The classical controllers like PI or PID controllers are widely used in process industries because of their structure and their tuning is well known among all industrial operators. But these controllers have so many limitations. These controllers provide better performance only at a particular operating range. The specific control problems associated with the plant operations severely limit the performance of conventional controllers. The increasing complexity of plant operations together with tougher environmental regulations, rigorous safety codes and rapidly changing economic situation demand the need for more sophisticated process controllers. Model predictive controller (MPC) is an important branch in automated control theory. MPC refers to a class of control algorithm in which a process model is used to predict and optimize the process performance. In this project temperature in pasteurization process is controlled using model predictive controller. It show a good performance in keeping both the milk and water temperatures at the desired set points without any oscillation and overshoot.
[1]
Carlos F. Alastruey,et al.
Modelling and identification of a high temperature short time pasteurization process including delays
,
1999
.
[2]
Flavio Manenti,et al.
Nonlinear Model Predictive Control: A Self-Adaptive Approach
,
2010
.
[3]
Panagiotis D. Christofides,et al.
State-estimation-based economic model predictive control of nonlinear systems
,
2012,
Syst. Control. Lett..
[4]
M. Garcı́a-Sanz,et al.
Predictive control of a high temperature–short time pasteurisation process
,
2002
.
[5]
Ali Cinar,et al.
Modeling, monitoring and control strategies for high temperature short time pasteurization systems — 2. Lethality-based control
,
1998
.
[6]
J Prakash,et al.
Design of nonlinear PID controller and nonlinear model predictive controller for a continuous stirred tank reactor.
,
2009,
ISA transactions.
[7]
M. V. Pilipovik,et al.
Tuning a space–time scalable PI controller using thermal parameters
,
2005
.