Varying Zonotopic tube RMPC with switching logic for lateral path tracking of autonomous vehicle

Model mismatch caused by strong nonlinearity and other factors will severely impact the lateral path tracking control in Autonomous Vehicles (AVs) under extreme conditions. Previous studies have focused on guaranteeing robust stability under possible uncertainty realizations through Tube-based Robust Model Predictive Control (TRMPC). However, three deficiencies in TRMPC applications are revealed: unknown disturbance set, simple rigid tube, and excessive conservatism. In this paper, a novel scheme named Varying Zonotopic TRMPC with Switching Logic (SVTMPC) is developed to overcome these limitations. Firstly, a zero steady-state error dynamic model is established, and a new update mechanism of the nominal state is devised to determine the unknown internal disturbance set of the AV system. Secondly, zonotopic representation of all defined sets is used to construct the prediction model, as well as a flexible tube with varying cross-sections is naturally designed to overcome excessive conservation and non-solution of Quadratic Programming (QP). Finally, a switching logic between conservative and radical strategies improves tracking performance under conventional conditions without compromising robust stability. Numerical simulation through three scenarios shows that the SVTMPC controller can comprehensively improve robust stability and adaptability compared with MPC and TRMPC. Hardware-in-the-Loop (HIL) experiment verifies the effectiveness and real-time of the SVTMPC controller.     

On the training of a neural network for online path planning with offline path planning algorithms

One of the challenges in path planning for an automated vehicle is uncertainty in the operational environment of the vehicle, demanding a quick but sophisticated control of the vehicle online. To address this online path planning issue, neural networks, which can derive a heading for an operating vehicle in a given situation, have been actively studied, demonstrating their satisfactory performance. However, the study on the training path data, which specifies the desired output of a neural network and in turn influences the behavior of the neural network, has been neglected in the literature. Motivated by this fact, in this paper, we first generate different training path data sets applying two different offline path planning algorithms and evaluate the performance of a neural network as an online path planner depending on the training data under a simulation environment. We further investigate the properties of the training data that make a neural network more reliable for online path planning.     

Determinants of professionally autonomous end user acceptance in an enterprise resource planning system environment

To fully exploit the capabilities of complex technologies, businesses must deliberately foster technology acceptance by end users. This deliberate activity must recognize the complexity of factors that influence individuals’ perceptions, intentions, and usage of information technology. This study surveyed 66 professionally autonomous end users and gathered information on their perceptions related to several technology acceptance factors for a newly installed enterprise resource planning (ERP) system component. Study analyses focused on end user perceptions of ERP component usefulness, their intention to use the system, and self-reported usage of a system component. Valuable insights into the perceptions of professional end users toward a component of a complex technology were gained. Recommendations based upon the results of this study include: (a) clearly describe, early in the implementation process, an overall picture of the ERP system flow and visually show end users how the components they use “fit” into the whole system; (b) convert ERP-related “tech talk” to common end user language by either clear explanation of unique terms or associations of new terms to ones commonly understood by end users, and (c) provide adequate resources (financial, physical, human, etc.) to ensure that end users have access to timely support.     

Trajectory tracking of an autonomous vehicle using immersion and invariance control

An Immersion and Invariance [I & I] controller is designed to control the nonlinear lateral vehicle’s motion, using the steering angle as the only input. Similar to most of the lateral vehicle’s dynamics control law, the cornering stiffness parameters are involved in our proposed controller. Because of the tight relation between tire/road properties and the cornering stiffness parameters, they are not available from the outputs of the sensors and therefore, should be estimated for utilizing in the control law. An online data-driven identification is employed for estimating the cornering stiffness parameters. In addition, a robust model-based fault detection and approximation method in the presence of uncertainties via neural networks is presented. The performance of the obtained control law is investigated via simulation tests in different situations and in the presence of the disturbance. Moreover, some validation tests are performed using the CarSim software to show the effectiveness of our algorithm.     

HILS setup of dynamic flight path planning in 3D environment with flexible mission planning using Ground Station

This paper reports the creation of the HILS setup to simulate the performance of the AUS-UAV system and the Ground Station. The paper will give an overview of the integration of the Ground Station created using a guide, the Avionics Unit created using an embedded system, integrated with various sensors, and the simulator created using simulink/flight simulator combination. The simulation will show the Ground Station and the embedded system working cooperatively to guide the UAV through several mission waypoints in three dimensions (3D). The paper focuses on the algorithm used to create paths in 3D, and also the organization of waypoints to achieve a specific goal. The paper also details the testing of the HILS.     

Consensus-based economic hierarchical control strategy for islanded MG considering communication path reconstruction

In the islanded microgrid (MG), to improve the control effect of the output voltages of DERs and keep the economical operation of MG, a consensus-based economic hierarchical control strategy is proposed in this paper. The corresponding control structure is divided into physical and cyber layers, where the cyber layer is mainly composed by communicators. In these two layers, there are two main designs: the consensus-based primary control (CBPC) method and the secondary control (CBSC) method. In CBPC: Firstly, the undirected communication path among communicators is designed by path planning. Then, based on the constructed path, an economic P–U droop control method considering with line loss and flexible load is realized by using consensus control. In CBSC: Firstly, a cyber-physical vulnerability assessment method is designed. Based on this method, the DER with the lowest vulnerability is selected to be connected with the “virtual leader”. And when the data transmission behavior of the undirected communication path is selected, the undirected network can be transferred as a directed network. Thus, it can make the virtual leader-following consensus control (VLFCC) and the secondary control on voltage accomplished. Finally, the simulation results show the effectiveness of the proposed strategy.     

全球低碳汽车技术合作创新网络演化路径研究

随着全球气候变暖、能源紧张与环境污染等问题日益严峻,低碳汽车技术创新在全球范围内获得极大关注。本文以全球低碳汽车技术创新专利申请量排名前100名的领先组织为研究对象,通过专利数据挖掘,构建1992—2011年全球低碳汽车技术合作创新网络,分析全球低碳汽车技术合作创新网络特征及演化路径。研究结果表明,全球低碳汽车技术合作创新网络中行动者之间连接不紧密,信息的传播速度较慢;网络演化路径呈现网络密集度逐步提升,核心组织逐渐突显的趋势。     

Event-triggered adaptive target tracking control for an underactuated autonomous underwater vehicle with actuator faults

In this paper, the target tracking control problem is investigated for an underactuated autonomous underwater vehicle (AUV) in the presence of actuator faults and external disturbances based on event-triggered mechanism. Firstly, the five degrees-of-freedom kinematic and dynamic models are constructed for an underactuated AUV, where the backstepping method is introduced as the major control framework. Then, radial basis function neural network (RBFNN) and adaptive control method are made full use of estimating and compensating the influences of uncertain information and actuator faults. Besides, the relative threshold event-triggered strategy is integrated into the tracking control to further reduce communication burden from the controller to the actuator. Moreover, through Lyapunov analysis, it is proved that the designed controllers guarantee that the tracking error variables of the underactuated AUV are uniformly ultimately bounded and can converge to a small neighborhood of the origin. Finally, the effectiveness and reasonableness of the designed tracking controllers are illustrated by comparative simulations.     

人工免疫算法规划复杂环境下三维飞行航迹

应用人工免疫算法规划复杂地形和火力威胁环境下的三维飞行航迹.根据实际地形的特点提取在山岭横栏的地形和多火力威胁包围的复杂场景,利用人工免疫算法的3种情况分别进行飞行器的航线设计,同时根据飞机的机动性和适航性对上述规划出的航迹进行优化;并把免疫算法3种情况的模拟结果进行比较.仿真结果表明,与遗传算法相比,人工免疫算法在规划复杂环境下三维航迹是可行的,在时间上有一定的优势.     

Robust fault-tolerant control for four-wheel individually actuated electric vehicle considering driver steering characteristics

A robust fault-tolerant control scheme for distributed actuated electric vehicles is proposed to maintain vehicle stability suffering actuator faults while considering the driver personality differences. The proposed scheme integrates the cooperative game and terminal sliding mode control into the framework of the feedback linearization method (FLM). Firstly, the nonlinearities of the driver-vehicle system are treated by the knowledge of Lie derivative, and then a set of controllable virtual subsystems is obtained through diffeomorphism. To achieve multi-objective cooperation, the interaction framework of virtual subsystems is modeled based on cooperative game theory, which provides a basic feedback control scheme (BFCS). Finally, a terminal sliding mode technology-based active compensation control scheme is integrated into BFCS to handle the systemic disturbances caused by actuator faults. An implementation of hardware-in-the-loop verifies that the stability of the vehicle under the control of the developed approach can be guaranteed for different drivers and different fault types.     

A general motion control framework for an autonomous underwater vehicle through deep reinforcement learning and disturbance observers

This paper investigates the application of deep reinforcement learning (RL) in the motion control for an autonomous underwater vehicle (AUV), and proposes a novel general motion control framework which separates training and deployment. Firstly, the state space, action space, and reward function are customized under the condition of ensuring generality for various motion control tasks. Next, in order to efficiently learn the optimal motion control policy in the case that the AUV model is imprecise and there are unknown external disturbances, a virtual AUV model composed of the known and determined items of an actual AUV is put forward and a simulation training method is developed on this basis. Then, in the given deployment method, three independent extended state observers (ESOs) are designed to deal with the unknown items in different directions, and the final controller is obtained by compensating the estimated value of ESOs into the output of the optimal motion control policy obtained through simulation training. Finally, soft actor-critic is chosen as deep RL algorithm of the framework, and the generality and effectiveness of the proposed method are verified in four different AUV motion control tasks.     

Path tracking control strategy for the intelligent vehicle considering tire nonlinear cornering characteristics in the PWA form

To improve the path tracking control performance of the intelligent vehicle under critical maneuvers, a novel control strategy is introduced in this work. Considering that the tire cornering characteristics show high nonlinearities and uncertainties under those special driving conditions, a three-dimensional piecewise affine (PWA) identification method is proposed to realize the nonlinear modeling of the tire cornering characteristics for the first time. On this basis, the PWA model of the vehicle lateral dynamics is established. To obtain the vehicle target yaw rate for path tracking, a driver direction control model with adaptive preview time is put forward. Then, the linear quadratic optimal control method is further adopted to design multiple path tracking controllers for different working areas of the affine subsystems, thus the optimal steering angles of the front wheels can be generated to guarantee the path tracking performance for the intelligent vehicle under a wide range of driving conditions. Finally, to evaluate the performance of the proposed path tracking control strategy which considers the tire nonlinear cornering characteristics in the PWA form, the CarSim-Simulink co-simulation work is conducted. The co-simulation results show that the proposed control strategy presents significant performance advantages over the other two methodologies and demonstrates satisfactory path tracking control performance.     

A solution to the path planning problem via algebraic geometry and reinforcement learning

In this paper, the path planning problem for an unicycle-like mobile robot is considered. By using some results borrowed from algebraic geometry, a technique is given to determine a dynamical system that is affine in the input and whose trajectories tend to a chosen algebraic set independently of the control input. Since this does not guarantee that the corresponding paths of motion are collision free, an optimal control problem is formulated to enforce this behavior, and its approximate solution is determined via integral reinforcement learning. Finally, it is shown how such results can be used to derive a feedback control law for unicycle-like mobile robots.     

企业自主创新体系及模式研究

分析企业自主创新及其体系的慨念和特征,从技术来源和技术创新战略的角度构建企业自主创新体系的结构模型,在此基础上提出企业自主创新的模式,并通过自主创新模式决策过程,指出自主创新组合的路径,最后,提出企业实施自主创新战略的主要措施。     

三维表面微观形貌的等高图绘制及粗糙度3-D评定参数计算方法研究

针对零件表面质量的要求愈来愈高，而机加工表面微观形貌的粗糙度3-D评定方法却相对滞后。针对这一问题，本文就三维表面微观形貌的等高图的绘制方法、粗糙度3-D评定参数的计算提出了一些具体编程实现方法。重点阐述了三维表面等高图的绘制方法、3-D支承率和液体滞留性能指数的计算方法。利用JB-4C测量仪，开发了粗糙度3-D评定参数计算系统，验证了该方法的可行性。     

Correntropy based model predictive controller with multi-constraints for robust path trajectory tracking of self-driving vehicle

Self-driving vehicles must be equipped with path tracking capability to enable automatic and accurate identification of the reference path. Model Predictive Controller (MPC) is an optimal control method that has received considerable attention for path tracking, attributed to its ability to handle control problems with multiple constraints. However, if the data acquired for determining the reference path is contaminated by non-Gaussian noise and outliers, the tracking performance of MPC would degrades significantly. To this end, Correntropy-based MPC (CMPC) is proposed in this paper to address the issue. Different from the conventional MPC model, the objective of CMPC is constructed using the robust metric Maximum Correntropy Criterion (MCC) to transform the optimization problem of MPC to a non-concave problem with multiple constraints, which is then solved by the Block Coordinate Update (BCU) framework. To find the solution efficiently, the linear inequality constraints of CMPC are relaxed as a penalty term. Furthermore, an iterative algorithm based on Fenchel Conjugate (FC) and the BCU framework is proposed to solve the relaxed optimization problem. It is shown that both objective sequential convergence and iterate sequence convergence are satisfied by the proposed algorithm. Simulation results generated by CarSim show that the proposed CMPC has better performance than conventional MPC in path tracking when noise and outliers exist.     

论“社会科学的三维框架—知识经济的总方程”

鲍吉人先生建立的“社会科学的三维框架－知识经济的总方程，用“复数矩阵图表”不仅完美地表达了社会现实中“领导，专家和公众”相互作用的三维关系，且具有很高的应用价值。     

Motion information based avoidance control for 3-D multi-agent systems

This paper presents a closed-form cooperative avoidance control design for 3-dimensional rigid-body agents. New avoidance functions are designed to integrate the collision risk with the addition of motion and posture information. Time-varying sensing regions enable the conflict resolution actions only when there is a potential risk of collision, thus further reducing some unnecessary interference with other objectives. These characteristics lead to the less-conservative avoidance response, smoother maneuvers, and milder motion trajectories. The stability of the proposed method is analyzed and the corresponding proofs and guaranties for collision-free maneuvering, are provided. Performance comparisons are presented for two simulation scenarios, which illustrate the effectiveness and reliability of the new method.     

An information system for decision support in national information policy-making and planning

It is widely recognized that national information policies and plans severely suffer from the lack of timely and relevant data which could support decision-making. Through a pilot project sponsored by UNESCO/PGI and a subsequent application project at the Brazilian Institute for Information in Science and Technology (IBICT), an information system is being developed in order tentatively to overcome this obstacle. It consists of several related modules for the control of the internal production at the national agency and of the development projects and their related contracts, and for the monitoring of the information scene, both national and international. The two first modules are based upon the items of standardized work plans. The third one consists of a coherent series of data bases which contain basic information about the actors and components of the information scene, further transformed into single and aggregated numerical values. The latter are themselves aggregated and standardized according to a comprehensive list of variables, which are calculated on an international basis for the upper levels of the system. The system has been designed in order to cater to various perspectives of the information sector and the calculation of specific or composite indicators. It is linked with a bibliographic information system which controls the documents from which part of the data have been extracted, and with a referral system. The principles and examples of practical applications of the system are presented. The prospects and requirements for its full-scale implementation are discussed.