Xiaofang Yuan

Hunan University · College of Electrical and Information Engineering

When the autonomous vehicle (AV) is under various road friction and speed, emergency collision avoidance is extremely difficult. In this situation, the AV may encounter severe understeering problem, so it is hard to achieve collision avoidance, even under the control of active safety system. To tackle this problem, an adaptive collision avoidance s...

Due to the energy-consumption efficiency between up-slope and down-slope is hugely different, a path with the shortest length on a complex off-road terrain environment (2.5D map) is not always the path with the least energy consumption. For any energy-sensitive vehicles, realizing a good trade-off between distance and energy consumption on 2.5D pat...

Path planning is a crucial technology for autonomous vehicle (AV). However, it is difficult to adapt to dynamic driving environment, and AV may lose lateral dynamic stability due to high speed and various friction. This paper presents an adaptive dynamic path planning method (ADPPM) for AV to address the challenges. The ADPPM is comprised of three...

The rapid development of intelligent connected technologies and cellular vehicle-to-everything communication (C-V2X) provide new opportunities to solve the connected automated vehicle (CAV) traffic problem for eco-driving at continuous signalized intersections. With C-V2X, a hierarchical velocity optimization design based on hybrid model predictive...

Estimating the 6-D pose of an object is a vital and challenging task for robot vision systems in industrial robotic grasping. With the wide use of 3-D cameras, the additional acquired depth image provides geometric information of the scene to increase the pose estimation performance but leads to a challenge, fully leveraging the two-modal data, the...

Three-phase current is the cornerstone parameter in vector control. Restricted by minimum sampling time of the traditional space vector pulse width modulation, the problem of immeasurable areas (IAs) exists in one DC bus current sensor (ODBCS) three-phase current reconstruction. In addition, affected by actual conditions such as temperature drift,...

Path planning has received more and more attention due to its indispensability in autonomous vehicle (AV). Generally speaking, the stability of AV is not fully considered in path planning, therefore, the planned path may be detrimental for maintaining the stability. And this problem is even more acute for roll stability in complex 3D environment, s...

Hybrid energy storage systems are widely used in electric vehicles and other fields. Focused on the problem of lithium‐ion battery life attenuation caused by high‐frequency components in load power requirements, a closed‐loop Haar wavelet power splitting method is proposed. First, the circuit structure of the hybrid energy storage system is introdu...

Path planning is the research hotspot of automatic driving technology. However, it is hard to ensure path safety for autonomous vehicle (AV) under multiple obstacles with various velocities. To solve this problem, an adaptive velocity region-based path planning system (AVR-PPS) which includes two parts, an adaptive velocity region controller (AVRC)...

In the 3-D path planning, the undulation of terrain have a significant impact on the roll angle of autonomous vehicle (AV). However, the existing 3-D path planning methods rarely consider the roll angle, which may lead to the rollover of AV. To solve this problem, a 3-D path planning system considering the rollover and path length (3DPPS-CRPL) is p...

In the study of obstacle avoidance for autonomous vehicle (AV), the moving direction of obstacle is generally the same as that of AV. But in actual situation, the moving direction of obstacle is various, which may lead to collision phenomenon of AV. To solve this problem, a dynamic estimation-based obstacle avoidance system (DEOAS) which includes t...

Traditional reactive power optimization mainly considers the constraints of active management elements and ignores the randomness and volatility of distributed energy sources, which cannot meet the actual demand. Therefore, this paper establishes a reactive power optimization model for active distribution networks, which is solved by a second-order...

Casting production scheduling problem has attracted increasing research attention in recent years to facilitate the profits, efficiency, and environment issues of casting industry. Casting is often characterized by the properties of intensive energy consumption and complex process routes, which motivate the in-depth investigation on construction of...

The underlying control in the hybrid energy source system (HESS) of an electric vehicle plays a pivotal role. Uncertainty is unavoidable in system modeling owing to variations in electrical parameters and unknown external disturbances, which inevitably deteriorate the control performance of the HESS. In this study, an innovative adaptive dynamic su...

Accurate object detection and 6D pose estimation are the key technologies in robotic grasping applications, where efficiency and robustness are the two most desirable goals. Especially for textureless industrial parts, it is difficult for most existing methods to extract robust image features from cluttered scenarios with heavy occlusion. To addres...

DC distribution network faults seriously affect the reliability of system power supply. Therefore, this paper proposes a fault recovery reconfiguration strategy for DC distribution networks, based on hybrid particle swarm optimization. The original particle swarm algorithm is improved by simplifying the distribution network structure, introducing L...

Casting production scheduling problem (CPSP) has attracted increasing research attention in recent years to facilitate the profits, efficiency, and environment issues of casting industry. Casting is often characterized by the properties of intensive energy consumption and complex process routes, which motivate the in-depth investigation on construc...

Robotic 3D measurement for evaluating the final shape of blades can improve product quality and reduce fabrication costs. However, large or complex objects require multiple scans from different viewpoints to capture the entire object. Errors in registration artificially introduce defects and surface discontinuties in the reconstructed object model....

Abstract Focussing on the ineffective operating cycle and potential battery life degradation introduced by traditional energy converter‐based balancing techniques, a new distributed online active balancing scheme is proposed. In order to achieve a wider output voltage range, a new distributed converter is presented first, which can operate in boost...

Reduction of carbon emissions is receiving growing attention in manufacturing industry. In the real-life flexible open-shop manufacturing environments, the workpieces generally need frequent transport between machines so that the limitation of the transport resource is non-negligible. Joint scheduling is a better way to achieve global optimum than...

Dual resource constrained flexible job shop scheduling problem (DRCFJSP) becomes a hot research topic in recent years. However, worker fatigue is barely considered in DRCFJSP, which will result in unsuitable task assignments for workers and bring about negative effects such as muscle fatigue and cognitive confusion. To this end, a fatigue-conscious...

Robotic grinding is a promising method to form the surfaces of industrial components, which improves product quality, lowers machining cost, and reduces processing time. Allowance optimization is a surface matching process, which is important to grinding measurement. The grinding efficiency highly depends on the the results of the surface matching...

The poor cruising range of electric vehicle (EV) is a problem preventing its popularity. To tackle this problem, methods such as battery technology, energy-based motion control technology are developed. This paper proposes a new solution from the perspective of path planning. Such a solution is called 3-D multi-object path planning method (3D-M met...

The underlying voltage/current tracking control is a key issue for a hybrid energy storage system (HESS) in electric vehicles. This paper presents an innovative passivity-based L2-gain adaptive robust control (L2-ARC) method for a fully active battery/supercapacitor HESS. First, by exploiting and analyzing the internal structural properties, the po...

Path planning is a basic function for autonomous vehicle (AV). However, it is difficult to adapt to different velocities and different types of obstacles including dynamic obstacle and static obstacle (such as road boundary) for AV. To solve the problem of path planning under different velocities and different types of obstacles, a two potential fi...

The path tracking is a basic function of the autonomous vehicle. Generally, it is difficult to realize the path tracking with high accuracy at high speeds. To solve this problem, an adaptivity-enhanced path tracking system (AEPTS) is investigated in this paper. The adaptive performance of this AEPTS is realized via three aspects. The first is to ac...

Unmanned aerial manipulator (UAM) is usually a combination of a quadrotor and a robotic arm that can exert active influences on the environments. The control problems of the UAM system include model uncertainty caused by its center of gravity shift and external disturbances from the environments. To handle these two disturbances, a tracking control...

When standard neural style transfer approaches are used in portrait style transfer, they often inappropriately apply textures and colours in different regions of the style portraits to the content portraits, leading to unsatisfied transfer results. This paper presents a portrait style transfer method to transfer the style of one image to another. I...

Chaos optimization algorithm (COA) usually utilizes chaotic maps to generate the pseudorandom numbers mapped as the decision variables for global optimization problems. Recently, COA has been applied to many single objective optimization problems and simulations results have demonstrated its effectiveness. In this paper, a novel parallel chaos opti...

The slip ratio control is an important research topic in in-wheel-motored electric vehicles (EVs). Traditional control methods are usually designed for some specified modes. Therefore, the optimal slip ratio control cannot be achieved while vehicles work under various modes. In order to achieve the optimal slip ratio control, a novel model predicti...

Distributed driver electric vehicle (DDEV) works under various road excitations in practice, which may cause the changes in steering performance significantly. However, the various road excitations are not a priority for stable steering problem of DDEV, and this possibly leads to unstable steering performance, particularly oversteer or tail flick....

Generally, the distributed drive electric vehicle (DDEV) works under different fault status, and this may lead to unstable operating performance. However, the conventional fault-tolerant controller is only suitable for one special fault status, and thus, the stability of DDEV is hard to be guaranteed efficiently. To deal with this problem, a novel...

The lateral and longitudinal stability is important and difficult for distributed drive electric vehicle (DDEV). Current control methods for the lateral and longitudinal stability are designed based on the static model and parameter without considering the uncertain characteristic in DDEV. To solve this problem, this paper presents a novel compensa...

Path following is the basic technology of the autonomous vehicle (AV), many preview control methods have been widely applied to path following tasks. However, less of them take the variable vehicle velocities into account. In fact, the velocity is an important factor affecting the tracking accuracy. Especially, when an AV is in high velocity, it is...

The lateral stability is the crucial feature in a distributed drive electronic vehicle (DDEV). A high speed DDEV in a sharp turn may lose the lateral stability when it encounters fast varied road adhesion coefficients. To solve this problem, a BP-PID controller-based multi-model control system (MMCS) is designed for DDEV via direct yaw-moment contr...

In this paper, a subspace predictive control (SPC) method with a novel data-driven event-triggered law is proposed for linear time-invariant systems with unknown model parameters. Based on the conventional SPC method, the event-triggered law is introduced to substitute the typical receding horizon optimization, which reduces the data computation lo...

The yaw stability of distributed drive electric vehicle (DDEV) can be guaranteed by the active steering and torque distribution systems. Conventional yaw stability control strategy mainly focuses on the study of yaw moment, while the tyre lateral saturation and excessive longitudinal skid problems are difficult to be solved efficiently. This may le...

The steering performance of the distributed drive electric vehicle (DDEV) is an important research topic. Generally, DDEV works under various operating status with high switching frequency, while the conventional stability controller is only suitable for one special operating status. In addition, the lateral force saturation or deficiency always le...

The four-wheel steering (4WS) is an efficient method to improve the manoeuvrability of electric vehicle with the tendency of understeer, by providing the sufficient steering angles. Because of the various kinds of driving environments, the inner coupling between the active front and rear wheels of the 4WS vehicle is a challenging problem, which usu...

In recent years, it has been observed that there is an increasing rate of road accidents due to the low vigilance of drivers. Thus, the estimation of drivers’ vigilance state plays a significant role in Public Transportation Safety (PTS). We have adopted a feature fusion strategy that combines the electroencephalogram (EEG) signals collected from v...

Conventional yaw stability strategy of distributed drive electric vehicle (DDEV) is usually realised by torque distribution strategy. However, the instantaneous variations of four independent tyres slip ratio and the effect of disturbance have not been considered sufficiently. Therefore, it is difficult to realise the robustness of yaw stability fo...

Image segmentation can be considered as a problem of clustering since the pixels in the digital image are clustered in term of some evaluation criteria. Generally, clustering technique in image segmentation employs a single objective which can not reach ideal result for various kinds of images. Moreover, fuzzy c-means (FCM) algorithms which determi...

Distributed drive electric vehicle(DDEV) has been widely researched recently, its longitudinal stability is a very important research topic. Conventional wheel slip ratio control strategies are usually designed for one special operating mode and the optimal performance cannot be obtained as DDEV works under various operating modes. In this paper, a...

In order to resolve the starting problem for position sensorless interior permanent magnet synchronous motor, an improved initial rotor position estimation method based on square-wave signal injection is presented in this paper. Instead of the conventional sinusoidal voltage injection, square-wave voltage signals are injected into stator windings t...

This paper proposes a novel harmony search algorithm with gaussian mutation (GMHS) for multi-objective optimization. Harmony search (HS) algorithm has shown many advantages in solving global optimization problems; however, it also has some shortcomings, such as poor ability of escaping from local optimum and poor convergence. In view of the weaknes...

This paper proposed an optimal strategy for coordinated operation of large scale Electric vehicles(EVs) charging and discharging with Wind-Thermal system. Different from conventional works, the proposed cooperation modelis more practical, specially pays attention to EV users' costs while doing power commitments schedule on thermal plants, wind farm...

This paper presented an optimal torque distribution scheme for the stability improvement of a distributed-driven electric vehicle (DEV). The nonlinear dynamics and tire model of the DEV are constructed. Moreover, the single-point preview optimal curvature model with the proportional-integral-derivative (PID) process is developed to simulate the dri...

This work presents a robust regenerative charging (RC) control scheme for the brushless dc (BLDC) motor drives in advanced electric vehicle (EV). After analyzing the equivalent circuit of the bidirectional ac-dc converter, we first derive the mathematical model under RC mode by using state-space averaging method. Then, we originally formulate the T...

The parameter identification problem can be formalized as a multi-dimensional optimization problem, where an objective function is established minimizing the error between the estimated and measured data. In this article, a master–slave model (MSM)-based parallel chaos optimization algorithm (PCOA) (denoted as MSM-PCOA) is proposed for parameter id...

In order to control the permanent-magnet synchronous motor system (PMSM) with different disturbances and nonlinearity, an improved current control algorithm for the PMSM systems using recursive model predictive control (RMPC) is developed in this paper. As the conventional MPC has to be computed online, its iterative computational procedure needs l...

Bidirectional inductive power transfer (BIPT) system facilitates contactless power transfer between two sides and across an air-gap, through weak magnetic coupling. Typically, this system is nonlinear high order system which includes nonlinear switch components and resonant networks, developing of accurate model is a challenging task. In this paper...

Inductive power transfer (IPT) system facilitates contactless power transfer across an air-gap through weak magnetic coupling. The controller design for IPT system is very difficult owing to load and system parameter variations, very high operation frequency, strong non-linearity and discreteness. In this study, an extremum seeking control (ESC) st...

Abstract Although harmony search (HS) algorithm has shown many advantages in solving global optimization problems, its parameters need to be set by users according to experience and problem characteristics. This causes great difficulties for novice users. In order to overcome this difficulty, a self-adaptive multi-objective harmony search (SAMOHS)...

Abstract Chaos optimization algorithm (COA) utilizes the chaotic maps to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. A kind of parallel chaos optimization algorithm (PCOA) has been proposed in our former studies to improve COA. The salient feature of PCOA lies in its pseudo-parallel me...

To simulate solar cell systems or to optimize photovoltaic (PV) system performance, the estimation of solar cell model parameters is extremely crucial. In this paper, the parameter extraction of solar cell models is formalized as a multi-dimensional optimization problem, and an objective function is established minimizing the errors between the est...

Inductive power transfer (IPT) systems facilitate contactless power transfer between two sides and across an air-gap, through weak magnetic coupling. However, IPT systems constitute a high order resonant circuit and, as such, are difficult to design and control. Aiming at the control problems for bidirectional IPT system, a neural networks based pr...

Stand-alone hybrid photovoltaic(PV)-wind-diesel-battery system is becoming an appropriate choice of power supply system for remote areas far from the power grid. However, the sizing optimization of the stand-alone hybrid PV-wind-diesel-battery system is difficult because of the system’s complexity. In this paper, a novel improved fruit fly optimiza...

In this paper, we propose a novel nonlinear predictive control strategy based on an extreme learning machine to address the path-tracking control problem of wheeled mobile robots in the presence external disturbances. The hybrid chaotic optimization algorithm (HCOA), which can avoid being trapped in local minima and improve convergence in dealing w...

Bidirectional inductive power transfer (IPT) system facilitates contactless power transfer between two sides and across an air gap, through weak magnetic coupling. Typically, this system constitutes a high-order resonant circuit and, as such, is difficult to design and control. In this study, a novel technique for parameter identification of bidire...

Magnetic resonant wireless power transfer is an emerging technology that may create new applications for wireless power charging. However, for general deployment, low efficiency is a main obstructing factor. In this paper, a novel four-resonator coil structure is presented to improve system efficiency. Compared with the conventional four-resonator...

To simulate solar cell systems or to optimize photovoltaic (PV) system performance, accurate parameter values of solar cell systems are extremely crucial. In this article, the parameter extraction of solar cell models is posed as an optimization process with an objective function minimizing the difference between the measured values and estimated d...

As demonstrated earlier, the learning accuracy of the single-layer-feedforward-network (SLFN) is generally far lower than expected, which has been a major bottleneck for many applications. In fact, for some large real problems, it is accepted that after tremendous learning time (within finite epochs), the network output error of SLFN will stop or r...

Swarm intelligence is a research field that models the collective behavior in swarms of insects or animals. Recently, a kind of Drosophila (fruit fly) inspired optimization algorithm, called fruit fly optimization algorithm (FOA), has been developed. This paper presents a variation on original FOA technique, named multi-swarm fruit fly optimization...

Chaos optimization algorithms (COAs) utilize the chaotic map to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. Many existing applications show that COAs escape from the local minima more easily than classical stochastic optimization algorithms. However, the search efficiency of COAs cruci...

The application of chaotic sequences can be an interesting alternative to provide search diversity in an optimization procedure, named chaos optimization algorithm (COA). Since the chaotic motion is pseudo-randomness and chaotic sequences are sensitive to the initial conditions, the search ability of COA is usually effected by the starting values....

Series hybrid electric vehicles (SHEVs) improvements in fuel consumption and emissions directly depend on the operating point of the auxiliary power unit (APU). A new APU operating point optimization approach based on dynamic combined cost map (DCM) and particle swarm optimization (PSO) is presented in this paper. The influence of coolant temperatu...

Electronic throttle valves are electromechanical systems which regulate the air flow inside gasoline engines. The objective of electronic throttle valve control is to ensure fast and accurate reference tracking of the valve plate angle. This control demands are hard to accomplish since the plant is burdened with strong nonlinear effects and paramet...

In this paper, the mixed H-two/H-infinity control synthesis problem is stated as a multiobjective optimization problem, with objectives of minimizing the H-two and H-infinity norms simultaneously. Instead of building a LMIs-based synthesis algorithm, a self-adaptive control parameter multiobjective differential evolution algorithm is developed dire...