The coal pulverizing system equipped with ball mills is a nonlinear, long delay, and closed coupling multivariable system, its automatic control being a research hot spot all along. 钢球磨煤机制粉系统是一个非线性、大滞后、强耦合的多变量系统,其自动控制一直是热控领域的研究热点。
A kind of fuzzy-neuro network ( FNN) adaptive control law was proposed for a class of nonlinear multivariable system that include unknown functions and external disturbances. 针对一类数学模型不完全确知并包含外部扰动的非线性多变量系统,提出一种模糊神经网络(FNN)自适应控制策略。
Test Signal Design for High/ Low Pass Multivariable System Identification 高/低通复合多通道系统辨识的测试信号设计
Automatic tuning multivariable system coordinated control pole placement; 自整定;多变量系统;协调控制;极点配置;
New Design Method of Decentralized PID for Multivariable System 一种新的多变量系统分散PID参数设计方法
Research and Application on Approximate Model Design Method for Multivariable System Based on Genetic Algorithm 基于遗传算法的多变量系统近似模型设计方法研究与应用
The method also achieves good decoupling control results in this multivariable system. Finally, the paper gives the simulation results that meet the engineering demands. 最后,考虑到工程应用的实际情况,给出了满足工程要求的卫星天线跟踪指向控制系统数学仿真结果。
Auxiliary Regulatory Control Design of Multivariable System in Industrial Process 工业过程多变量系统的辅助常规控制设计
PID control Automatic tuning Expert control Multivariable system; PID控制;自整定;专家控制;多变量系统;
Robust control for a combined shape and gauge multivariable system in hot strip rolling 热连轧板形板厚多变量系统鲁棒控制
The classical system identification methods have many limits and shortages, especially for multivariable system. 对于系统辨识,经典的方法存在着一定的局限性和不足,尤其对于多变量系统,经典的方法得不到很好的辨识效果。
This paper discusses the optimal model-reduction problem of a multivariable system with sine-function input. 本文讨论了在正弦函数输入时高阶模型的最优简化问题。
Decoupling control is an effective method in multivariable system control. 解耦控制是多变量系统控制的有效手段。
Decoupling Control Method and Its Simulation Research of Linear Unknown Multivariable System Based on FNN 基于模糊神经网络的线性不确定多变量系统解耦控制方法及仿真研究
Structural identification of a multivariable system is very troublesome. 多变量系统的结构辨识是很麻烦的,Guidorzi提出了一个辨识不变性指标的方法,但必须用矩阵求逆。
Research and Application of Multivariable System Identification 多变量系统辨识的研究与应用
Decoupling Control with Exact Model Matching and Adaptive Decoupling Control for Multivariable System 多变量系统的精确模型匹配解耦控制与自适应解耦控制
This control system is a 2 × 2 multivariable system. 该控制系统是一个2×2多变量系统。
Variable Structure Prediction Control for Multivariable System with Time-delay 时滞多变量系统的变结构预测控制
In this paper, a new method of time-varying multivariable system identification is presented, and the convergence of the algorithm is analyzed. 本文提出时变多变量系统辨识的一种新方法,并分析了算法的收敛性和稳定性。
A new design method is proposed for multivariable system to realize the fault-tolerant control against sensor failures. 本文研究了对任意传感器故障系统的容错设计问题。
This paper presented a simulation method for multivariable system having multiple time delays, which is implemented using the C programming language. The simulation results for actual systems are satisfactory. 本文提出了一种多变量多重时延系统的仿真方法,用C语言实现了程序设计,并对实际时延系统进行了仿真,取得满意的结果。
New Decoupling Method Based on Neural Network for Multivariable System 多变量系统的神经网络解耦新方法
The self-learning method of neuron decoupling and its mechanism in multivariable system are analysed. 文章以三输入三输出系统为例,详细分析了神经元解耦的学习方法,及其在多变量系统中的工作机理。
The result of simulation shows the algorithm is an efficient way to deal with the multivariable system. 仿真表明,该算法是一种有效的处理多变量系统的方法。
Robust Diagonal Dominance and Application in Multivariable System Robust Design 鲁棒对角优势及在多变量系统鲁棒设计中应用
The presented algorithm is also generalized to the multivariable system. 该算法也被推广到多变量系统。
The application of IMC in multivariable system with multiple time delays was discussed and Multivariable Internal Model control Algorithm proposed by Garcia and Morari was improved. 本文讨论了内模控制算法在多变量多时滞系统上的应用,并且改进了Garica和Morari提出的多变量内模控制算法。
The multivariable robust control system for a power boiler combustion process is designed and simulated with multivariable system robust design CAD platform. 使用多变量系统鲁棒设计CAD平台对某电厂锅炉燃烧过程设计了多变量鲁棒控制系统,并进行了数值仿真。
For the multivariable system with autoregressive noise, an identification model is derived. 针对类多变量输出误差自回归系统,推导了其辨识模型。