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Operating Range Scheduled Robust Dahlin Algorithm to Typical Industrial Process with Input Constraint

机译:操作范围预定强大的Dahlin算法与输入约束的典型工业过程

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摘要

There is a class of typical nonlinear industrial process, which can be characterized by a first-order inertia plus pure delay model in an operating range, but the model parameters are different in different operating ranges. Usually, a set of Proportion Integration Differentiation (PID) controllers may be used to control the process, and the controllers have different parameters in different operating areas. However, the adjustment process of the PID controllers' parameters is not an easy job in practice, and the control performance may also be not perfect. The Dahlin algorithm may provide very good control performance for the process, but its control performance may become very poor if the model parameters are not accurate and/or the input is constrained. Faced with this issue, this paper proposes an Operating-Range Scheduled Robust Dahlin Algorithm (ORSRDA) for the process control with input constraint, which is designed on the basis of a nominal first-order inertia plus pure delay model and the given parameters uncertainty. The process operating ranges are divided into pre-designed several zones according to the difference between output setting value and current output when a new setting appears. For each operating range, the parameters of ORSRDA are obtained by solving a min-max problem offline to guarantee the closed-loop system's robust stability and acquire the best step-response control performance. To eliminate the steady state error, the integration control action is added into the ORSRDA when the system output is close to its setting value. The proposed method is applied to temperature control of an experimental electric furnace to demonstrate its effectiveness and implement procedure.
机译:存在一类典型的非线性工业过程,可以在操作范围内的一阶惯性加纯延迟模型表征,但模型参数在不同的操作范围内不同。通常,可以使用一组比例集成区分(PID)控制器来控制处理,并且控制器在不同的操作区域中具有不同的参数。然而,PID控制器参数的调整过程在实践中不是一个简单的作业,并且控制性能也可能不完美。 Dahlin算法可以为该过程提供非常好的控制性能,但如果模型参数不准确和/或输入受约束,则控制性能可能变得非常差。面对此问题,本文提出了一种用于输入约束的过程控制的工作范围预定的鲁棒算法(ORSRDA),其基于标称一阶惯性加上纯延迟模型和给定的参数不确定性设计。根据出现新设置时,根据输出设定值和电流输出之间的差异,将过程操作范围分为预先设计的多个区域。对于每个工作范围,通过求解偏心最小的问题以确保闭环系统的鲁棒稳定性并获取最佳阶跃响应控制性能来获得orsRDA的参数。为了消除稳态误差,当系统输出接近其设置值时,将集成控制操作添加到ORSRDA中。该方法应用于实验电炉的温度控制,以证明其有效性和实施过程。

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