最优鲁棒极点配置控制器的设计

本文对动态区间系统(dynanmic interval system)给出了最优鲁棒极点配置控制器的设计方法。     

基于极点配置的二级倒立摆最优控制器设计

介绍了按规定的主导极点选择最优控制加权阵的原理,并在方法上作了一定改进。把传统的最优控制与极点配置结合起来,既得到了系统最优控制器,又得到了具有工程意义希望的性能指标。并成功地把最优控制理论应用于二级倒立摆控制系统,设计出具有期望主导极点的最优控制器,实现了对二级倒立摆系统的稳定控制。     

Pareto‐Set Based Multi‐Objective Dynamic Reactive Power and Voltage Control

A novel approach is proposed in this paper to solve multi‐objective dynamic reactive power and voltage control (Volt/VAR control, VVC). The method is able to attain the Pareto‐optimal solutions, based on the day‐ahead load forecast, for the VVC considering reducing daily power loss, enhancing voltage profile and optimizing dispatch schedules for on‐load tap changer (OLTC) and shunt capacitor switching, which will provide decision maker more options to schedule the dynamic VVC. This approach is simulated in IEEE14 buses system and IEEE30 buses system, and the results are encouraging with respect to performance in dynamic reactive power control. Moreover, the application in an actual distribution system verifies its effectiveness further.     

基于分布估计算法的人工神经网络优化设计

布估计算法是一类新的进化算法,它通过统计在当前群体中选出的个体信息给出下一代个体分布的概率统计,用随机取样的方法生成下一代群体。文章将建立在一般结构Gauss网络上的分布估计算法应用于人工神经网络的优化。仿真实验结果表明,分布估计算法用于优化神经网络,可以在很短的时间内收敛至全局最优解,避免了BP算法的不足,提高了网络的学习性能,从而为人工神经网络的优化提供了一种新的途径。     

Existence of Optimal Mild Solutions and Controllability of Fractional Impulsive Stochastic Partial Integro‐Differential Equations with Infinite Delay

In this paper, we investigate a new class of fractional impulsive stochastic partial integro‐differential equations with infinite delay in Hilbert spaces. By using the stochastic analysis theory, fractional calculus, analytic α‐resolvent operator and the fixed point technique combined with fractional powers of closed operators, we firstly give the existence of of mild solutions and optimal mild solutions for the these equations. Next, the controllability of the controlled fractional impulsive stochastic partial integro‐differential systems with not instantaneous impulses is presented. Finally, examples are also given to illustrate our results.     

Design Of Anti‐Slip Controller For An Electric Vehicle With An Adhesion Status Analyzer Based On The Ev Simulator

The In this paper, a simulator of a one‐wheel Electric Vehicle system is designed for testing an anti‐slip controller using the Motor‐Generator system. The drive motor of the M‐G system is used to simulate the drive wheel of the Electric Vehicle, and the load motor is used to simulate the load force of the chassis. In the driving process, the torque of the load motor is changed according to the drive force of the chassis that is calculated by the program. So it can simulate the dynamic process of the tire‐road system. Based on this simulator system, an anti‐slip controller based on an Adhesion Status Analyzer is proposed. Information about the wheel speed is acquired by using a Back EMF Observer. A load torque disturbance observer is designed to stabilize the acceleration of the wheels. The Adhesion Status Analyzer is used to generate safe acceleration commands for the anti‐slip controller. When a slip occurs, the anti‐slip controller will decrease the torque quickly, and at the same time, by estimating the dynamic status of adhesion, the Adhesion Status Analyzer will restrain the acceleration command within a safe area. The effectiveness of the proposed approach is verified by using the EV slip simulator.