This paper presents a hierarchical peer-to-peer-energy transaction model (P2P-ETM) considering the renewable energy preference. The model divides the characteristics of energy into normal and green energy. Green energy was assumed to be more expensive than normal energy, and prosumers and consumers considered in this model assumed that they have a preference for this green energy. Prosumer and consumer

Interval type-2 fuzzy logic controller (IT2FLC) owns good performance under uncertainty and nonlinearity environments while its optimization is hard and complicated. In this work, we propose an optimization method based on differential evolution with better and nearest option (NbDE) for interval type-2 fuzzy logic PID controller (IT2FL-PID-C) in order to control the position of hydraulic serial elastic

The paper presents an adaptive identification algorithm via data filtering and improved prescribed performance function for Sandwich systems with hysteresis nonlinearity. By developing a filter in which the filter is simple and easy to realize online and several variables, the estimation error vector can be derived. To improve the transient performance of estimator, a modified prescribed performance

In this paper, we propose an immersion and invariance-based sliding mode controller for a tilt tri-rotor unmanned aerial vehicle subjects to parameter perturbation, unmodeled dynamics, and external disturbances. The control scheme is divided into three parts, including the disturbance observer, the attitude controller, and the control allocation. Firstly, to alleviate the chattering and improve the

In this paper, a neural network-based robust anti-sway control is proposed for a crane system transporting an underwater object. A dynamic model of the crane system is developed by incorporating hoisting dynamics, hydrodynamic forces, and external disturbances. Considering the various uncertain factors that interfere with accurate payload positioning in water, neural networks are designed to compensate

In this paper, the distributed fixed-time formation-containment (DFTFC) problem of multiple Euler-Lagrange systems with parametric uncertainties and input disturbances is studied under directed graphs. First, a distributed fixed-time sliding-mode estimator is constructed to estimate the desired states of each robot with that only parts of followers can access the information of leaders. Next, based

Labor shortage and an aging population are driving automation in the aqua and agricultural industries. In a flatfish farm, it is important to sort flatfishes according to their sizes for effective and stable growth. This sorting is often done by human eye-estimation, thereby making it difficult to carry out total inspection of the fishes on the farm. Most fish graders in the industries sort round fishes

The dynamic H∞ feedback boundary control for a class of parabolic distributed parameter systems with a non-constant (spatially varying) diffusion rate is addressed in this paper. The observer-based controller is designed to deal with non-collocated sensors and actuators, and the H∞ performance index is employed to tackle the influence of the external disturbance and measurement noise. The resulting

This paper proposes a deep reinforcement learning (deep RL) method for simultaneously designing several notch filters in complex industrial servo systems. Notch filters are highly effective for suppressing resonances in motion control systems and are widely utilized in industry. However, severe limitations exist in complex servo systems because there are many vibration modes that are difficult to identify

In a dc microgrid, a conventional solution for the primary control is droop control, which is achieved by imposing a virtual impedance on each converter. Its main drawbacks are the current sharing inaccuracy and the voltage deviation. To address these problems, we propose a robust distributed cooperative controller, which is an alternative to the droop mechanism. The controller is distributed in the

The proportional-integral-derivative (PID) controller is standard technique for controlling the industrial batch process. However, the parameter tuning and updating of PID controller has been a challenging topic for control engineers especially for the real system having initial state error, state and output disturbances. In this paper, a kind of robust optimal iterative learning control (ILC) scheme

Dynamic compensation can improve the accuracy of trajectory tracking for industrial manipulators. For irregularly shape or flexible manipulators, however, it is difficult to measure the position of the center of mass (COM) so that its dynamic model cannot be expressed explicitly. This paper proposes a proportional derivative (PD) controller with radial basis function neural network based gravity and

This paper proposes a bidirectional Z-source dc-dc converter topology for the optimal utilization of renewable energy sources to the microgrid with the proposed control technique. Compared to the existing dc-dc converter circuits, they can reduce in-rush and harmonic current, provide larger range of output dc voltage and improve reliability. It can operate in voltage-fed and current-fed when the place

In this paper, we propose a novel distributed control scheme for a planar serial-link manipulator with revolute joints. The control scheme is based on the conventional model-based nonlinear control scheme that achieves linearization by feedback. A dedicated controller controls each joint of the manipulator, as in the case of the decentralized manipulator control scheme. However, in the proposed control

This paper tackles the problem of a discrete time N players game affected by some sort of time-varying uncertain perturbation. The philosophy of the uncertainty worst case scenario with respect to the i-player is developed to derive necessary and sufficient conditions for the existence of an Open Loop Robust Nash Equilibria. Such conditions are presented in terms of the solvability of a set of discrete

This paper investigates an adaptive finite time control scheme for wearable exoskeletons to realize trajectory tracking control. The main feature of the proposed scheme is model-free in which no dynamic models are required except for the input and output data. Firstly, a second order ultra-local model is employed to replace the complex dynamic model of wearable exoskeleton as the controlled object

In this paper, an adaptive sliding mode neural network(NN) control method is investigated for input delay tractor-trailer system with two degrees of freedom. An uncertain camera-object kinematic tracking error model of a tractor car with n trailers with input delay is proposed. Radial basis function neural networks(RBFNNs) are applied to approximate the unknown functions in the error model. A sliding

The low floor tram, which has been recently introduced, uses an independently rotating wheelset to achieve 100% low-floor structure and improve the running performance of curves. The independently rotating wheelset is designed to allow smooth curve driving by allowing the left and right wheels to rotate freely, allowing the outer wheels to rotate faster during sharp curves. As the rotational constraints

Currently, the application of mobile ground robots spans a range of fields from surveillance, search and rescue, exploration, agriculture, military among others. In unstructured and dangerous environments such as disaster scene, military fields or chemical spray in agricultural farms, the experience and intelligence of the operator are necessary for making complex decisions beyond the autonomy of the

This paper addresses the robot-assisted rehabilitation of back pain, an epidemic health problem affecting a large portion of the population. The design is composed of two springs in series connected to an end-effector via a pair of antagonistic cables. The spring and cable arrangement forms an elastic coupling from the actuator to the output shaft. An input-output torque model of the series-elastic

This article proposes an efficient integrated navigation algorithm to secure reliable navigation solutions in urban flight environments where satellite navigation is not available. Also, this study investigates a new sensor deployment and filter configuration that can perform real-time navigation onboard small drones by reducing the complexity and computational burden of the conventional point cloud-based

This paper focuses on the fundamental problems of linear quadratic gaussian (LQG) control and stabilization problems for networked control systems (NCSs) with unreliable communication channels (UCCs) where packet dropout, input delay and observation delay occur. These basic issues have attracted extensive attentions due to broad applications. Our contributions are as follows. For the finite horizon

In this paper, we propose the generalized modified Hermitian and skew-Hermitian splitting (GMHSS) approach for computing the generalized Lyapunov equation. The GMHSS iteration is convergent to the unique solution of the generalized Lyapunov equation. Moreover, we discuss the convergence analysis of the GMHSS algorithm. Further, the inexact version of the GMHSS (IGMHSS) method is formulated to improve

This paper investigates the problem of the finite-time synchronization of a class of coupled memristor-based recurrent neural networks (MRNNs) with time delays. Based on the drive-response concept and differential inclusions theory, several sufficient assumptions are given to ensure the finite-time synchronization of MRNNs. In order to realize the finite-time synchronization between the drive system

This paper presents a modified repetitive control scheme comprising of a state error and a control input via delayed feedback to track periodic reference trajectories and/or attenuate disturbances. The closed-loop state error dynamics can be represented using a typical neutral delay system with an exogenous input to be attenuated. The sufficient conditions to achieve overall stability and H∞ performance

In this paper, an adaptive terminal sliding mode control scheme for an omnidirectional mobile robot is proposed as a robust solution to the trajectory tracking control problem. The omnidirectional mobile robot has a double-frame structure, which adsorbes on the aircraft surface by suction cups. The major difficulties lie in the existence of nonholonomic constraints, system uncertainty and external

Most of adaptive iterative learning control (AILC) algorithms focus on one-dimensional (1-D) systems, rather than two-dimensional (2-D) systems. This brief is first concerned with AILC for 2-D nonlinear discrete time-varying Fornasini-Marchesini system (NDTVFMS) with nonrepetitive reference trajectory under iteration-varying boundary states. By using Lyapunov analysis method, it can guarantee that

This paper addresses the formation tracking control problem of multiple underactuated unmanned surface vehicles. Considering many actual situations, a practical formation control scheme, which is performed by using a leader-follower approach, minimum learning parameter technique, adaptive technology and so on. Firstly, a virtual unmanned surface vehicle is designed according to the location information

This paper aims to provide a generic robust controller that is able to manipulate all kinds of quadrotor unmanned aerial vehicle (UAV) systems automatically or adaptively in the presence of severe parametric uncertainties and fully unknown external disturbance. The dynamic model of the quadrotor is first obtained using Newton-Euler equations. Then, considering the underactuated and the strongly coupled

Nonlinear dynamical and time varying parameters of the permanent magnet synchronous generator (PMSG), make it difficult to control. This paper presents a new passivity-based control (PBC) of tidal turbine based PMSG, connected to the grid through a back-to-back converter. The control problem is challenging for at least two reasons. First, the dynamics of the conversion system are described by a highly

In this paper, we consider a problem of global stabilization for a class of approximately feedback linearized nonlinear systems. In order to handle more nonlinearity over the existing results, we provide a new feedback controller with two gain-scaling factors and we show that more nonlinearity can be treated by our control scheme. Moreover, we analytically show that the considered nonlinear systems

Advances in convolutional neural networks (CNNs) have driven the development of computer vision. Recent CNN architectures, such as those with skip residual connections (ResNets) or densely connected architectures (DenseNets), have facilitated backpropagation and improved the performance of feature extraction and classification. Detecting objects in underwater environments by analyzing sound navigation

This study develops an autonomous vehicle control method that enables it to perform a drift maneuver which is an expert driving technique consisting of sliding the rear wheel intentionally for fast cornering. By developing an autonomous control algorithm for such an agile maneuver, the safety of the future autonomous vehicle on extreme conditions such as slippery road, will be increased. Drift equilibrium

In this paper, we present two adaptive control approaches to handle uncertainties caused by parametric and modeling errors in a class of nonlinear systems with uncertainties. The methods use the Port-controlled Hamiltonian (PCH) modelling framework and the interconnection and damping assignment passivity-based control (IDA-PBC) control design methodology being the most effectively applicable method

This paper is mainly dedicated to the challenging issue of fixed-time attitude control for a flexible spacecraft in the presence of actuator faults, external disturbances and coupling effect of flexible modes. The attitude controller is developed by employing a fixed-time nonsingular terminal sliding mode under which the convergence time is bounded and independent of the initial states. This robust

In order to reduce the influence of time-varying disturbances for magnetic levitation system, we propose a reduced-order generalized proportional integral observer (RGPIO) based continuous dynamic sliding mode control scheme for magnetic levitation system in this paper. Unlike the popular extended state observer (ESO), it could deal with constant or slowing varying disturbances from theoretical point

This paper proposes a neural approximation based model predictive control approach for tracking control of a nonholonomic wheel-legged robot in complex environments, which features mechanical model uncertainty and unknown disturbances. In order to guarantee the tracking performance of wheel-legged robots in an uncertain environment, effective approaches for reliable tracking control should be investigated

This paper studies the reliable H∞ control on stochastic delayed Markovian jump systems (SDMJSs) with asynchronous jumped actuator failure and uncertain transition rates (TRs). It is assumed that the actuator failure occurs randomly under a Markov process with its jumping mode different from the system’s one. A generalized functional Itô’s formula for the closed-loop SDMJSs with mixed asynchronous

In this paper, the topic of sampled-data based dissipativity control for Takagi-Sugeno (T-S) fuzzy Markovian jump systems with incomplete transition rates and actuator saturation is addressed. First of all, by constructing an appropriate two-sided closed-loop function that captures the realistic information of sampling pattern, together with the free-matrix-based inequality approach, a sufficient condition

This study investigates a new fractional-order nonsingular terminal sliding mode control (FTSMC) leveraging a finite-time extended state observer, a simpler prescribed control, and hybrid grey wolf optimization (GWO) combined with whale optimization algorithm (WOA) for manipulator systems. The new FTSMC system is based on an improved fractional-order terminal sliding surface. Initially, the study experimentally

In this paper, an event-triggered extended dissipative control problem for networked singular systems is investigated, where the extended dissipativity analysis unifies the H∞ performance, L2 − L∞ performance, passivity, (Q, S, R)-dissipativity in one framework. Under the event-triggered scheme, the closed-loop system is modeled as a time-delay system. Some sufficient conditions for extended dissipativity

This paper proposes positioning and trajectory tracking for Caterpillar Vehicles (CVs) in unknown environments. To do these tasks, the following are performed. Firstly, a system modeling of the Caterpillar Vehicle is presented. Secondly, solving the complicated tracking control problem in unknown environments is a challenging mission. Therefore, to guarantee the Caterpillar Vehicle system to be strong

In this paper, a robust control scheme using back-stepping and α-filter-based uncertainty and disturbance estimator (UDE) is designed for flexible air-breathing hypersonic vehicle (FAHV) in the presence of severe external disturbances. Firstly, with the aid of back-stepping technique, the longitudinal dynamics of FAHV is separated into velocity and altitude subsystems. Feedback linearization (FL) is

This paper presents a control strategy to enhance the lateral dynamics stability and handling performance of the four-wheel independently actuated (FWIA) electric vehicles (EVs). The vehicle longitudinal velocity uncertainty and controller saturation are considered, a double layers control scheme is adopted. In the upper layer, the homogeneous polynomial parameter-dependent approach is introduced to

This paper deals with the identification problem of discrete-time linear time-invariant errors-in-variables systems for the case of the colored output noise. Based on the correlation analysis, the multi-innovation theory is introduced to the errors-in-variables systems where both input and output data are noisy. A correlation analysis-based multi-innovation stochastic gradient algorithm and a correlation

In view of the fact that the vibration displacement system of continuous casting mold driven by a servo motor requires the motor rotate in a certain fixed direction, a compound control scheme combining feedforward and feedback control is proposed in this paper. In controller designing, there are mainly two issues to be considered: i) constraint condition that the servo motor rotates in a fixed direction

This paper presents a practical time-optimal and smooth trajectory planning algorithm and then applies it to robot manipulators. The proposed algorithm uses the time-optimal theory based on the dynamics model to plan the robot’s motion trajectory, constructs the trajectory optimization model under the constraints of the geometric path and joint torque, and dynamically selects the optimal trajectory

This letter investigates the variance of state dimensions of linear discrete dimension-unbounded systems, which are a class of cross-dimensional systems. First, the dimensional relationship of states, initial values and system matrices of some special cases is discussed. Then, for the general case, to directly calculate the transition time and state dimensions after the transition time, an algorithm

In this paper, a hybrid protocol which can control multi-agent systems to achieve “leader-following consensus” is proposed, the control protocol is periodic and is composed of continuous control and impulse control. Considering the power limitation and the time error of the actual industrial production equipments, the impulse saturation effects and the impulse time window are introduced. In this paper

In this paper, fractional calculus theory is employed to inspect a finite time fault tolerant controller for robotic manipulators in the presence of uncertainties, unknown external load disturbances, and actuator faults, using fractional-order adaptive backstepping approach in order to achieve, fast response and high-precision tracking performance. Knowing the advantages of adaptive controllers an

A disc-type underwater glider (DTUG) has a highly symmetrical full-wing shape that allows it to move omnidirectionally and have the same hydrodynamic characteristics in all directions in the horizontal plane. These characteristics make the viscous hydrodynamic coefficients measured by conventional methods unsuitable for simulating the omnidirectional and steering motions of the DTUG. To further reveal

This paper focuses on an observer-based output-feedback controller design for a nonlinear discrete-time system. The major characteristics of this system is that all of the subsystems are in strict-feedback form and all the states of the system are not measurable. An output tracking control problem is firstly considered in this paper. NNs are utilized to approximate unknown functions, while a state

In this paper, an interval estimator is designed for discrete sequence systems (DSSs) with delayed measurements. In order to reduce network transmission burden and prevent data collision, the round-robin (RR) protocol is employed to schedule the transmission order of the nodes. The purpose of the problem addressed is to design a novel interval estimator consisting of two coupled sub-estimators for

Accurate underwater navigation systems are required for closed-loop guidance and control of unmanned underwater vehicles (UUV). This paper proposes a sensor-based hybrid translational observer concept for underwater navigation using the hybrid dynamical systems framework, accounting for noisy, asynchronous and sporadic sensor measurements. Sensor measurements from an acoustic positioning system, a

At present, switched reluctance motors (SRM) become very interesting for many industrial applications in variable speed control. For such systems, the linear quadratic regulator with integral action (LQI) method is commonly used when using plants in state spaces due to its robustness and easy adjustment. All methods from the linear quadratic regulator (LQR) project provide a weighting of the Q and

This paper deals with the fixed-time group consensus problem for multi-agent systems (MASs) subjected to exogenous disturbances. Firstly, two pinning control algorithms are constructed for MASs, which not only reduce the number of controllers but also achieve expected tracking consensus. Secondly, fixed-time group consensus is ensured by utilizing the algebraic graph theory, Lyapunov stability and

In this paper, the problem of robust mixed H2/H∞ control is studied for an uncertain wireless sensor network (WSN) systems with random time delay, packet loss and sensor faults. A system model is established based on the characteristics of uncertain time delay and packet loss in WSN. In this model, system uncertainties are represented by random time delay and stochastic packet loss, which are described

In this paper, a model predictive control algorithm is developed for the regulation problem of a biaxial feed drive system. The orthogonal error component in the moving frame is considered as an approximation of the real contour error. Then, the control policy is derived from the worst-case optimization of a quadratic cost function, which penalizes transformed errors, velocity errors and control variables

In this paper, we investigate the state estimation, unknown input and measurement noise reconstruction problems and the feedback controller design issues for a linear discrete-time system with both unknown inputs and measurement noises. First, an augmented system is constructed and the state vector of the augmented system consists of the original system state and the measurement noise, and the preconditions

Generally, stiffness and impedance control schemes require knowledge of the location of any object with which a robot interacts within its workspace; therefore, the integration of a computer vision system within the control loop allows us to know the location of the robot end effector and the object (target) simultaneously. In this paper, a generalized and saturating vision-based stiffness controller