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APPLICATIONS OF IDENTIFICATION METHOD OF VOLTERRA KERNELS OF NONLINEAR SYSTEMS TO PRACTICAL PROCESSES

非线性系统Volterra核辨识方法在实际过程中的应用

基本信息

批准号：
10650435
负责人：
KASHIWAGI Hiroshi
金额：
$ 2.05万
依托单位：
KUMAMOTO UNIVERSITY
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1998
资助国家：
日本
起止时间：
1998 至 1999
项目状态：
已结题

项目摘要

Identification of nonlinear control system is an important task for designing controller to obtain high performance of the actual processes. Although almost all control systems are strictly speaking nonlinear, the identification of nonlinear system is so far not yet well investigated. The authors have recently developed a new method of obtaining Volterra kernels of nonlinear system by use of pseudorandom M-sequence. Computer simulation showed that this identification method is effective with wide applications.Under this Grant-in-Aid, the authors investigated the possibility of applying the author's method to two actual processes. One is the application to the identification of nonlinear mechatro-servo system; robot manipulator. We applied M-sequence to driving torque of a robot manipulator and the movement angle is measured, Taking the crosscorrelation between them, we obtain Volterra kernels of up to 3rd order. Comparison of the estimated output calculated from the obtained Volterra k … More ernels and the actual output shows a good agreement between them. This result is published in Proc. IMEKO-XV held in Osaka, Japan, in 1999 (Ref. 10). Identification of nonlinear system having backlash type nonlinearity is also investigated and the results are published in Proc. '99KACC held in Seoul, Korea, in 1999 (Ref.13).The other application of our nonlinear identification is to the identification of nonlinear chemical processes. This time we adopted Continuous Stirred Tank Reactor (CSTR), which is known as bilinear system, as the nonlinear process to be identified. The result shows that our method of nonlinear identification is very effective for nonlinear chemical processes. This result is published in Proc. ASCC which will be held in Shanghai, China, 2000(Ref. 14). The authors also applied our method to Model Predictive Control (MPC) of nonlinear chemical process, since it is thought that when we use more accurate model for MPC of nonlinear chemical processes, the control performance would be much better compared with using inaccurate model, Simulation result shows that our method on nonlinear process identification is also effective for MPC of chemical processes. This result is published in Proc. KACC'98 held in Pusan, Korea, in l998 (Ref. 7). Less

为了获得实际过程的高性能，非线性控制系统的辨识是控制器设计的重要任务。虽然几乎所有的控制系统都是严格意义上的非线性系统，但对非线性系统的辨识问题至今还没有得到很好的研究。作者最近发展了一种利用伪随机M序列获得非线性系统Volterra核的新方法。计算机仿真表明，该辨识方法是有效的，具有广泛的适用性。在此基础上，研究了作者的方法在两个实际过程中应用的可能性。一是在非线性机电伺服系统辨识中的应用；机器人机械手。将M序列应用于机械手的驱动力矩，并测量其运动角度，利用它们之间的互相关性，得到高达3阶的Volterra核。根据获得的Volterrak…计算的估计产量的比较更多的Ernels和实际产出表明它们之间有很好的一致性。这一结果发表在Proc上。1999年在日本大阪举行的IMEKO-XV(参考文献)10)。对具有齿隙类型非线性的非线性系统的辨识也进行了研究，其结果发表在Proc。99KACC会议于1999年在韩国首尔举行(参考文献13)。我们的非线性辨识的另一个应用是非线性化学过程的辨识。本文采用连续搅拌釜式反应器(CSTR)，即双线性系统，作为待辨识的非线性过程。结果表明，本文提出的非线性辨识方法对非线性化工过程是非常有效的。这一结果发表在Proc上。中国国际科学促进会将于2000年在上海举行。14)。将该方法应用于非线性化工过程的模型预测控制(MPC)中，认为对非线性化工过程的模型预测控制采用较精确的模型时，控制性能会比采用不准确的模型时要好得多，仿真结果表明本文提出的非线性过程辨识方法同样适用于化工过程的预测控制。这一结果发表在Proc上。1998年在韩国釜山举行的KACC‘987)。较少