Three-phase four-leg inverters widely used in microgrid can effectively provide the power for the non-linear/unbalanced loads. Here, the non-linear composite controller is proposed for three-phase four-leg inverter system under reference frame by integrating a higher order sliding mode observer and finite-time control technique. The observer adopts the soft sensing manner to feedforward compensate external disturbances caused by current variation of AC bus node, which relaxes some physical constraints. Meanwhile, the higher order sliding mode observer realises the decoupling of the inverter system, which paves the way for the construction of the non-smooth finite-time control law. Finally, the simulation results with PI comparison illustrate the feasibility of the proposed method for improving the robustness, stability, and rapid recovery capability of system.

The rail pressure control in diesel high-pressure common rail (HPCR) system is considered as one of the key issues for precise control of fuel injection. This study investigates the application of generalised proportional integral observer (GPIO)-based control in diesel HPCR system. Firstly, a non-linear mathematical model of HPCR system which uses the metering unit as the actuator is established based on hydromechanics under some proper simplifications. Secondly, a GPIO is developed to estimate the mismatched disturbance caused by the injection process. Then a composite controller combining GPIO and backstepping control method is designed. By introducing the disturbance estimations into the control design process, the disturbance rejection capability of the system is promisingly enhanced. The effectiveness of the proposed control method is validated by the simulation results.

This article considers the robust control problem of non-linear magnetic levitation system with parameter uncertainties and external disturbance. To obtain a simple and practical controller that does not depend on the exact model information, a generalised-proportional-integral observer is constructed to estimate the velocity and disturbance. Then, based on mild assumptions and the estimated values, an output feedback tracking controller is proposed such that the reference position tracking task could be realised. The obtained control approach is confirmed strictly by theoretical analysis. Finally, simulation results are provided to show the effectiveness of the proposed control method.

This study studies the height and attitude tracking control problem of an unmanned helicopter system with disturbances. A composite controller based on the combination of harmonic disturbance observers and backstepping technique is proposed to achieve asymptotic tracking for height and attitude. Firstly, harmonic disturbance observers (HDOB) are designed to estimate the unknown disturbances affecting each channel. Then, a composite controller is proposed by integrating the backstepping control technique and the HDOB technique together to achieve the height and attitude tracking goal. Stability analysis of the closed-loop system is given. Finally, numerical simulations are presented to verify the efficiency of the proposed control scheme.

In the steel mills, in order to improve the circulation efficiency of iron ladles and steel ladles, save energy and promote the development of industrial automation, an iron ladles and steel ladles tracking management system based on radio frequency identification (RFID) and wireless local area network (WLAN) is proposed in this study. Meanwhile, to obtain the optimal number of online iron ladles, the theory of queuing is proposed for optimising the logistics of iron ladles. The system uses RFID and readers to obtain relevant location information. WLAN is used to realise communication between the crane terminals and the main control. Two queuing models are analysed and compared, then the optimal solution of online iron ladles is quantitatively calculated. Moreover, in order to intuitively reflect the on-site scheduling situation, a visualised operation interface is designed accordingly. The system has been used in a steel mill in Northeast China and achieved good performance.

Electrocardiogram is a comprehensive reflection of cardiac electrical activity on the surface of the body. It is of great research value to analyse ECG signals and diagnose heart diseases. Since the heartbeat process is a chaotic system, this study proposes a multi-fractal detrended fluctuation half-spectrum analysis method of short-term heart rate variability-y (HRV) signals from the perspective of non-linear dynamics, for patients with normal heart rate, sporadic heart rate variation and supraventricular rate, the heart rate mutation signal of patients with heart rate variation is calculated, and the statistical value distribution of multi-fractal parameter α has a certain change trend with the change of disease condition. The classification accuracy can reach >75% through box plot analysis.

A two-dimensional iterative learning PID control algorithm with Markov tuning method for batch reaction process is presented in this study. The learning algorithm with parameters tuned by Markov method can be explicitly tackling the repetitiveness of batch process, while achieve precise tracking of preset trajectory. It further shows that the control algorithm can guarantee convergence of the tracking error. Simulation results show that the parameters tuned by the Markov method can make the tracking error converge faster compared with the intimal control method.

It is difficult to detect end pose of auto electrocoating conveying parallel robot based on binocular vision because of less features, noise and blurred edges in image. So a pose detection method is presented. Firstly, according to distance and similarity between image points, the bilateral filtering is adopted to reduce noise. Secondly, for extracting straight lines on blurred edges and feature points in lines accurately, a Hough-K-means algorithm using K-means clustering analysis in parameter space after Hough transform is proposed. Thirdly, the discrete Gaussian–Hermite moment is used as feature descriptor to solve the low accuracy problem of principal directions of feature points described by speeded-up robust features (SURF) descriptor. The extracted feature points are selected according to the similarity metric between constructed feature vectors. Finally, the vision model is developed to calculate the three-dimensional pose parameters of parallel robot based on obtained point pairs. The experiment results show that, compared with the SURF algorithm, the average matching time decreases by 21.58%, the average deviations of detected poses in x, z and β decrease by 1.149 mm, 0.646 mm and 1.164° respectively by using the proposed method. The speed and accuracy of pose detection of parallel robot can be improved.

The method of spatial positioning and pose measurement using computer vision have been widely used in satellite docking, motion control systems, navigation and guidance areas. A monocular vision measurement method of the telescope's spatial pose based on infrared target was proposed for the crane sway during industrial driving. An experimental system for monocular vision measurement of the crane spreader was established. Through the corresponding relationship between the geometric position of the infrared light spots and the imaging projection, the non-linear optimisation iterative method was used to solve the spatial pose parameters that were converted into four spreader model parameters. The system was measured under static conditions and dynamic pendulum for accuracy and real-time analysis. The experimental results show that the system can meet the real time and accuracy requirements of the spatial pose measurement of the crane sway.

With the rapid development of the stereo garage, there are plenty of security problems appeared in stereo garage. The monitoring and management system of the stereo garage has attracted more and more attention. A cloud monitoring and management system for stereo garage is designed based on Web technology, which collects real-time data from the intelligent controller of the stereo garage, stores them in the cloud database. History and real-time data are studied to complete the functions of garage overview, real-time video monitoring, fault management, garage management, and system management. Deep confidence networks are proposed to conduct fault diagnosis for stereo garage, and the results are sent to the management interface of cloud portal (APP and website) for remote management. Test results show that the management efficiency of the stereo garage is significantly improved. The system guarantees the safe and reliable work of the stereo garage. It achieves better performance especially in the remote management and fault diagnosis.

The gesture recognition technology based on computer vision can provide a more natural way of human–computer interaction, and become a research hotspot in the field of gesture recognition. This study proposes an improved Sobel operator which is used for static hand contour extraction. The method is based on the noise existing in the picture, and a bilateral filtering algorithm is employed to denoise and preserve the edges to a large extent. Based on the colour space, the elliptical skin colour model is used to extract the skin colour domain, and the hand is separated according to the block domain feature. Finally, in order to solve the oblique indirection problem of the traditional Sobel operator, two oblique direction templates are added and the weights are reassigned. Then the improved Sobel operator is used to extract the gesture edges, and compared with the classical extraction edge operator Laplace and Canny extraction effects. The experimental results show that the proposed algorithm has high efficiency and accuracy in static gesture segmentation in a simple environment.

In this study, the Lohe model limited on smooth curved surfaces is investigated. A necessary and sufficient condition of equilibria is obtained. Also, it is proved that the synchronisation can be achieved if the initial states lie in a half part of the state space and the interconnection graph is strongly connected. Finally, a numerical example is given to validate the obtained theoretical results.

Considering the problems of internal and external disturbances, i.e. time-varying load, inaccurate system model and external uncertainties etc., a compound control strategy based on model predictive control (MPC) and non-linear extended state observer (ESO) are proposed to attenuate the output voltage fluctuation under continuous conduction mode (CCM) mode of the buck circuits. In addition, a non-linear ESO is used to observe all kinds of uncertainties caused by internal and external disturbances and to eliminate their effects by compensating these disturbances in the feed-forward channel. Compared with the pure MPC control, the simulation results show that the proposed composite control method has the better disturbance suppression effect and also can effectively improve the stability of the buck circuit.

In order to improve the operational efficiency and quality of small tractors, the original manual steering system needs to be renovated to include automatic steering functionality, which is the basis of autonomous navigation. Here, a modification method based on the steering circuit of a Dongfanghong SG250 tractor and a method to calculate the virtual steering angle is proposed. A small tractor steering model is established from the step response data of the system, and a PD controller for this model is also designed. The PD controller can also adapt to varying tractor speeds for optimal functionality in changing operational conditions, and a parameter optimisation approach for the speed-adaptive PD controller is proposed. Test results show that at a speed of 0.5 m s⁻¹, the steady-state error in the step response is 0.32°, the percentage error is 2.3%, the overshoot is 1.86°, and the percentage overshoot is 13.7%. For a ramp response, the average signal latency is 0.82 s and the steady-state error is 0.25°. The ability of the PD to adapt to changing speeds is also tested at different speeds. The results show that the steering system performs well.

A backstepping-based robust adaptive fault tolerant control (FTC) scheme is proposed for the altitude and attitude dynamic model of the medium-scale unmanned autonomous helicopter (UAH) subjected to external disturbance and actuator fault. The external disturbance and actuator fault are integrated into the medium-scale UAH altitude and attitude dynamic model. Since the actuator fault is uncertain in occurring time instant, the adaptive control approach is adopted to compensate for its negative effect. Meanwhile, the upper bound of external disturbance is estimated and the estimation is employed to design the controller. Based on the backstepping control technique, a robust adaptive FTC law is developed, which guarantees the desired system stability as well as the satisfactory tracking property. Simulation studies verify the effectiveness of the designed controller.

Considering the internal and external disturbances of the direct-driven wind energy conversion systems, i.e. multi-variable coupling, non-linear characteristic and modelling error, and the environmental disturbances, an adaptive sliding mode observer with active disturbance rejection control (ADRC) method for a direct-driven permanent magnet synchronous generator (PMSG) based wind power conversion system is proposed to track the maximum power point precisely. First, adaptive sliding mode observer based on phase-locked loop can effectively observe the rotor position information of PMSG, and weak the inherent chattering of traditional sliding mode. Second, ADRC can enhance the anti-disturbance ability when the system is under linear state feedback. Finally, the simulation results show that this method can estimate the rotor position exactly, and the system has the strong robustness and the optimum power tracking performance.

In this study, the dynamic model of bridge crane system is established based on Lagrange equation. The transfer function of crane running system is derived. A new crane anti-swaying scheme different from traditional mechanical anti-shake strategy is proposed and it is based on phase plane analysis algorithm. By the adaptive speed planning method, the industrial grade bridge crane can calculate different motion trajectories online without any off-line optimisation calculation under the given acceleration and maximum speed limit conditions. At the same time, the industrial grade bridge crane realises the purpose of anti-sway and positioning of the crane. The field experiment results show that the swing of the crane is obviously suppressed and the positioning accuracy fully meets the industrial requirements when the load of the crane reaches the target position.

In this article, a fault tolerant controller (FTC) based on back-stepping sliding mode is proposed for a quadrotor unmanned aerial vehicle (UAV) with single-rotor failure. According to the working mechanism of the quadrotor, the control system of UAV is divided into position subsystem and attitude subsystem. Then, the yaw control is abandoned because of the increased underactuation. The controller is designed by the back-stepping sliding mode control (BSMC). BSMC is robust to system uncertainties and external disturbances. Sliding mode reaching law is designed. Therefore, it can reduce system chattering. Based on the Lyapunov function method, the proposed FTC approach makes the faulty UAV stable and realises position control accuracy. Finally, simulation results show that the quadrotor UAV can reach the desired position and maintain the hover state, which verifies the effectiveness of the proposed method.

Here, classification of rice planthopper (RPH) based on shape descriptors was addressed to solve the low semantics problem of shape features in traditional RPH (mainly including the whiteback planthopper (Sogatella furcifera (Horváth)), the brown planthopper (Nilaparvata lugens (Stål)), and the small brown planthopper (Laodelphax striatellus (Fallén))) image classification research. Images of RPH were obtained from rice field by an automatic insect image acquisition device made by ourselves and insect images were divided into single images based on OTSU threshold segmentation algorithm. In terms of the images of RPH after segmentation, Fourier descriptors and Hu moments, which are from two aspects of contour curve and shape area, were extracted to describe shape features of RPH. Then, random forest (RF), an ensemble learning algorithm, was used as the classifier to distinguish RPH efficiently. The optimal number of trees and prediction variables of RF are chosen to be 150 and 4, respectively, by minimising the out-of-bag error. Experimental results show that classification accuracy of RPH based on shape descriptors reaches up to 93.93%. Therefore, it has been verified that the classification with the method presented here is accurate and semantic.

This article examines the position tracking difficulties of the electronic throttle (ET) system and presents a continuous finite-time terminal sliding mode (TSM) control method. The development of this control method involves two procedures: (i) designing a global finite-time observer to estimate the derivative and higher order derivatives of the ET system output, and the total disturbances; and (ii) construction of a continuous finite-time TSM controller based on observer estimations, to ensure the realisation of fast finite-time convergence of system output with a comparatively smooth control action. Comprehensive stability proof, simulation study, and experimental implementation are provided to affirm the applicability of the proposed method.

In this study, a novel disturbance observer-based (DOB) robust anti-disturbance tracking control problem is discussed for a kind of single-link flexible-joint manipulator with separate types of disturbances. On the one hand, a disturbance observer is imported to estimate the modelable disturbances. On the other hand, the introduction of performance index optimises the impact of unmodelled disturbances on the system. A DOB proportional-integral control input is proposed such that the stability of single-link flexible-joint manipulator can be ensured. Furthermore, the satisfactory disturbance rejection and attenuation performance with index can be obtained simultaneously. Finally, the simulation results verify this feasibility and effectiveness of the proposed control method.

In this study, dynamical neural networks (DNNs) are used as an online identifier for a class of non-linear systems with unknown actuator faults. By integrating the designed non-linear FD observer with adaptive regulation algorithm, the parameter coupling problem in DNNs can be successfully solved and the unknown actuator fault can be rejected simultaneously. Based on Lyapunov theory and convex optimisation algorithm, both the observation error and the identification error can be proved to convergent to zero. Finally, simulation examples for the non-linear systems with actuator fault are given to illustrate the effectiveness of the proposed approach.

The control of elevator running speed, real-time, and reliable transmission is the key parameters of the elevator, the traditional elevator speed control method cannot ensure the real-time reliability of elevator transmission parameters, reduce the elevator speed control accuracy. For this reason, a new elevator speed control method based on wireless sensor network is proposed. Introduces the wireless sensor network, gives the car terminal sensor node design process. The operating principle of the elevator is analysed, and the speed curve of the ideal elevator is obtained under the condition of satisfying the high efficiency and comfort. The elevator speed is regarded as the feedback signal, and the fuzzy proportion integral differential (PID) control of the elevator speed is completed through the deviation and deviation change rate between the ideal speed curve and the ideal speed curve. The experimental results show that the proposed method has high control accuracy and good robustness.

Rainy weather can greatly reduce the image quality and hinder the subsequent processing of the image. In order to achieve raindrop removal on rainy images, the single image raindrop removal method based on conditional generative adversarial networks (CGAN) is proposed. In this method, CGAN is used as the basic framework. The network receives the raindrop image as an additional condition information and adds Lipschitz constraint on the network. The network model is trained by the combination of condition adversarial loss, content loss, and perception loss to repair the raindrop area and reconstruct the image. The experimental results show that the proposed method has better raindrop removal effect than the existing algorithm and can avoid image blurring on the basis of ensuring the raindrop removal effect.

This study focuses on detailed analysis of disturbance for three-phase uninterruptible power supply (UPS) in reality, as well as design of active-disturbance rejection controller (ADRC) and simulation of the corresponding model with multi-disturbances. Parameters of LC-filter will change with UPS operation. Also, UPS not only has pure resistive load, but also resistive–inductive load, and sometimes even non-linear load. The authors take the above disturbance of uninterruptible power supply into consideration at the beginning. Then, according to the above analysis of disturbances, a mathematical model with disturbance term is established. After, the active-disturbance rejection controller is designed to depress the disturbances from internal part and external part. Finally, the corresponding simulation is conducted in order to verify the precision of modelling and the effectiveness of ADRC control strategy.

Aiming at the noise suppression of switched reluctance machine (SRM), the two-step commutation control method is improved. Combining this with pulse width modulation (PWM), the optimisation problem of the switching angle is studied and analysed and given a method to determine the turn-on angle, the zero-voltage turn-off angle and the turn-off angle of the negative bus voltage online. The control method is verified by MATLAB/Simulink simulation and experimental prototype platform. The results show that this method is simple and effective. It can achieve variable angle control, and can reduce the operating noise of the motor under different speed and load conditions. It has a high application value in the field of switched reluctance motor-type electric vehicle development.