Adaptive control of permanent magnet synchronous machines with disturbance estimation

In this paper,an adaptive control scheme is introduced for permanent magnet synchronous machines (PMSMs)as an alternative to classical control techniques.The adaptive control strategy capitalizes on the machine’s inverse dynamics to achieve accurate tracking by using an observer to approximate disturbance in the form of friction and load torque.The controller’s output is then fed to a space vector pulse width modulation(SVPWM)algorithm to produce duty cycles for the inverter.The control scheme is validated through a set of simulations on an experimentally validated PMSM model.Results for different situations highlight its high speed tracking accuracy and high performance in compensating for friction and load disturbances of various magnitudes.     

Design of internal model control based fractional order PID controller

This article presents a design of the internal model control(IMC)based single degree of freedom(SDF) fractional order(FO)PID controller with a desired bandwidth specification for a class of fractional order system(FOS). The drawbacks of the SDF FO-IMC are eliminated with the help of the two-degree of freedom(TDF)FO PID controller. The robust stability and robust performance of the designed controller are analyzed using an example.     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.     

基于交流比例积分控制器的单相逆变器

提出一种电感电流、输出电压瞬时值反馈控制和负载电流前馈控制相结合的复合控制策略。在此基础上,研制了一台800W的单相逆变器。实验结果表明,提出的控制策略改善了逆变器输出电压的波形,提高了系统的暂态特性。     

电视监控系统云台控制器设计

电视监控系统是一种典型的分布式计算机信号采集系统。为了提高监控的范围和效果,云台控制器的优劣直接影响监控的范围和效果,因此对云台控制器的设计具有重要的意义。本系统采用串型通信,通过Modbus协议把控制信号输入单片机,经过对AT89S52单片机的编程,从而对八路继电器输出进行控制。系统不仅结构简单,而且还可以方便的对镜头、防护罩的控制进行扩展,功能强大,可以广泛应用于电视监控系统中的云台控制。     

P2P网络中的超级节点选取算法研究

P2P系统在构建覆盖网络时未考虑到与物理网络的结合,导致逻辑拓扑结构与物理拓扑结构严重不匹配问题,增加P2P相邻节点间的延迟。本文提出一种基于区域划分的超级节点选取机制,将P2P网络中的节点按照物理位置划分成若干区域,保证区域内节点在物理位置上是相近的。利用MATLAB进行仿真实验,仿真实验表明使用这种机制能降低半分布式P2P网络的信息检索延迟,有效地提高检索的效率,并且具有较好的可扩展性。     

反倾岩质边坡弯曲倾倒-剪切滑移破坏分析方法研究

目前反倾岩质边坡弯曲倾倒破坏分析方法仍以基于极限平衡理论的悬臂梁模型为主,但大多未考虑坡脚岩层的剪切破坏。为准确评价该类边坡的稳定性,建立考虑坡脚岩层剪切破坏的分析计算方法。首先,根据岩层变形破坏特征,将边坡分为后缘稳定区、中部弯曲倾倒区和前缘剪切区3个区域;其次,建立弯曲倾倒-剪切滑移破坏模式的稳定性分析方法;最后,通过工程实例验证,并进行参数分析。研究结果表明:提出的分析方法与工程实际符合性较好;边坡在倾角较陡、坡角较大时稳定性最差,坡角对边坡稳定性影响大于岩层倾角的影响;岩层厚度及层面内摩擦角增加有利于边坡稳定性,且会扩大坡脚剪切区范围。研究成果对反倾岩质边坡破坏的防治具有实践指导意义。     

Environmental Perception with Spatial Regularization Correlation Filter for Visual Tracking

With the introduction of correlation filtering (CF), the performance of visual object tracking is significantly improved. Circular shifts collecting samples is a key component of the CF tracker, and it also causes negative boundary effects. Most trackers add spatial regularization to alleviate boundary effects well. However, these trackers ignore the effect of environmental changes on tracking performance, and the filter discriminates poorly in the background interference. Here, to break these limitations, we propose a new correlation filter model, namely Environmental Perception with Spatial Regularization Correlation Filter for Visual Tracking. Specifically, we use the Average Peak to Correlation Energy (APCE) and the response value error between the two frames together to perceive environmental changes, which adjusts the learning rate to make the template more adaptable to environmental changes. To enhance the discriminatory capability of the filter, we use real background information as negative samples to train the filter model. In addition, the introduction of the regular term destroys the closed solution of CF, and this problem can be effectively solved by the use of the alternating direction method of multipliers (ADMM). Extensive experimental evaluations on three large tracking benchmarks are performed, which demonstrate the good performance of the proposed method over some of the state-of-the-art trackers.