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Normalized Normal Constraint Algorithm Based Multi-objective Optimal Tuning of Decentralised PI Controller of Nonlinear Multivariable Process - Coal Gasifier

机译:基于标准化的非线性多变量过程分散PI控制器的基于多目标最佳调谐 - 煤气化器

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Almost all the industrial processes are multivariable in nature and are very difficult to control, since it involves many variables, strong interactions and nonlinearities. Conventional controllers are most widely used with its optimal parameters for such processes because of its simplicity, reliability and stability. Coal gasifier is a highly nonlinear multivariable process with strong interactions among the loop and it is difficult to control at 0% operating point with sinusoidal pressure disturbance. The present work uses Normalized Normal Constraint (NNC) algorithm to tune the parameters of decentralised PI controller of coal gasifier. Maximum absolute error (AE) and Integral of Absolute Error (IAE) are objective function while the controller parameters of decentralised PI controller are the decision variables for the NNC algorithm. With the optimal controller the coal gasifier provides better response at 0%, 50% and 100% operating points and also the performance tests shows good results.
机译:几乎所有的工业过程都是多变量的,非常难以控制,因为它涉及许多变量,强烈的相互作用和非线性。由于其简单性,可靠性和稳定性,传统的控制器最广泛地利用其最佳参数。煤气化器是一种高度非线性多变量的过程,在回路之间具有强烈的相互作用,并且难以在0%的操作点中控制,具有正弦压力干扰。目前的工作使用标准化的正常约束(NNC)算法来调整煤气化器分散PI控制器的参数。最大绝对误差(AE)和绝对误差(IAE)的积分是客观函数,而分散式PI控制器的控制器参数是NNC算法的判定变量。利用最佳控制器,煤气化器在0%,50%和100%的操作点提供更好的反应,并且性能测试显示出良好的效果。

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