基于模糊神经网络的变换器自适应控制方法

提出了一种新型的基于模糊神经网络自适应PI调节电流控制电压型PWM变换器方法.结合了模糊神经网络控制与PI控制器,根据三相电流比较产生的三相电流误差和电流误差变化率,自动调整P、I参数,提高了电流的控制精度和变换器的动态性能.采用MATLAB/Simulink对常规PI控制器和模糊神经网络自适应PI控制器进行了仿真对比.仿真结果表明了采用模糊神经网络自适应PI控制器,其系统输出的误差及误差变化要小,系统的跟踪精度得以提高,动态性能得到改善.     

基于最优模糊PID温度控制方法研究

针对某智能大厦空调的温度控制系统,引入了一种新的模糊推理方法,设计了模糊PID控制器.该模糊推理方法将优化和反馈的思想引入推理过程中,依据不同的优化指标进行推理,使推理过程更为有效,论文给出了应用该推理方法的具体过程.以建立起的温度系统模型为基础,设计了基于最优模糊推理的温度系统模糊PID控制器,进行了仿真研究,仿真结果和实际运行表明了该控制方法具有强鲁棒性和良好控制品质.     

电力有源滤波器控制器的研究与仿真分析

建立了包括有源电力滤波器（ＡＰＦ）在内的公共连接点（ＰＣＣ）的数学模型;针对实际控制器计算过程中的时间延迟,提出对负载电流值进行预测的两种算法,对逆变器的开关元件提出一种新型脉宽调制（ＰＷＭ）控制方案,并采用电力电子仿真软件包进行了仿真验证。     

Tuning of multi-loop PI controllers based on gain and phase margin specifications

In this paper, a single-iteration strategy is proposed for the design of a multi-loop PI controller to achieve the desired gain and phase margins for two-input and two-output (TITO) processes. To handle loop interactions, a TITO system is converted into two equivalent single loops with uncertainties drawn from interactions. The maximum uncertainty is estimated for the initial controller design in one loop and single-input and single-output (SISO) controller design is applied. This controller is substituted to other equivalent loop for design, and finally, the first loop controller is refined on knowledge of other loop controller. For SISO controller tuning, a new method is presented to determine the achievable gain and phase margins as well as the relevant controller parameters. Examples are given for illustration and comparison.     

Robust parametric CMAC with self-generating design for uncertain nonlinear systems

In this paper, a robust parametric cerebellar model articulation controller (RP-CMAC) with self-generating design, called RPCSGD, is proposed for uncertain nonlinear systems. The proposed controller consists of two parts: one is the parametric CMAC with self-generating design (PCSGD), which is utilized to approximate the ideal controller and the other is the robust controller, which is designed to achieve a specified H^∞ robust tracking performance of the system. The corresponding memory size of the proposed controller can be suitably constructed via the self-generating design. Thus, the useless or untrained memories will not take possession of the space. Besides, the concept of sliding-mode control (SMC) is adopted so that the proposed controller has more robustness against the approximated error and uncertainties. The stability of the system can be guaranteed surely due to the derivations of the adaptive laws of the proposed RPCSGD based on the Lyapunov function. Finally, the proposed controller is applied to the second-order chaotic system and the one-link rigid robotic manipulator. The tracking performance and effectiveness of the proposed controller are verified by simulations of the computer.     

Controlling the diffusionless Lorenz equations with periodic parametric perturbation

Diffusionless Lorenz equations (DLE) are a simple one-parameter version of the well-known Lorenz model, which was obtained in the limit of high Rayleigh and Prandtl numbers, physically corresponding to diffusionless convection. A simple control method is presented to control chaos by using periodic parameter perturbation in DLE. By using the generalized Melnikov method, the parameter conditions could be obtained to guide the controlled DLE to a low-periodic motion. Moreover, the existence conditions of periodic orbits and homoclinic orbits in the system are given. Some results of the numerical simulation are also explained clearly by a rigorous analysis.     

A novel associative memory approach to speech enhancement in a vehicular environment

Numerous attempts have been undertaken to apply the spectral subtraction method to cancel noise perturbations but these efforts have yet to produce an algorithm that is able to adapt well to the environmental changes in the perturbations. In addition, the variants of the spectral subtraction method so far proposed in the literature would require a non-voice activity detector (NVAD), for a single microphone system, to store the perturbation. This is used as an estimate for the reference signal. Inaccuracy in the perturbation estimates causes the cleaned speech to be corrupted by musical artifacts, which is unacceptable. Post processing of signals corrupted by the musical artifacts is very costly. This paper provides an alternative approach that employs associative memory for speech enhancement. Extensive comparison is made using the soft computing approaches for noise cancellation based on associative memories. A set of stereo microphones captures the corrupted speech in a vehicle and is used to point to the closest associative memory location. The Wiener filter approach is used to cancel the noise. The paper discusses novel examples of the associative memories using the cerebellum model for noise modeling. Experimental results show the potential of these novel soft computing architectures in generating and adapting the required Weiner filters to cancel perturbation even at signal to noise ratio (SNR) of less than −13 dB.     

基于网络状态参数估计的主动队列管理PI改进算法

作为一种重要的主动队列管理手段,PI控制器算法通过积分嚣的引入有效地消除了队列长度控制的稳态误差,在提高网络吞吐的同时缩短了排队时延.但是PI控制器不能根据网络状态变化而自动调整控制参数,故当网络流量变化时PI控制器的收敛速度很慢.基于TCP-AQM系统模型,对经过中间节点的活动连接数、平均往返时间和前向链路容量等3个参数进行估计.通过计算击中概率的倒数,估计出活动流数;通过计算单位时间的数据包数,估计出网络容量;通过往返时延、活动流数、网络容量以及丢包概率在稳态时的关系式,估算出平均往返时延.在此基础上,提出了对网络状态变化自适应调整控制参数改进的快速收敛PI算法——FCPI算法.仿真结果表明,该算法有效提高了算法的收敛速度,并且鲁棒性好,易于实现,适用于未来高速网络的路由器.     

油田污水处理站自控系统的优化设计

随着网络技术和多媒体技术的不断发展,传统的工业控制模式也需要不断引入新技术来满足当今社会对控制和管理的新要求.文中着重介绍了对新疆新港公司油田污水处理站监控系统的优化升级.其中采用了一体化控制理念,选用了将PLC控制、网络通讯、视频监控、数据存贮集成于一体的控制器,使控制系统的功能得到了增强.该系统已投入运行两年多,稳定可靠,具有良好的应用和推广价值.