Direct yaw moment control for distributed drive electric vehicle handling performance improvement

For a distributed drive electric vehicle (DDEV) driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control (DYC) has been widely studied and applied to vehicle stability control. Good vehicle handling performance: quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts: a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error (ITAE) function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method: yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.     

基于跟踪误差约束的机器鱼抗扰动路径跟踪控制

为了解决机器鱼在扰动下跟踪效率低的问题,本工作提出了一种抗扰动和自适应的误差约束控制方案。 首先,通过设 计虚拟控制输入,并利用积分环节更新了自适应视线制导律,消除了侧滑导致的运动位置偏离,增强了机器人的抗干扰能力。 其次,通过构造机器鱼的偏航和浪涌自适应控制器,使神经网络函数拟合模型的不确定项和水流扰动,并用逼近值补偿系统的 控制输入。 这提升了机体的环境适应性。 最后,利用障碍 Lyapunov 理论,机器鱼跟踪位置和角度的一致最终有界性被证明。 通过模拟和实验,与经典制导方案相比,所提方案提高了机器鱼的跟踪效率和稳态性能,使机器鱼的位置误差收敛速率平均提 升了 14. 57% 。 关键词: 机器鱼     

Fast inverse dynamics computation in real-time robot control

In this paper, two fast algorithms for the inverse dynamics computation in real-time robot control are developed by using simple Lagrange-Euler formulation. The high computational efficiency of the proposed algorithms can make the inverse dynamics computation of any practical robot to be implemented on a current microcomputer in real-time. As compared with other existing algorithms, the algorithms proposed in this paper are, computationally, the fastest of all existing algorithms for robot dynamics computation.     

基于主动转向的爆胎汽车操纵稳定性模糊控制研究

汽车在高速行驶时发生爆胎后引起的交通事故危害较大,为了能够更好地控制爆胎后的方向稳定性,主要是通过分析爆胎后的主要影响因素,建立爆胎汽车方向失稳动力学模型,并建立基于主动转向的模糊控制器。重点研究了汽车爆胎后车轮的滚动半径变小以后对汽车行驶方向失稳的影响,进而分析由于爆胎汽车姿态变化而引起的载荷转移,以及由于载荷转移所导致的各个车轮上的侧偏力大小对汽车行驶方向失稳的影响。最后通过仿真验证模糊控制系统能够较好的纠正由于爆胎引起的汽车跑偏。     

Model predictive control for systems with fast dynamics using inverse neural models

In this work, a novel model predictive control (MPC) scheme is introduced, by integrating direct and indirect neural control methodologies. The proposed approach makes use of a robust inverse radial basis function (RBF) model taking into account the applicability domain criterion, in order to provide a suitable initial starting point for the optimizer, thus helping to solve the optimization problem faster. The performance of the proposed controller is evaluated on the control of a highly nonlinear system with fast dynamics and compared with different control schemes. Results show that the proposed approach outperforms the rivaling schemes in terms of response; moreover, it solves the optimization problem in less than one sampling period, thus effectively rendering MPC-based controllers capable of handling systems with fast dynamics.     

汽车操纵稳定性的联合仿真技术研究

提出了一种基于ADAMS-MATLAB联合仿真平台研究汽车操纵稳定性的控制方法,采用MSC.ADAMS/Car软件与MATLAB/Simulink软件分别建立整车多体动力学模型和模糊控制策略,并通过相关技术构建联合仿真平台,研究和分析不同典型工况下的汽车操纵稳定性,来设计和验证控制策略的可行性和有效性。仿真结果表明:联合仿真平台可以作为汽车操纵稳定性电子控制产品的先期研发工具,能够高效地设计和优化模糊控制器,可提高汽车操纵稳定性电子控制产品的性能。     

Fuzzy chaos control for vehicle lateral dynamics based on active suspension system

The existing research of the active suspension system（ASS） mainly focuses on the different evaluation indexes and control strategies. Among the different components, the nonlinear characteristics of practical systems and control are usually not considered for vehicle lateral dynamics. But the vehicle model has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, the nonlinear dynamic model of lateral system is considered and also the adaptive neural network of tire is introduced. By nonlinear analysis methods, such as the bifurcation diagram and Lyapunov exponent, it has shown that the lateral dynamics exhibits complicated motions with the forward speed. Then, a fuzzy control method is applied to the lateral system aiming to convert chaos into periodic motion using the linear-state feedback of an available lateral force with changing tire load. Finally, the rapid control prototyping is built to conduct the real vehicle test. By comparison of time response diagram, phase portraits and Lyapunov exponents at different work conditions, the results on step input and S-shaped road indicate that the slip angle and yaw velocity of lateral dynamics enter into stable domain and the results of test are consistent to the simulation and verified the correctness of simulation. And the Lyapunov exponents of the closed-loop system are becoming from positive to negative. This research proposes a fuzzy control method which has sufficient suppress chaotic motions as an effective active suspension system.     

路况识别在车辆动力学稳定性控制中的应用

在分析现有的车辆动力学稳定性控制策略的基础上，提出了一种新的控制策略，构建了以横摆角速度为控制变量的反馈控制器和以路面附着系数μ构成的前馈控制器组成的联合控制系统，并建立了相应的车辆动力学仿真模型，通过仿真验证，得出联合控制系统比单独以横摆角速度为控制变量的控制系统的控制效果更好，对路面的适应能力更强。     

汽车操纵稳定性仿真用轮胎模型的研究

介绍了四种常见的车辆操纵稳定性仿真用轮胎模型,即简单非线性轮胎模型、半经验公式轮胎模型、魔术公式轮胎模型和分析轮胎模型。通过对含上述四种轮胎模型的车辆动力学系统进行C级不平路面上转向盘角阶跃输入仿真试验,结果表明车辆系统响应总体趋势一致。以简单非线性轮胎模型为例,对比了车辆在水平路面与正弦路面上的响应,分析了不平路面的频率和幅值及车速对车辆操稳性的影响。     

基于制动力矩的ABS整车控制方法的研究

提出了一种基于整车的控制方法,首先根据制动压力进行道路自动识别,然后根据路况自动调整左右两侧车轮的制动力之差,以保证车辆制动时的方向稳定性.结合14自由度的虚拟样机整车模型,分别在对接路面和分离路面上进行基于ADAMS/Simulink的联合仿真制动模拟试验.结果表明该方法能够较好的识别路面状态,使车辆在兼顾其制动距离与时间的前提下提高其直线制动的方向稳定性,为一些基于路面状态的汽车主动控制策略提供了条件.     

基于线控转向系统操作稳定性的研究

针对汽车线控转向系统的操作稳定性问题,研究了固定转向灵敏度型与γ和β联合控制策略,之后设计了基于dSPACE的线控转向硬件在环仿真实验台架对算法进行实验验证.按照国家标准中转向瞬态响应实验中的要求,验证了汽车在此控制策略下的操纵稳定性能     

组态王监控系统界面设计中的图形处理问题

总结了组态王界面设计中的图形处理方式。对图形对象进行了分析，指出了组态王图形处理功能存在的不足。介绍了优秀矢量软件CorelDRAW的特点及CorelDRAW图形如何应用于组态王界面设计的方法，对快速创建个性化用户界面具有指导意义。     

汽车顶蓬搬运折断风险计算及应用

针对聚氨酯汽车顶蓬在生产搬运过程中容易折断的问题,在分析顶蓬搬运折断失效模式的基础上,对顶蓬及其搬运过程进行了假设和简化,把搬运中的顶蓬简化为简支梁,然后使用与FEA相同的基本数学模型,设计了一种计算顶蓬侧边折断风险的方法,并用MathCAD编制程序实现项蓬受力的计算和折断风险的评估.使用编制的程序对某E级车双天窗顶蓬进行了分析,结果表明此计算方法使用简便,计算结果准确、可靠.最后对顶蓬折断问题的改进提出了可行的建议.     

车辆路径问题的智能建模方法研究

针对车辆路径问题的自动建模工作,以人类建模思维规律为依托,提出了基于结构差异的智能建模方法,实现了车辆路径问题的智能建模系统,解决了车辆路径问题动态性导致问题建模不能实现的瓶颈.通过该系统的实际应用,验证了建模方法的可行性与有效性.     

车辆路径问题的捕食搜索算法研究

针对车辆路径问题存在的NP难题,设计了一种模仿动物捕食策略的捕食搜索算法进行求解。该算法利用搜索空间限制的大小,定义算法的局域搜索和全局搜索,并通过调节搜索空间的限制,以实现局域搜索和全局搜索之间的转换,它具有较好的局部集中搜索和跳出局部最优的能力。通过测试实例的计算,并与已有相关算法进行比较,结果表明该算法简洁而行之有效,是求解车辆路径问题的一个较好方法。     

Integrated control of lateral and vertical vehicle dynamics based on multi-agent system

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention（BDI）-agent model framework, the TYRE agent, electric power steering（EPS） agent and active suspension system（ASS） agent are proposed. In the system（SYS） agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system（MAS） controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.     

Gesture recognition in the problem of contactless control of an unmanned aerial vehicle

Optoelectronics, Instrumentation and Data Processing - The problem of contactless control of an unmanned aerial vehicle by human gestures is considered. A system of commands is proposed for an...     

On the inverse problem of magnetostatics

This work is devoted to solving the inverse problem of the magnetic method for nonde- structive testing (MMNDT). The purpose of the work, frankly speaking and avoiding complicated concepts and formulas, is to identify research directions in MMNDT that would approach solution of the inverse problem in the field of magnetic defectoscopy to the highest extent.