Advanced Control Algorithm: Applications to Industrial Processes
Keywords:
Dynamic matrix control, predictive control, water heater.Abstract
As in the most industrial systems, a control of the
input of the systems including a classic regulator is a key point. The Proportional-Integral-Derivative controllers are commonly used in many industrial control systems and appeared suitable to stable the control of the majority of real processes. But in some cases like a non-minimum-phase plant or a plant with a dead-time proceed to a thin regulating of coefficients until to get
a system respecting the conditions specified. It is possible also to present a problem of overtaking with the increase of the gain or seems impotent for systems having a big delay and the use of sophisticated process controllers is required. Model predictive control is an important branch of automatic control theory, it
refers to a class of control algorithms in which a process model is used to predict and optimize the process performance. MPC has been widely applied in industry. Dynamic Matrix Control Algorithm belongs to the family of Model predictive control Algorithms where these algorithms only differ between themselves in the model that represents the process, disruptions and the function of cost. In this paper the study of the Dynamic
Matrix Control Algorithm are interested while applying him on processes of water heating and mechanical rotations of steering mirrors in a Light Detection and Ranging system as a second application. The objective of this work consists of solving the problem of prediction of the output and input of the process by
fixing a horizon finished N, and while considering the present state like initial state, to optimize a cost function on this interval, while respecting constraints. Therefore, the future reference is known and the system behavior must be predictable by an appropriate model. It results an optimal sequence of N control of it among which alone the first value will be applied effectively. As the time advances, the horizon of prediction slips and a new
problem of optimization is to solve while considering the state of the system updating. In summary, every moment, it is necessary to elaborate an optimal control sequence in open loop, refined systematically by the present measure arrival.
Downloads
Downloads
Published
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
