Optimal Trajectory Planning for Wheeled Mobile Robots Based on Kinematics Singularity

This research introduces a new optimality criterion for motion planning of wheeled mobile robots based on a cost index that assesses the nearness to singularity of forward and inverse kinematic models. Slip motions, infinite estimation error and impossible control actions are avoided escaping from singularities. In addition, high amplification of wheel velocity errors and high wheel velocity values are also avoided by moving far from the singularity. The proposed cost index can be used directly to complement path-planning and motion-planning techniques (e.g. tree graphs, roadmaps, etc.) in order to select the optimal collision-free path or trajectory among several possible solutions. To illustrate the applications of the proposed approach, an industrial forklift, equivalent to a tricycle-like mobile robot, is considered in a simulated environment. In particular, several results are validated for the proposed optimality criterion, which are extensively compared to those obtained with other classical optimality criteria, such as shortest-path, time-optimal and minimum-energy.     

管理信息网抗毁构建研究

在机动通信组网时,网络管理信息网是网络管理系统对各节点设备进行参数下发和状态监控的交互通道,在基于ATM虚连接和IP路由器构建的网管信息网中,通过研究网络互连策略和IP动态路由技术,构建了不受限于节点连接接口的抗毁管理信息组网,提高了网络的顽存能力,拓宽了机动通信的适应性,该方法可在工程中推广应用。     

逆M序列在机抖激光陀螺消除动态闭锁中的应用

对逆M序列在消除激光陀螺动态闭锁误差中的应用进行了研究和验证.目前多采用M序列对抖动的幅度进行调制来消除激光陀螺动态闭锁误差,而逆M序列与M序列相比不仅满足注入到激光陀螺抖动中的要求,且比M序列有其性质等方面优势.通过理论分析及M序列和逆M序列在消除机抖激光陀螺动态闭锁中实验中的应用对比,实验数据表明逆M序列在消除动态闭锁中的作用要优于M序列.     

一种新型神经网络广义逆系统

提出一种新型带有反馈环节的广义逆系统方法,并给出了其存在性的证明．该方法首先利用神经网络构造被控对象的α 阶逆系统,通过改变反馈环节参数可随时任意配置复合系统极点,无需重新构造广义逆系统．分别对ＳＩＳＯ 和ＭＩＭＯ 非线性系统进行仿真研究．仿真结果表明,在配置极点变换时,利用该方法构造的广义逆系统仍可对原系统实现有效的线性化和解耦．     

行波型超声电机基于神经网络的逆模型辨识

行波型超声电机的动态特性受定子压电陶瓷迟滞和接触层非线性摩擦力的影响,表现出复杂的多值映射特征.通过引入动态迟滞逆算子,将存在于超声波电机逆系统中的多值映射在新的扩张输入空间上,转换为一一映射;然后使用神经网络建立超声波电机的逆模型,对迟滞和非线性摩擦力的影响进行补偿.所建立的模型结构简单,可以在线调整适应电机参数的非线性变化.实验仿真结果验证了该方法的有效性.     

不确定系统的稳定广义预测控制

针对一类有界不确定线性离散被控对象,采用Min-Max优化方法,提出一种新的稳定广义预测控制(MMSGPC)算法.引入内模控制结构,将干扰和不确定性从被控对象中分离出来,并利用局部反环节对其进行补偿;采用Min-Max优化方法,将终端约束条件转化为有界不确定性最差情况时应的线性方程;通过引入矩阵的Moore-Penrose逆,得到了终端约束线性方程的通解,并结合性能指标函数求得了最优控制律.通过仿真实例验证了该方法的稳定效果.     

Application of the general elimination method in robot kinematics

A general method for solving the robot inverse kinematics problem is presented. The method is based upon the general elimination method to obtain the equivalent system of equations which are triangularized and the solutions of the inverse kinematics problem can be solved by backsubstitutions.     

Inverse-compensation-based DETC for nonlinear hysteresis system with disturbance

To control a nonlinear system with both hysteresis and disturbance, it is necessary to establish a hysteresis model and improve the disturbance rejection ability. However, the input signal implicitly involved in the classical hysteresis model can lead to difficulty in constructing a compensator. In this study, a hysteresis model in explicit form is proposed with a bounded auxiliary variable. Then, a model-based inverse is constructed for approximate compensation for the hysteresis. Moreover, the compensation error, which is considered a part of the disturbance, is proved to be bounded. Disturbance estimation triggered control (DETC) is utilized to address the compensation error coupled with the external disturbance. According to the disturbance effect indicator (DEI), DETC can improve the system control performance by considering the disturbance effect judgment. Experimental results are presented to illustrate the potential of the proposed technique.     

The method of fundamental solutions for problems in static thermo-elasticity with incomplete boundary data

An inverse problem in static thermo-elasticity is investigated. The aim is to reconstruct the unspecified boundary data, as well as the temperature and displacement inside a body from over-specified boundary data measured on an accessible portion of its boundary. The problem is linear but ill-posed. The uniqueness of the solution is established but the continuous dependence on the input data is violated. In order to reconstruct a stable and accurate solution, the method of fundamental solutions is combined with Tikhonov regularization where the regularization parameter is selected based on the L-curve criterion. Numerical results are presented in both two and three dimensions showing the feasibility and ease of implementation of the proposed technique.     

Real‐time updating of structural mechanics models using Kalman filtering,modified constitutive relation error,and proper generalized decomposition

The paper aims at proposing a new strategy for real‐time identification or updating of structural mechanics models defined as dynamical systems. The main idea is to introduce the modified constitutive relation error concept, which is a practical tool that enables to efficiently solve identification problems with highly corrupted data, into the Kalman filtering, which is a classical framework for data assimilation. Furthermore, a PGD‐based model reduction method is performed in order to optimize capabilities of the online updating strategy. Performances of the proposed approach, in terms of robustness gain and computational cost reduction, are illustrated on several unsteady thermal applications. Copyright © 2015 John Wiley & Sons, Ltd.