基于支持向量机的智能ATO控车算法

为解决ATO(列车自动运行)系统在实际线路实施过程中的适应能力差以及与车辆牵引制动性能耦合度过紧等问题,提出一种基于支持向量机(SVM)且具有训练模式和运营模式的智能ATO系统。该ATO系统直接采用车载设备性能参数、车辆性能参数、ATP(列车自动保护)/ATO曲线和线路参数等作为系统输入,通过基于SVM的机器学习算法计算ATO系统牵引和制动电压/电流输出参数。通过对实际线路ATO控车曲线数据的训练,调节SVM参数,得到最优智能ATO控车算法,且可利用该算法对实际线路环境下的控车命令进行预测。

列控车载设备的控车核心算法

针对高速列车运行超速安全防护,提出列控车载设备的控车核心算法,总体架构包括动车组制动参数导入、线路数据输入、安全距离预留、模式曲线生成和速度监控处理。算法功能模块划分为制动参数处理、线路数据处理、模式曲线处理和速度监控处理4个模块,其中控车曲线计算公式为列控车载设备控车核心算法关键,分别给出紧急制动曲线、常用制动曲线、紧急制动触发曲线和常用制动触发曲线的计算公式。在真实设备实验室内进行不同线路坡度和线路速度条件下的动车组制动实验,测得列控车载设备模式曲线制动距离,并将其与仿真算法软件计算的距离进行对比验证。结果表明:列控车载设备控车核心算法仿真结果与真实列控车载设备实时监测结果误差率不大于0.08%。将控车核心算法应用于新建铁路客运专线闭塞分区的符合性验证可知,该算法简化了仿真数据配置,减少了测试工作量,有利于缩短检算周期,并能及时反馈闭塞分区符合性检算结果,具有理论和实用价值。

A Novel Energy-regenerative Active Suspension for Vehicles

In order to regenerate electric power from the vibration excited by road unevenness,a novel energy- regenerative active suspension for vehicles was proposed with the description of its structure and its working principle with two modes switched in different operating conditions.Then,the novel active system was modeled and simulated to show the performance improvement in ride comfort in its electrical motor mode.Finally,the performance tests of the actuator prototype were carried out,which proves its capability for damping in its regenerative braking mode.The research results can provide useful guidance for the similar electrical active suspension design and development.

Modeling and control for hydraulic transmission of unmanned ground vehicle

Variable pump driving variable motor(VPDVM) is the future development trend of the hydraulic transmission of an unmanned ground vehicle(UGV).VPDVM is a dual-input single-output nonlinear system with coupling,which is difficult to control.High pressure automatic variables bang-bang(HABB) was proposed to achieve the desired motor speed.First,the VPDVM nonlinear mathematic model was introduced,then linearized by feedback linearization theory,and the zero-dynamic stability was proved.The HABB control algorithm was proposed for VPDVM,in which the variable motor was controlled by high pressure automatic variables(HA) and the variable pump was controlled by bang-bang.Finally,simulation of VPDVM controlled by HABB was developed.Simulation results demonstrate the HABB can implement the desired motor speed rapidly and has strong robustness against the variations of desired motor speed,load and pump speed.

Analytical modeling and multi-objective optimization(MOO) of slippage for wheeled mobile robot(WMR) in rough terrain

Good understanding of relationship between parameters of vehicle, terrain and interaction at the interface is required to develop effective navigation and motion control algorithms for autonomous wheeled mobile robots （AWMR） in rough terrain. A model and analysis of relationship among wheel slippage （S）, rotation angle （0）, sinkage （z） and wheel radius （r） are presented. It is found that wheel rotation angle, sinkage and radius have some influence on wheel slippage. A multi-objective optimization problem with slippage as utility function was formulated and solved in MATLAB. The results reveal the optimal values of wheel-terrain parameters required to achieve optimum slippage on dry sandy terrain. A method of slippage estimation for a five-wheeled mobile robot was presented through comparing the odometric measurements of the powered wheels with those of the fifth non-powered wheel. The experimental result shows that this method is feasible and can be used for online slippage estimation in a sandy terrain.

Combining Market-Based Control with Distribution Grid Constraints when Coordinating Electric Vehicle Charging

The charging of electric vehicles(EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid(e.g., undervoltage, phase unbalances); for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with eventdriven control at the operational level. Diff erent case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.

Optimization design and experimental research for space intelligent structure

There are more and more research on active control in the application of civil structure.However,some problems such as the drive levers design,optimization and control law problems restricted its application development.In this work,we presented a kind of piezoelectric drive lever to convert pulling force to pressure without flexural moments based on characteristics of the piezoelectric pile,using the genetic algorithm to optimize the layout of the driving lever,which greatly improved the efficiency.Then an active control experiment on a three-layer intelligence space structure was carried out.The experimental data show that the intelligent structures can produce through active control greatly inhibitive effects on the correspondingly controlled modal displacement and acceleration.Spectral analysis shows that the corresponding modal damping coefficient can be improved to different degrees.

Study on simulation and scheduling algorithm of CAN control for independently driving electric vehicle

Safety-critical applications such as the independently driving systems of electric vehicle （EV） require a high degree of reliability. The controller area network （CAN） is used extensively in the control sectors. A new real-time and reliable scheduling algorithm based on time-triggered scheduler with a focus on the CAN-based distributed control systems for independently driving EV is exploited. A distributed control network model for a dual-wheel independendy driving EV is established. The timing and reliabili- ty analysis in the worst case with the algorithm is used to evaluate the predictability and dependability and the simulation based on the algorithm with CANoe software is designed. The results indicate the algorithm is more predicable and dependable.

Control allocation algorithm for over-actuated electric vehicles

A control allocation algorithm based on pseudo-inverse method was proposed for the over-actuated system of four in-wheel motors independently driving and four-wheel steering-by-wire electric vehicles in order to improve the vehicle stability. The control algorithm was developed using a two-degree-of-freedom(DOF) vehicle model. A pseudo control vector was calculated by a sliding mode controller to minimize the difference between the desired and actual vehicle motions. A pseudo-inverse controller then allocated the control inputs which included driving torques and steering angles of the four wheels according to the pseudo control vector. If one or more actuators were saturated or in a failure state, the control inputs are re-allocated by the algorithm. The algorithm was evaluated in Matlab/Simulink by using an 8-DOF nonlinear vehicle model. Simulations of sinusoidal input maneuver and double lane change maneuver were executed and the results were compared with those for a sliding mode control. The simulation results show that the vehicle controlled by the control allocation algorithm has better stability and trajectory-tracking performance than the vehicle controlled by the sliding mode control. The vehicle controlled by the control allocation algorithm still has good handling and stability when one or more actuators are saturated or in a failure situation.

Parametric Body Model Development

This study shows a novel three-dimensional （3D） parametric body model development using cross-section control and control algorithm retrieved from anthropometric survey. The 3D parametric body model was shaped into the most common body shape of the young Hong Kong female and be able to automatically change its critical body shape according to the user＇s critical body dimension inputs. The control algorithm controls the profile of the parametric model is retrieved from an anthropometric survey using 3D scanner to study the profile change of body and the relation between some critical body dimensions. Compared to the traditional anthropometric surveys, the 3D body scanner provides more accurate body dimension and information as well as new body shape measurements.

Vector Field Based Sliding Mode Control of Curved Path Following for Miniature Unmanned Aerial Vehicles in Winds

In this paper, a curved path following control algorithm for miniature unmanned aerial vehicles（UAVs） in winds with constant speed and altitude is developed. Different to the widely considered line or orbit following, the curved path to be followed is defined in terms of the arc-length parameter, which can be straight lines, orbits, B-splines or any other curves provided that they are smooth. The proposed path following control algorithm, named by VF-SMC, is combining the vector field（VF） strategy with the sliding mode control（SMC） method. It is proven that the designed algorithm guarantees the tracking errors to be a bounded ball in the presence of winds, with the aid of the Lyapunov method and the BIBO stability. The algorithm is validated both in Matlab-based simulations and high-fidelity semi-physical simulations. In Matlab-based simulations, the proposed algorithm is verified for straight lines, orbits and B-splines to show its wide usage in different curves.The high-fidelity semi-physical simulation system is composed of actual autopilot controller, ground station and X-Plane flight simulator in-loop. In semi-physical simulations, the proposed algorithm is verified for B-spline path following under various gain parameters and wind conditions thoroughly.All experiments show the accuracy in curved path following and the excellent robustness to wind disturbances of the proposed algorithm.

Intelligent and connected vehicles： Current status and future perspectives

Intelligent connected vehicles(ICVs) are believed to change people's life in the near future by making the transportation safer,cleaner and more comfortable. Although many prototypes of ICVs have been developed to prove the concept of autonomous driving and the feasibility of improving traffic efficiency, there still exists a significant gap before achieving mass production of high-level ICVs. The objective of this study is to present an overview of both the state of the art and future perspectives of key technologies that are needed for future ICVs. It is a challenging task to review all related works and predict their future perspectives, especially for such a complex and interdisciplinary area of research. This article is organized to overview the ICV key technologies by answering three questions: what are the milestones in the history of ICVs; what are the electronic components needed for building an ICV platform; and what are the essential algorithms to enable intelligent driving? To answer the first question, the article has reviewed the history and the development milestones of ICVs. For the second question, the recent technology advances in electrical/electronic architecture, sensors, and actuators are presented. For the third question, the article focuses on the algorithms in decision making, as the perception and control algorithm are covered in the development of sensors and actuators. To achieve correct decision-making, there exist two different approaches: the principle-based approach and data-driven approach. The advantages and limitations of both approaches are explained and analyzed. Currently automotive engineers are concerned more with the vehicle platform technology, whereas the academic researchers prefer to focus on theoretical algorithms. However, only by incorporating elements from both worlds can we accelerate the production of high-level ICVs.