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:
- Improving product quality
- Increasing production rates of desired products
- Reduction in unwanted by-products
- Optimization of utilities
- Reducing environmental pollution
- More stable plant and equipment operation
- Increasing automation and modernization
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.