIMO) nonlinear systems, this paper presents a multi-variable linear extended state observer (MVLESO), which is applied to estimate uncertain dynamics of system real-timely. After that, a new frequency-domain analysis approach is explored to present the convergence property of MVLESO with respect to the estimation on uncertain dynamics. Meanwhile,

The adaptive control of a class of strict-feedback nonlinear system under replay attack is investigated in this paper. Durations of each attack and the resting time after each attack are analyzed and their explicit bounds are presented to ensure closed-loop stability. Two scenarios are considered. In the first scenario, it is shown that if the duration of each attack is less than a given constant,

Image fusion expands the space–time scope of the detection target by making full use of the information complementarity between images, which is useful for automatic target recognition. An adaptive fractional multi-scale edge-preserving decomposition based on the weighted least square framework is proposed to fuse infrared (IR) and visible (VIS) images. It decomposes images into the base layer and

In this work, a novel methodology for tuning fractional order controller, so-called fractional order pole placement (FOPP) is proposed. The proposed methodology extends classical (integer order) pole placement technique, using commensurable transfer functions for representing fractional order controllers and placing the fractional dominant poles within an extended stability region based on three terms

In this paper, a novel grey decision-differential evolution (GD-DE) optimized internal model controller is proposed for the control of nonlinear aeroelastic blade system (ABS) under time-varying uncertainties and control saturations. Two-port internal model control structure is presented for saturation compensation. The filter parameter of the controller is optimally tuned by proposed GD-DE algorithm

Nowadays, most intelligent diagnosis methods focus on fault classification and the discriminative knowledge is unknown due to the ‘black box’ characteristic. However, impulse responses in vibration signals, which is important sign to determine whether mechanical equipment is faulty, are rarely studied under intelligent methods since their recognition is both difficult and time-consuming, especially

The increased usage of electric and electronic devices on board the aircraft requested by the “More Electric Aircraft” (MEA) requires the adoption of multi-objective control algorithms, with controllers (supervisors) able to autonomously switch among different objectives. However, the operating point changes during operations, and “small signal” analysis becomes inconclusive to assess overall stability

Correlated representation learning has found wide usage in process monitoring. However, slow and normal changes frequently occur in practical production processes, which may lead to model mismatch and degrade monitoring performance. Therefore, updating the monitoring model online and involving recently processed data information are important. This study proposes a recursive correlated representation

In this study, a typical supply chain network design problem consisting of plants, distribution centers, and customers is considered with the assumptions of multi-mode demand and multi-mode transportation. In it, the parameters of the problem are considered as a trapezoidal intuitionistic fuzzy value to handle the vagueness in the information. Based on it, a hybrid approach is proposed where the fuzzy

This paper studied the performance of networked control systems (NCSs) with coding and quantization constraints. In the forward channel of NCSs, the effects of noise and coding-decoding under a two-degree of freedom controller (2DOF) are considered, while in the feedback channel, the effects of quantization and bandwidth are taken into account. The performance expression is achieved by the spectral

In this paper, robust tracking control for a class of nonlinear systems with external disturbance in the presence of input saturation and collision avoidance constraints is investigated. Both of these constraints are considered in a non-quadratic cost function. To obtain optimal control laws, a technique is proposed based on adaptive dynamic programming (ADP) assuming the worst case of disturbance

This paper focuses on the consensus tracking control of nonlinear multi-agent systems by utilizing the quadratic inner-bounded (QIB) and the one-sided Lipschitz (OSL) conditions in the presence of input saturation constraint under a directed communication topology. A novel sector constraint for the saturation function to formulate consensus control of nonlinear systems under saturating inputs is derived

This study aims to design a robust reset dynamic output feedback control (DOFC) for a class of uncertain linear systems. This procedure is performed as following. First, the elements of the robust DOFC are designed via the linear matrix inequality (LMI) technique such that closed-loop exponential stability is achieved. Second, reset law which contains value of after reset and a constraint for the reset

In this paper, we consider a fixed-time autonomous ship landing control design for helicopters subject to asymmetric output constraints, model uncertainties and external perturbations. By incorporating a universal barrier function into the backstepping design, an output-constrained fixed-time control algorithm is proposed, where a new adaptive estimation method is introduced to compensate the effects

This article addresses the formation control with obstacle avoidance for a mixed-order linear multi-agent in the ocean environment via a distributed optimal control approach. The considered system is comprised of unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs) and unmanned underwater vehicles (UUVs). A consensus control law for horizontal direction and height direction is then designed

Precious metal recovery is the main economic power of electronic waste (e-waste)1 recovery. The prediction of e-waste and its precious metal content is of great significance to the realisation of China’s circular economy. In this work, the generation mechanism of e-waste is firstly deduced to determine model characteristics suitable for its prediction. Fractional derivative grey models base on a weak

This paper presents a novel vibration signal fusion algorithm using improved empirical wavelet transform and variance contribution rate to fuse three-channel vibration signals for weak fault detection of hydraulic pumps. Firstly, empirical wavelet transform (EWT) is utilized to decompose the three-channel signals into several AM-FM components. Then in accordance with the statistical characteristics

A nonlinear sliding mode controller is proposed for a single stage grid-connected photovoltaic system with a novel nonlinear sliding surface. The proposed controller is designed to ensure maximum power extraction with unity power factor. There are two main advantages of the proposed sliding surface. The new surface will results in a first order sliding mode controller. The second advantage is that

This paper presents a simulation study and an experimental implementation of a single-phase Series Active Power Filter (SAPF) for the mitigation of harmonics in the load voltage. The aim is to regulate the injection voltage of the SAPF to compensate the grid voltage via the injection transformer in addition to maintaining the load voltage stable. The control strategies investigated in this work include

Real-time detection of early chatter is a vital strategy to improve machining quality and material removal rate in the high-speed milling processes. This paper proposes a maximum entropy (MaxEnt) feature-based reliability model method for real-time detection of early chatter based on multiple sampling per revolution (MSPR) technique and second-order reliability method (SORM). To enhance the detection

Increase of consumed energy is the dominating challenge in many industrial fields, especially in computer numerical controlled (CNC) machines. Reducing even a small amount of energy consumption in each facility can lead to a significant reduction in the world’s energy consumption. Control approaches, which are used to manufacture industrial parts using higher controller gains can generally enhance

This paper concerns with the issues of designing an improved-equivalent-input-disturbance (IEID) based robust two dimensional modified repetitive control (2D MRC) for a class of fuzzy systems in the presence of aperiodic disturbances. Specifically, IEID-estimator is implemented to the 2D MRC systems that estimates all types of disturbances and compensates them for assuring robust stability. In particular

Temperature variation will affect the prediction accuracy when using the near-infrared (NIR) analytical model to measure the viscosity of bisphenol-A. In order to correct the effect of temperature on the prediction performance of NIR model, a multilevel least-absolute shrinkage and selection operator (LASSO) is proposed in this paper. The multilevel LASSO algorithm combines LASSO with the multilevel

With the development of commercial application of unmanned surface vessels, the real-time collision avoidance is the research focus on the multi-vessels situation, the structure complexity and time consumption problem limit its efficiency. To simplify the complex model and enhance the collision avoidance performance, the field theory is used to describe the navigation of ships abstractly, from which

Grey theory-based time series models are widely used in various fields and disciplines. While most of the research is focused on the development and improvement of novel discrete-time models, very limited attention has been paid to the relationships among diverse models. The current paper proposes a methodological and practical framework to unify the single-variable, multi-variable, and multi-output

The current study concerns with the leader-following group consensus issue for discrete-time fractional-order multi-agent systems. The agents are assumed as fractional-order double-integrators. The interconnection among the agents is characterized by a bidirectional fixed graph. By considering some assumptions on the interaction graph, it is proved that leader-following group consensus will be realized

In this study, a new approach for time series based condition monitoring and fault diagnosis based on bidirectional recurrent neural networks is presented. The application of bidirectional recurrent neural networks essentially provide a viewpoint change on the fault diagnosis task, which allows to handle fault relations over longer time horizons helping in avoiding critical process breakdowns and increasing

Permanent Magnet Synchronous Motors (PMSMs) have recently been used commonly in all areas of the industry due to their position control as well as precise speed. The success of these motors in applications of precise speed and position control depends on their whole operation. Even if the fault is at a highly-low-level, this negatively affects the precision of the motor. In this study, the one dimensional

In this paper, a model predictive direct power control (MP-DPC) with power compensation and circulating current reduction is proposed for modular multilevel converter under unbalanced grid conditions. The main objectives of this paper are to achieve the circulating currents reduction and the power ripples elimination under unbalanced grid-side voltage conditions. In order to realize the aforementioned

This paper concerns with the robust stabilization of a perturbed linear time-invariant (LTI) single-input single-output (SISO) system based on event-based/ event-triggered sliding mode control (SMC) with logarithmic quantized state measurement. This technique is expected to reduce communication traffic in control networks with the assurance of robust stability against the quantization error and external

The paper proposes an integrated adaptive coordination technique for active front steering (AFS) and direct yaw moment control (DYC). The main contribution is to present an integrated multi-input multi-output (MIMO) adaptive control method to manage the variations of vehicle mass and tire-road friction coefficient as parameter uncertainties. The proposed integrated control strategy encompasses two:

In this paper, a novel memristive neural networks model is developed. In the new model, the states of memristors are related to the initial resistance of the memristors and the amount of charge flowing through them in a specific direction, which embodies the memory characteristic of memristors. As a consequence, parameters in the model vary continuously and cannot be determined by the states of neurons

This paper considers the reliable control problem for multiple trailing fixed-wing unmanned aerial vehicles (UAVs) against actuator faults and wake vortices. A distributed adaptive fault-tolerant control (FTC) scheme is proposed by using a distributed sliding-mode estimator, dynamic surface control architecture, neural networks, and disturbance observers. The proposed control scheme can make all trailing

Accurate sintering condition recognition (SCR) is an important precondition for optimal control of rotary kilns. However, the occurrence probability of abnormal conditions in the industrial field is much lower than normal, resulting in imbalanced class sintering samples in general. This significantly deteriorates the effectiveness of existing recognition models in abnormal condition detection. In this

A hierarchical hybrid control system is proposed to cope with highly automated driving in highway environments with multiple lanes and surrounding vehicles. In the high-level layer, the discrete driving decisions are coordinated by the finite-state machine (FSM) based on the relative position identification and predictive longitudinal distance of the surrounding vehicles. The low-level layer is responsible

In this research, to achieve the altitude and attitude tracking control of an underactuated quadrotor UAV with mismatched uncertainties, based upon Udwadia–Kalaba theory, a novel adaptive robust tracking control approach is proposed and which will be designed in two steps. First, aiming at the uncertain and underactuated quadrotor UAV, regardless of initial constraint deviation and mismatched uncertainties

In this paper, non-fragile fuzzy sampled-data control is used to analyze the dissipation of uncertain time-varying delay T–S fuzzy system under actuator saturation. First, this paper builds a novel augmented Lyapunov–Krasovskii functional that is more flexible. It involves complete information about the relevant sampled-data patterns. Second, the use of Wirtinger-based integral inequality and Newton–Leibniz

Efficiency and robustness in remaining useful life (RUL) prediction are crucial in system health monitoring. Thus, the internal logic computation of a Deep LSTM model for RUL prediction is mainly shaped and evaluated over a training data-set and its performance examined on a testing data-set. This paper proposes a framework for testing robustness of deep Long Short Term Memory (LSTM) architecture for

A decentralized adaptive quantized feedback tracking problem is addressed for uncertain interconnected nonlinear systems in a strict-feedback form. All local state variables for each subsystem are quantized by a hysteresis quantizer. Different from the existing results in the literature, the primary contribution of this study is to establish an adaptive control design and stability analysis strategy

This paper develops a trajectory tracking control design algorithm to be applied in unmanned aerial vehicles (UAVs). The strategy is simple but effective and it is based on linear algebra theory. The proposed approach reforms the column space of a system of linear equations at each sampling time to ensure the tracking objective when environmental disturbances appear. This new formulation ensures a

To accurately extract fault signatures from noisy signals, an improved orthogonal matching pursuit (OMP) with adaptive Gabor sub-dictionaries is proposed in this paper. Firstly, based on the optimal time–frequency characteristics of Gabor atom, the Gabor sub-dictionaries that adaptively change with the residual signals and have low redundancy are designed for signal sparse representations. Then, an

In this paper, a fault diagnosis (FD) and fault tolerant control (FTC) scheme is proposed for the leader–follower based multiple manipulator system with sensor fault under network communication topology. The learning observer is designed to obtain the fault information when the time-varying sensor fault occurs in follower manipulators. The synchronization error between the leader manipulator and the

This paper investigates the pole assignment stabilization with memory state feedback controllers for switched nonlinear time-varying delay systems. More general time-varying delays which depend on the subsystem number are considered. Based on novel common Lyapunov functions (CLFs), the aggregation techniques, the proprieties and the Borne–Gentina criterion, new algebraic stabilization criteria are

Multi-sensor data fusion (MSDF) is an efficient technology to enhance the performance of the system with the involvement of different kinds of sensors, which are broadly utilized in many fields at present. However, the data obtained from multi-sensors may have different degrees of uncertainty in the practical applications. Evidence theory is very useful to convey and manage uncertainty without a priori

Gear is a commonly-used rotating part in industry, it is of great significance to predict its failure in advance, which is helpful to maintain the health of the whole machine. Firstly, the isometric mapping algorithm is applied to construct the health indicator (HI) based on the statistical characteristics of gear. Then a novel variant of long-short-term memory neural network with attention-guided

The conventional Extended State Observer-Based Control (ESOBC) technique is mostly applicable to a class of Integral Chain Form (ICF) structure with the matched kind of single-channel lumped disturbances. However, the systems having the non-ICF structure with the multi-channel matched and mismatched lumped disturbances are widely prevailing in the control applications, where the conventional ESOBC

This paper focuses on tuning parameters of fractional order PID controller (FOPID) by using neural networks (NNs). For tuning the coefficients of the controller and orders of fractional derivative and integrator, five exclusive NNs are employed. Moreover, an emulator is used to identify the plant’s behavior. Extended Kalman Filter (EKF) algorithm is used to update the weights of the controller’s NNs

For the model plant mismatch (MPM) assessment of MPC systems, a correlation analysis method between the input and the disturbance (CAID) is proposed and is combined with model quality index (MQI) for its application in multivariable system. By deducing the input–output correlation coefficient variation law of adding independent variables in a function, the paper defines the CAID index of assessing

In the present work, impedance control of robot manipulators is enhanced. The controller is designed by using Szász–Mirakyan operator as Universal approximator. Although the Szász–Mirakyan operator has been extensively used for dealing with approximation of nonlinear functions, the main novelty of this paper is presenting a completely different application of Szász–Mirakyan operator. Since in robust

Traffic accidents are costing the world more than a million lives yearly alongside monetary losses, especially in the Gulf Cooperation Council region. This situation raised the need to examine potential risk factors contributing to traffic accident severities. In this paper, three data mining models were applied to provide a comprehensive analysis of risk factors related to traffic accidents’ severities