This work combines the benefits of cascaded control, Smith predictor, moment matching, and outer-loop decomposition to design an enhanced series cascaded control approach with Smith Predictor for some industrial integrating plants. The inner-loop controller is assumed as a PI/PID type. If the outer-loop process model is of second-order, it is split into first-order models and an individual control-loop is established for each model. This technique is called ‘outer-loop decomposition’. PI controller is employed in the loop having a first-order lag whereas proportional control is used if the loop contains an integrator. Controller parameters are obtained by moment matching i.e. equating the Maclaurin series of expected and real closed-loop system functions. Suitable equations and procedures are given to tune adjustable parameters to attain an expected maximum sensitivity. This makes the proposed method more beneficial than the contemporary schemes that require a hit and trial search within a given range of values. It is seen that the suggested scheme yields noteworthy enhancement in closed-loop response compared to some recent strategies even in the presence of perturbed process dynamics.

这项工作结合了级联控制、Smith 预测器、力矩匹配和外环分解的优点，为一些工业集成工厂设计了一种带有 Smith 预测器的增强型串联级联控制方法。内环控制器假定为 PI/PID 类型。如果外环过程模型是二阶的，则将其拆分为一阶模型，并为每个模型建立单独的控制环。这种技术称为“外循环分解”。PI 控制器用于具有一阶滞后的回路，而如果回路包含积分器，则使用比例控制。控制器参数是通过力矩匹配获得的，即使预期和实际闭环系统函数的 Maclaurin 级数相等。给出了合适的方程和程序来调整可调参数以获得预期的最大灵敏度。这使得所提出的方法比需要在给定值范围内进行命中和试验搜索的当代方案更有益。可以看出，即使在存在扰动过程动力学的情况下，与一些最近的策略相比，所建议的方案在闭环响应方面也产生了显着的增强。