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System Parameters’ Identification and Optimal Tracking Control for Nonlinear Systems

机译:非线性系统的系统参数辨识与最优跟踪控制

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This paper proposes a parameters’ identification methodology via the continuous-time least-squares algorithm for those nonlinear systems which are linear with respect to their parameters. The parameter identification method can be used for easily determining all the parameters in real plants from only input-output data measurements, such that a posteriori, a model-based control strategy can be synthesized. It is worth mentioning that when a control engineer wants to design a modern and sophisticated controller, usually the system model is used for such purposes, which depends on its parameters, however, in general the system parameters are not easy to determine. Also, this paper uses the parameters’ identification methodology for the design of an optimal tracking controller for state-dependent coefficient factorized (SDCF) nonlinear systems. Both, the parameters’ identification scheme and the optimal control strategy are applied via simulations for the control of a Permanent Magnet Synchronous Motor (PMSM), a three-phase nonlinear machine.
机译:本文针对那些参数线性的非线性系统,提出了一种基于连续时间最小二乘算法的参数辨识方法。参数识别方法可用于仅从输入输出数据测量值轻松确定实际工厂中的所有参数,从而可以合成基于模型的后验控制策略。值得一提的是,当控制工程师要设计现代而复杂的控制器时,通常将系统模型用于此目的,这取决于其参数,但是总的来说,系统参数不容易确定。此外,本文还使用参数的识别方法来设计状态依赖系数分解(SDCF)非线性系统的最佳跟踪控制器。参数的识别方案和最佳控制策略均通过仿真来控制三相非线性机器永磁同步电动机(PMSM)。

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