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Neurofuzzy model based l/sub /spl infin// predictive control of nonlinear CSTR system

机译:基于神经模糊模型的L / sub / spl infin //非线性CSTR系统的预测控制

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In this paper the nonlinear dynamics of a continuously stirred tank reactor (CSTR) are modelled with a neuro-fuzzy network, so that a predictive control strategy is developed based on the l/sub /spl infin// norm performance. Stability of the closed loop system is proved that the system is stable if each local linear control system is closed loop stable. The pH control in neutralisation process within the CSTR was simulated to indicate that the control performance is superior to that from quadratic predictive control.
机译:在本文中,使用神经模糊网络对连续搅拌釜反应器(CSTR)的非线性动力学进行建模,从而基于l / sub / spl infin //规范性能开发了一种预测控制策略。证明了闭环系统的稳定性,即如果每个局部线性控制系统都是闭环稳定的,则系统是稳定的。对CSTR中中和过程中的pH控制进行了模拟,表明该控制性能优于二次预测控制。

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