The modern advanced aero-engine control methods are onboard dynamic model–based algorithms. In this article, a novel aero-engine dynamic modeling method based on improved compact propulsion system dynamic model is proposed. The aero-engine model is divided into inlet, core engine, surge margin and nozzle models for establishing sub-model in the compact propulsion system dynamic model. The model of

Aiming at the maximum power point tracking for wind turbine, a sensorless intelligent second-order integral sliding mode control based on wind speed estimation is proposed in this article. The maximum wind energy capture is realized by controlling permanent magnet synchronous motor to adjust the speed of wind turbine. First, an intelligent second-order integral sliding mode control is designed for

This article develops a distributed adaptive fault-tolerant formation control scheme for the multiple unmanned aerial vehicles to counteract actuator faults and intermittent communication interrupt, where the issues on control input saturation and mismatched uncertainties are also addressed. The discontinuous communication protocol technique is exploited to achieve the stability of the formation system

At the request of the author, with the agreement of the Journal Editor, the following article has been retracted.

In this article, an adaptive radial basis function neural network scheme for trajectory tracking control of surface vehicles is proposed. Under complex uncertainties, the proposed controller is designed by combining radial basis function neural network and finite-time control algorithm. Using the novel controller, the stability of accurate trajectory tracking can be ensured and the robustness of control

Vernier-gimballing magnetically suspended flywheel is often used for attitude control and interference suppression of spacecrafts. Due to the special structure of the conical magnetic bearing, the radial component generated by the axial magnetic force and the change of the magnetic air gap will cause the nonlinearity of stiffness and disturbance. That will lead to not only poor stability of the suspension

This article focuses on accurate identification of the critical moving characteristics of the high speed on/off valve. Typically, there are two strategies for identifying the critical moving characteristics, including calculation strategy based on force balance and strategy for detecting the coil current’s certain points. However, the accuracy of the two above strategies needs to be improved. Therefore

Model-free adaptive control has been developed greatly since it was proposed. Up to now, model-free adaptive control theory has become mature and tends to be an effective solution for complex unmodeled industrial systems. In practical industrial processes, most control systems are inevitably accompanied by noise that will result in indelible error and may further cause inaccurate feedback to the output

Shape memory alloys are among the highly applicable smart materials that have recently appealed to scientists from various fields of study. In this article, a novel shape memory alloy actuator, in the form of a rod, is introduced, and an adaptive model predictive control system is designed for position control of the developed actuator. The need for such an advanced control system emanates from the

Delta parallel robot is widely used in the manufacturing process of food, medicine, electronics and military industries, which is a highly nonlinear system with strongly uncertain dynamics. Therefore, there are many difficulties in the controller design of delta robot. Based on the simplified dynamic model, a nonlinear PD+ controller with nonlinear disturbance observer is proposed for Delta parallel

This article deals with the distributed filtering problem for a class of discrete-time Markov jump systems over sensor networks. First, in the distributed filtering network, each local filter simultaneously fuses the estimation and measurement from itself and neighboring nodes to achieve the system state estimation. And each sensor intelligent node is embedded with an event-triggered sampling mechanism

This article presents a novel identification approach which can deal with nonlinear and time-varying characteristics of complex dynamic systems, especially an aerial vehicle in the entire flight envelope. A set of local sub-models are first developed at different operating points of the system, and subsequently a self-organizing multi-model ensemble is introduced to aggregate the outputs of the local

In this article, a real-time road-Object Detection and Tracking (LR_ODT) method for autonomous driving is proposed. This method is based on the fusion of lidar and radar measurement data, where they are installed on the ego car, and a customized Unscented Kalman Filter is employed for their data fusion. The merits of both devices are combined using the proposed fusion approach to precisely provide

Some autonomous navigation methods, when implemented alone, can lead to poor performance, whereas their combinations, when well thought out, can yield exceptional performances. We have demonstrated this by combining the artificial potential field and fuzzy logic methods in the framework of mobile robots’ autonomous navigation. In this article, we investigate a possible combination of three methods

This article proposes a new H∞ sliding mode control strategy for stabilizing controller design for fractional-order Markovian jump systems. The suggested approach is based on the diffusive representation of fractional-order Markovian jump systems which transforms the fractional-order system into an integer-order one. Using a new Lyapunov–Krasovskii functional, the problem of H∞ sliding mode control

This article investigates the command filtered adaptive neural tracking control for uncertain nonlinear time-delay systems subject to asymmetric time-varying full state constraints and actuator saturation. To stabilize such a class of systems, the radial basis function neural networks and the backstepping technique are used to structure an adaptive controller. The command filter is utilized to overcome

In view of the problems that the analytical inverse system decoupling method of bearingless induction motor is sensitive to the change of motor parameters and is greatly affected by unmodeled dynamics, and that of traditional proportional–derivative controller lacking the self-adaptive regulation ability, a neural network inverse system decoupling fuzzy self-tuning proportional–derivative control strategy

This article establishes an innovative and general approach for the dynamic modeling and trajectory tracking control of a serial robotic manipulator with n-rigid links connected by revolute joints and mounted on an autonomous wheeled mobile platform. To this end, first the Gibbs–Appell formulation is applied to derive the motion equations of the mentioned robotic system in closed form. In fact, by

In this article, a novel vision-based automatic liquid filling control system is proposed. The method can be used for many high-viscosity liquid filling applications, especially for packaging of fuel tank sealant in the aerospace industry. Due to the high viscosity and highly adhesive properties, filling and packaging this type of liquid can have challenges in terms of time and cost. A new control

Hydropower system has great attention due to the cheapest and simplest renewable power generation, available potential and environmental concern. Francis turbine has wide operating range compare to other hydro turbine runner. Electrohydraulic Francis turbine inlet guide vane system has advantages like, high power density, self-lubrication property, very good controllability and rugged. Francis turbine

Losses in control valves drag down the average overall efficiency of electrohydraulic systems to only about 22% from nearly 75% for standard pump-motor sets. For achieving higher energy efficiency in slower systems, direct pump control replacing fast-response valve control is being put in place through variable-speed motors. Despite the promise of a quicker response, displacement control of pumps has

Most control methods deployed in lower extremity rehabilitation robots cannot automatically adjust to different gait cycle stages and different rehabilitation training modes for different impairment subjects. This article presents a continuous seamless assist-as-needed control method based on sliding mode adaptive control. A forgetting factor is introduced, and a small trajectory deviation from reference

This article presents the control synthesis of robotic manipulators with an unknown constant payload. A novel nonlinear disturbance observer with an adaptive scheme is designed to estimate the external force induced by the unknown constant payload. A general design procedure for designing the gain of the nonlinear observer is developed rather than the time-consuming trials and error to choose proper

This article presents robust stabilization and tracking control problems for multi-input multi-output Hammerstein model with external disturbances. This model is characterized by static nonlinear elements followed by a linear dynamic block. Moreover, the unknown parameters of the identified mathematical model are estimated using the multivariable output error state space subspace algorithm. Unlike

In this study, the problem of finite-time stability and boundedness for parabolic singular distributed parameter systems in the sense of L2 norm is investigated. First, two new results on L2 norm-based finite-time stability and finite-time boundedness for above-mentioned systems, inspired by the light of partial differential equations theory and Lyapunov functional method, are presented. Then, some

In this article, an adaptive neural network is proposed for the tracking control problem of unknown nonlinear interconnected systems with inaccessible states and sensor delays based on dynamic surface strategy. The system has unknown nonlinearities and immeasurable states. Thus, a neural network state observer based on delayed outputs of subsystems is applied. The main difficulty in obtaining local

Control system performance assessment is significant, especially in practical applications. One of the most important indices for the performance assessment of control systems is minimum variance. Calculating the minimum variance index in multivariate systems requires prior knowledge of system parameters and models, and is therefore an obstacle in practical applications. In this article, an index is

This article focuses on the design of event-triggered asynchronous H∞ fault-tolerant controller for Markov jump system subject to actuator faults and external disturbances. The asynchronization phenomenon not only occurs between the controlled system and controller but also exists between the controlled system and faulty actuator, which are portrayed as two corresponding hidden Markov models. Moreover

Raw meal fineness is the percentage content of 80 µm sieving residue after the cement raw material is ground. The accurate prediction of raw meal fineness in the vertical mill system is very helpful for the operator to control the vertical mill. However, due to the complexity of the industrial environment, the process variables have coupling, time-varying delay and nonlinear characteristics in the

Simultaneous localization and mapping is very essential for autonomous navigation when the mobile robot is navigating in unknown environment without a global positioning system. Various techniques to solve the simultaneous localization and mapping problem have been extensively studied using the combination of low-cost sensors. Most of the work in mobile robotics still consists of finding solutions

The dynamic characteristics of reciprocating pump–pipeline system are directly affected by the fluid–mechanism dynamic interaction related to the slider-crank mechanism, valves and pipes conveying fluid. In this article, the fluid–mechanism interaction and nonlinearities involved in the kinetic of slider-crank mechanism, the motions of pump valves and the dynamic transmission in pipeline are explored

The exhaustive and irresponsible use of fossil fuels has created numerous public and environmental health issues in the past few decades. To address this issue, this work has investigated the use of polanga (Calophyllum inophyllum) biodiesel/diesel blends in a diesel engine. This study focuses primarily on the optimization of performance and emission characteristics of a diesel engine fuelled with

This article presents a set of algorithms for the estimation of state of charge, specifically deployed for lithium-ion batteries. These algorithms are based on appropriate battery models. These models can be developed having different levels of accuracy, also including the possibility to correctly represent the hysteresis voltage behaviour of the selected lithium cells. In addition, different identification

With the wide application of robots in the material distribution process on the assembly lines, single robot scheduling cannot meet the actual production needs. However, the high degree of mechanization also brings about environmental problems. Therefore, this article aims to develop a scheduling methodology to accomplish material supply tasks using multiple robots with energy consumption consideration

The pulverised coal and its mixture with biomass are one of the most popular fuels in industrial energy. To ensure, on one hand, minimal greenhouse gas emission and, on the other hand, maximum energy production efficiency, it is necessary to monitor the combustion process of these fuels. One way to do this is to monitor the flame intensity. This is an optical, non-invasive solution, and information

In this study, a novel fuzzy logic–based decision support system approach to provide assistance in the selection of suitable input shaping techniques is presented. The proposed approach selects the suitable input shaping technique for point-to-point motion type of systems such as precise positioning, crane operations, flexible robotic systems and so on. The problem solution addressed is the selection

This article introduces a unified Hamiltonian formulation for controlling grid-connected direct current microgrid via interconnection and damping assignment–passivity-based control. The direct current microgrid includes hydro–solar–wind hybrid renewable energy systems and battery/supercapacitor hybrid energy storage system. Hybrid renewable energy systems are integrated as a disturbed direct current

In this article, to improve the accuracy of rotor position estimation in sensorless permanent magnet synchronous motor drives, a reduced-order resonant regulator for the rotor position sliding mode observer is proposed. Since fundamental back electromotive force can be utilized to calculate the rotor position, a mathematical model for the observer is first established based on the analysis of estimation

The environmental adaptability of autonomous underwater vehicles is always a problem for its path planning. Although reinforcement learning can improve the environmental adaptability, the slow convergence of reinforcement learning is caused by multi-behavior coupling, so it is difficult for autonomous underwater vehicle to avoid moving obstacles. This article proposes a multi-behavior critic reinforcement

In most applications of autonomous navigation, the state of a system must be estimated from noisy sensors. Accurate estimation of the true system state can be achieved using data fusion algorithms. Furthermore, the fusion scheme can be affected by many factors such as modeling errors and parameters uncertainties. The gaps and inconsistencies due to the sensors noise and modeling errors can be reached

This article presents a comparative study between the performances of different energy management strategies for hybrid energy storage source supplying electric vehicle. In our case, the hybrid supply is composed of fuel cell as an energy source and lithium-ion batteries as a power buffer. The two storage systems are connected to the DC bus via DC/DC boost converters. The used management strategies

The active control of a suspension system is meant to provide an isolated behavior of the system spring-mass (for example, increased comfort and performance). During this article, we are going to explain the importance of developing an intelligent control approach for active truck suspensions based on the artificial neural network. From where the main objective of this article is to obtain a mathematical

This article considers finite-time bounded controller design for one-sided Lipschitz nonlinear differential inclusions. Sufficient conditions of finite-time bounded criterion are given employing convex hull Lyapunov function approach. An algorithm is designed to calculate the finite-time bounded controller. Moreover, a system initial state selection method is presented to find the domain of system

A novel active suspension control strategy is introduced to improve dynamic response of vehicle suspension systems. The proposed algorithm is a fusion of classical controller design methods together with an online observer and is based on the cancelation of system disturbances. The operational calculus method and the differential algebraic theory are applied to build the observer/compensator that is

In real-time hybrid testing, systems are separated into a numerically simulated substructure and a physically tested substructure, coupled in real time using actuators and force sensors. Actuators tend to introduce spurious dynamics to the system which can result in inaccuracy or even instability. Conventional means of mitigating these dynamics can be ineffective in the presence of nonlinearity in

This article presents an estimator-based nonlinear robust optimal controller for an active prosthetic leg for transfemoral amputees. The proposed controller is derived from a combination of the state-dependent Riccati equation technique to optimize the energy consumption of the robot/prosthesis system and the sliding mode control to reduce the effects of the model parametric uncertainties and ground

This article details a new Model Predictive Control algorithm ensuring robust stability and control feasibility for uncertain nonlinear multi-input multi-output dynamical systems considering uncertain time-delay effects. The proposed control algorithm is based on construction of a Lyapunov–Krasovskii functional as terminal cost. Incorporation of this terminal cost into the Model Predictive Control

The control of twin rotor multi-input multi-output system is difficult as it is subjected to model uncertainties and external disturbances. Furthermore, there also exists a coupling between pitch and yaw positions, which makes the system more difficult to control them separately. Considering the above difficulties in twin rotor multi-input multi-output system control, H∞-based robust controller is

A new adaptive time delay estimation technique with sliding mode control method is proposed and investigated in this passage for cable-driven manipulators. Time delay estimation technique is an effective tool to compensate for unmodeled dynamics and unknown disturbance, and adaptive time delay estimation performs better due to its adaptive control gain. The proposed adaptive method is based on the

Trajectory tracking in upper limb rehabilitation exercises is utilized for repeatability of joint movement to improve the patient’s recovery in the early stages of rehabilitation. In this article, non-linear active disturbance rejection control as a combination of non-linear extended-state observer and non-linear state error feedback is used for the sinusoidal trajectory tracking control of the two-link

This research is concerned with the problem of parameter identification for ship response model. A novel nonlinear innovation–based algorithm is proposed by use of the hyperbolic tangent function and the stochastic gradient algorithm. In order to demonstrate the validity of the algorithm, two identification experiments are adopted by the “Galaxy” ship and the “Yupeng” ship. Furthermore, the comparison

Modular satellite, which has the ability of self-repairing and accomplishing different tasks, draws more and more satellite designers’ attention recently. One of the trending topics is to design the algorithm of self-reconfigurable path planning, since searching a near-optimal path is an effective way to reduce electrical energy consumption and mechanical loss of satellites. A major thrust of this

In the field of underwater image recognition, a chip with smaller footprint and lower energy consumption is required to be implanted into autonomous intelligent underwater vehicle to make real-time response to the surrounding objects. Therefore, a promising accelerator with high performance and low energy consumption is designed, which optimizes the features possessed by convolutional neural network

Aiming at the problems of inaccurate fault detection and error alarm in the process of hot strip mill process, a fault detection scheme of canonical independent component analysis is proposed. The new scheme first uses canonical variable analysis to calculate the canonical variable matrix of observation data, which effectively solves the problem of autocorrelation and cross-correlation. Then the canonical

It is almost impossible to detect the health status of the aircraft hydraulic system via a single variable, because of the complexity and the coupling relationship between components of the system. To serve the purpose, a novel anomaly detection method considering multivariate monitoring data is proposed in this article. The unsupervised auto-encoder model with the long short-term memory layers is

The aim of this study was to design a first-order sliding mode controller for dual AC/DC/AC power converters to regulate the production of a corona discharge ozone generator. The design is presented in the two following parts: (a) The first part regulates a three-branch (phase) AC/DC converter to control the DC intermedium voltage that is required to produce the desired ozone concentration, while (b)

In four-motor servo systems, actuator failures influence control performance seriously through huge inertia ratio changes and unknown disturbances. To solve this problem, an adaptive fault-tolerant control scheme based on characteristic modeling and extended state observer is proposed. First, an adaptive sliding mode observer is designed as fault detection part and offers motor information for controller

Determination of optimum cutting parameters is one of the most essential tasks in process planning of metal parts. However, to achieve the optimal machining performance, the cutting parameters have to be regulated in real time. Therefore, utilizing an intelligent-based control system, which can adjust the machining parameters in accordance with optimal criteria, is inevitable. This article presents

There is growing interest in recycling and re-use of electric vehicle batteries owing to their growing market share and use of high-value materials such as cobalt and nickel. To inform the subsequent applications at battery end of life, it is necessary to quantify their state of health. This study proposes an estimation scheme for the state of health of high-power lithium-ion batteries based on extraction

This article considers the trajectory tracking control for unmanned surface vessels with unknown time-variant external disturbances and input saturation. The strategy mainly consists of event-triggered reset sub-controller and nonlinear disturbance observer–based compensation sub-controller. To reduce network transmissions, and in the meanwhile, guarantee the desirable closed-loop behavior, the event-triggered