Quasi-Newton-type optimized iterative learning control for discrete linear time invariant systems

In this paper, a quasi-Newton-type optimized iterative learning control (ILC) algorithm is investigated for a class of discrete linear time-invariant systems. The proposed learning algorithm is to update the learning gain matrix by a quasi-Newton-type matrix instead of the inversion of the plant. By means of the mathematical inductive method, the monotone convergence of the proposed algorithm is analyzed, which shows that the tracking error monotonously converges to zero after a finite number of iterations. Compared with the existing optimized ILC algorithms, due to the superlinear convergence of quasi-Newton method, the proposed learning law operates with a faster convergent rate and is robust to the ill-condition of the system model, and thus owns a wide range of applications. Numerical simulations demonstrate the validity and effectiveness.     

三平移并联机器人控制算法

论文对一种三平移并联机器人进行了运动学建模,运用矩阵计算方法得到其机构运动学反解,即根据终端执行器的运动规律,求出原动件在单位时间内的位移,进而求得步进电机在单位时间内所发的脉冲数。实验验证该步进电机控制算法的正确性,为并联机器人的运动控制提供了理论方法。     

重庆羊角滑坡群滑带土抗剪强度研究

羊角滑坡群是乌江白马航电枢纽坝前的一个巨型滑坡群,该滑坡群的稳定与否,对白马航电枢纽的安全运行至关重要.为能给该滑坡群的治理工程设计和稳定分析提供准确的强度参数,对该滑坡群中各滑坡的滑带土抗剪强度进行研究.采用滑带土室内试验、现场大剪试验、反演分析等方法,确定了羊角滑坡群各滑带土的抗剪强度参数,为工程设计提供了可靠的数...     

Pulse-order recursive method for inverse covariance matrix computation applied to space-time adaptive processing

The conventional space-time adaptive processing(STAP) method such as the typical sample matrix inversion(SMI)-based STAP method is difficult to implement for a practical system because intense computational complexity arises in calculating the inversion of a space-time covariance matrix directly.According to the block Hermitian matrix property of space-time covariance matrix,a new pulse-order recursive method is proposed in this paper to calculate the inverse covariance matrix for the STAP adaptive weight,which can reduce the computational complexity significantly.The proposed method requires initially calculating the inverse covariance matrix of the first pulse-order recursively based on the block Hermitian matrix property.In the following,the inversion of space-time covariance matrix is obtained recursively based on the previous pulse-order inverse covariance matrix.Next,the STAP adaptive weight is calculated based on the inversion space-time covariance matrix previously obtained.Compared with the conventional SMI-based STAP algorithms,the computational complexity of the proposed method is reduced to more than 50% for the same clutter suppression performance.This method can be applied to practical systems benefiting from small computational complexity and stable clutter suppression performance.     

基于双目视觉的机器人目标定位与机械臂控制

为了更好地与复杂多变的非结构化环境进行交互,完成对目标物体的识别和抓取,提出了一种应用于服务机器人平台的基于双目视觉的仿人机械臂控制方法.文中首先用D-H方法对机械臂进行建模,并对这个模型做了改进,给出了一种更加简便的3+1自由度仿人机械臂的逆解算法,采用基于双目视觉与颜色分割的目标识别方法;然后根据识别出的目标三维坐标信息控制机械臂完成抓取任务;最后,本方法在家庭服务机器人上得到了验证,机器人能够完成对目标物体的识别和抓取动作.     

Turbo码的按位迭代译码仿真与优化

Turbo码的迭代译码次数越多,译码延时和功耗也越大,通过图像传输的Turbo译码仿真分析,提出按不同比特位迭代次数不同的译码方法,并对各比特位的迭代次数进行优化,结果能使总迭代译码次数减少50%,且能保证译码后的图像效果。     

Computations with quasiseparable polynomials and matrices

In this paper, we survey several recent results that highlight an interplay between a relatively new class of quasiseparable matrices and univariate polynomials. Quasiseparable matrices generalize two classical matrix classes, Jacobi (tridiagonal) matrices and unitary Hessenberg matrices that are known to correspond to real orthogonal polynomials and Szegö polynomials, respectively. The latter two polynomial families arise in a wide variety of applications, and their short recurrence relations are the basis for a number of efficient algorithms. For historical reasons, algorithm development is more advanced for real orthogonal polynomials. Recent variations of these algorithms tend to be valid only for the Szegö polynomials; they are analogues and not generalizations of the original algorithms.     

Rollout sampling approximate policy iteration

Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervised learning problem. This paper proposes variants of an improved policy iteration scheme which addresses the core sampling problem in evaluating a policy through simulation as a multi-armed bandit machine. The resulting algorithm offers comparable performance to the previous algorithm achieved, however, with significantly less computational effort. An order of magnitude improvement is demonstrated experimentally in two standard reinforcement learning domains: inverted pendulum and mountain-car.     

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.     

噪声对基于不同梯度算子的ICG算法的影响

反向合成梯度算法是一种基于局部指向性的反向合成图像对齐算法,能有效克服光照变化对匹配结果准确性的影响。局部指向性的计算在本质上是梯度的计算,可以用不同的梯度算子求解。该文采用4种梯度算子计算局部指向性,通过给输入图像和模板图像中加入噪声模拟实际图像,研究了噪声对基于4种梯度算子的反向合成梯度算法的影响。