M.Bharathi, C.Selvakumar
Designing control systems for complete plants is the ultimate goal of a control designer. The problem is quite large and complex. It involves a large number of theoretical and practical considerations such as quality of controlled response; stability; the safety of the operating plant; the reliability of the control system; the range of control and ease of startup, shutdown, or changeover; the ease of operation; and the cost of the control system. The difficulties are aggravated by the fact that most of the industrial and chemical processes are largely nonlinear, imprecisely known, multivariable systems with many interactions. The measurements and manipulations are limited to a relatively small number of variables, while the control objectives may not be clearly stated or even known at the beginning of the control system design. Thus, the presence of process input-output time delay of different magnitude in multi-input-multi-output systems have drawn attention to research as the processes are difficult to control. Increase in complexity and interactions between inputs and outputs yield degraded process behavior. Such processes are found only in process industries as they arise from the design of plants that are subject to rigid product quality specifications, are more energy efficient, have more material integration, and have better environmental performance. Multivariable systems contain more than one controlled variable (outputs) or manipulated variables (inputs). Thus the control of these MIMO systems plays a major role and has been interesting various engineers in the recent years. In process control industries, more than 95% of the control loops are of PI/PID type. This is mainly attributed to its effectiveness and relatively simple structure, which can be easily understood and implemented in practice. Consequently, the research on PID control algorithm development and their applications is still a very active area; many formulas have been derived to tune the PID controllers over the years. For easier field implementation, it is desirable to apply well established single loop PID tuning principles to the MIMO processes. However, compared with single-input single single-output (SISO) counterparts, MIMO systems are more difficult to control due to the existence of interactions between input and output variables. Adjusting controller parameters of one loop affects the performance of the others, sometimes to the extent of destabilizing the entire system. To ensure stability, many industrial controllers are tuned loosely, which causes inefficient operation and higher energy costs. Thus, an efficient design methodology which ensures both the plant stability as well as the increased productivity is the need of the hour.