航空三相静止变流器死区效应分析与补偿

为了解决航空三相静止变流器输出波形失真问题,详细分析了死区效应造成电压畸变的原因和由此带来的谐波成分.采用正弦脉宽调制(SPWM)控制技术,使变流器输出的波形更接近于正弦波,提出了设置死区与电压补偿相结合的控制方法,并通过SABER进行了仿真分析.同时,利用TMS320F2812数字芯片实现了相应的补偿策略.仿真和试验结果证明了该控制方法的有效性.     

执行机构含死区环节的自适应补偿控制

火电厂炉膛负压控制系统中有时含死区类的强非线性环节，死区使该控制回路产生振荡，仅用常规PID控制器无法克服这一现象。为此，该文提出了一种用自适应死区逆对控制回路进行补偿的方法。该方法用描述死区特性的参数构造死区逆来补偿控制器输出；同时又由于死区是未知和时变的，所以用一种鲁棒自适应更新律对死区参数进行在线更新，从而达到用死区逆完全抵消死区影响的目的。仿真试验结果表明，该文的方法几乎能让系统恢复到线性状况，并且死区参数收敛，证明了方法的有效性。     

死区非线性系统特性分析及补偿控制

针对含有非线性"死区"环节的热工控制对象,用线性系统理论和描述函数方法分析了系统的动态特性,给出了可选择的控制器的类型和参数的极限值;为了克服"死区"对闭环系统性能的影响,建立了偏差信息与死区参数之间的关系,构造了一个动态"死区逆模型"来修正控制器的输出,试验结果表明,所设计的动态逆模型可以完全补偿死区特性的影响,这种方法简单、可行.     

Control of an overlap-type proportional directional control valve using input shaping filter

In a hydraulic control system (herein, termed a major control loop), a proportional directional control (PDC) valve with spool position feedback may work in a minor (or inner) control loop. In this study the authors propose control designs to improve the performance of the PDC valve control loop (a minor control loop). At first, the mathematical model for the PDC valve is developed through an experimental identification process. Then, a dead-zone compensator that facilitates jumping of the overlap zone in spool/sleeve combination is devised and applied. A reference input following controller (including PI-D and feed-forward controller) that enables robust control of the PDC valve under disturbances is devised using the pole placement method and the zero placement method. Subsequently, an input shaping filter is incorporated into the devised control system to improve the reference following characteristic in high frequency range. Finally, the effectiveness of the proposed control design is verified experimentally.     

Recursive identification for Hammerstein–Wiener systems with dead-zone input nonlinearity

A new recursive algorithm is proposed for the identification of a special form of Hammerstein–Wiener system with dead-zone nonlinearity input block. The direct motivation of this work is to implement on-line control strategies on this kind of system to produce adaptive control algorithms. With the parameterization model of the Hammerstein–Wiener system, a special form of model estimation error is defined; and then its approximate formula is given for the following derivation. Based on these, a recursive identification algorithm is established that aims at minimizing the sum of the squared parameter estimation errors. The conditions of uniform convergence are obtained from the property analysis of the proposed algorithm and an adaptive setting method for a weighted factor in the algorithm is given, which enhances the convergence of the proposed algorithm. This algorithm can also be used for the identification of the Hammerstein systems with dead-zone nonlinearity input block. Three simulation examples show the validity of this algorithm.     

Identification and adaptive neural network control of a DC motor system with dead-zone characteristics

In this paper, an adaptive control approach based on the neural networks is presented to control a DC motor system with dead-zone characteristics (DZC), where two neural networks are proposed to formulate the traditional identification and control approaches. First, a Wiener-type neural network (WNN) is proposed to identify the motor DZC, which formulates the Wiener model with a linear dynamic block in cascade with a nonlinear static gain. Second, a feedforward neural network is proposed to formulate the traditional PID controller, termed as PID-type neural network (PIDNN), which is then used to control and compensate for the DZC. In this way, the DC motor system with DZC is identified by the WNN identifier, which provides model information to the PIDNN controller in order to make it adaptive. Back-propagation algorithms are used to train both neural networks. Also, stability and convergence analysis are conducted using the Lyapunov theorem. Finally, experiments on the DC motor system demonstrated accurate identification and good compensation for dead-zone with improved control performance over the conventional PID control.     

一种新的基于二阶神经网络的执行器死区补偿方法

针对执行器的未知宽度的死区非线性环节,提出一种基于神经网络死区补偿的新方法。该补偿器采用了两个神经网络。一个是用来预测未知的死区,另外一个则在前向反馈通路中提供适当的补偿。仿真结果表明该补偿策略对于对称的和非对称的死区非线性都是有效的。     

电液伺服振动台加速度谐波抑制

由于电液伺服振动台中存在着伺服阀死区、连接铰间隙和摩擦力以及液压缸摩擦力等非线性因素,导致振动台在正弦信号激励下,其加速度响应信号中存在高次谐波失真现象。在对死区、间隙、摩擦补偿相关文献的研究基础上,针对加速度信号中的高次谐波,提出了基于自适应陷波器技术的自适应谐波抑制策略。其参考信号频率为要抑制的谐波频率,利用最小均方自适应滤波算法,根据输入加速度信号与反馈加速度信号间的误差信号,实时在线调整自适应滤波器的权值。参考信号经过自适应滤波器的加权作用,得到自适应滤波器的输出,它是一个谐波复制信号,并与输入加速度信号相加,以抑制输出加速度信号中的谐波,进而使总谐波失真度大大降低。