Introduction:
Need for automation and process control was felt back in early 1900’s, old factory mills, distilleries, breweries, mechanical transmission, and in many other examples. Since the 1960’s the field of process control has generated numerous money-saving ideas. Therefore, has become increasingly important in chemical and petrochemical plants, oil refineries and in other manufacturing units in order to improve and keep stable their entire operation and production. Process control continues to be one of the most fascinating and growing areas with tremendous future prospects related to economy, safety and process stability. Optimal process control strategy can help by:
The primary control layer is the backbone of process control hierarchy and it supports all advanced control and complex optimization applications. Study of the chemical and other manufacturing plants reveals that often the modern, complex advanced control applications receive primary focus and often the underlying bottom-layer, primary control, issues are somewhat neglected because of lesser emphasis.
The heart and soul of a primary control layer is an PID controller. The PID control algorithm is the oldest, yet most popular and widely used control method. Amazingly, the PID control algorithm is unclear and misunderstood by many. If understood clearly, the PID control algorithm can provide, tremendous benefits, control improvements in a simple and robust manner.
The PID controller is basically a Proportional, Integral & Derivative algorithm-based controller which works on the output sum of these three terms. Each of these terms in most of the times depends on the error (e ). Error is the calculation value between the desired process output i.e. Set Point (SP), set by the operator or some advanced process control logic and the actual measurement signal i.e. Process Value (PV), coming from the field measurement sensor. According to the present and past error values the controller Output (OP) is generated by the algorithm, which moves final control element (valves, motors, etc. ), in order to minimize the error. In the PID control algorithm PID parameters play a key role, where the most effective control action depends on their optimal values, as shown in Figure 1.