Wyniki wyszukiwania - BazTech

1

On-line process identification using the Modulating Functions Method and non-asymptotic state estimation

Byrski Witold, Drapała Michał

Archives of Control Sciences

|

2022

|

Vol. 32, No. 3

535--555

EN

The paper presents an iterative identification method dedicated for industrial processes. The method consists of two steps. In the first step, a MISO system is identified with the Modulating Functions Method to obtain sub-models with a common denominator. In the second step, the obtained subsystems are re-identified. This procedure enables to obtain the set of models with different denominators of the transfer functions. The algorithm was used for on-line identification of a glass conditioning process. Identification window is divided into intervals, in which the models can be updated based on recent process data, with the use of the integral state observer. Results of the performed simulations for the identified models are compared with the historical process data.

2

Online continuous-time adaptive predictive control of the technological glass conditioning process

Drapała Michał, Byrski Witold

Archives of Control Sciences

|

2022

|

Vol. 32, No. 4

755--782

EN

Glass production has a great industrial importance and is associated with many technological challenges. Control related problems concern especially the last part of the process, so called glass conditioning. Molten glass is gradually cooled down in a long ceramic channels called forehearths during glass conditioning. The glass temperature in each zone of the forehearth should be precisely adjusted according to the assumed profile. Due to cross-couplings and unmeasured disturbances, traditional control systems based on PID controllers, often do not ensure sufficient control quality. This problem is the main motivation for the research presented in the paper. A Model Predictive Control algorithm is proposed for the analysed process. It is assumed the dynamic model for each zone of the forehearth is identified on-line with the Modulating Functions Method. These continuous-time linear models are subsequently used for two purposes: for the predictive controller tuning, measurable disturbances compensation and for a static set point optimisation. Proposed approach was tested using Partial Differential Equation model to simulate two adjacent zones of the forehearth. The experimental results proved that it can be successfully applied for the aforementioned model.

3

State estimators and observers for continuous and discrete linear systems. Part 2. Integral observers for exact state reconstruction

Byrski Jędrzej, Byrski Witold

Science, Technology and Innovation

|

2019

|

Vol. 5, no. 2

23--33

EN

In the paper, the exact state observers will be presented. The state estimators and observers can be used in technical processes for many purposes like the fault detection and diagnosis, the implementation of the state controllers, and soft reconstruction of inaccessible for measurements variables of the system. As the standard, for continuous systems the differential estimators of Kalman filter or Luenberger type observer are commonly used. However, if the initial conditions of the real state are unknown, both estimators guarantee only an asymptotic quality of the real state tracking. The paper presents another type of the state observers, which for continuous system have the structure given by two integral operators. Based on measurements of the system input and output signals on some predefined finite time interval T, they can reconstruct the initial state exactly. In on-line version, the exact state reconstruction is performed continuously for every t, based on special procedure executed within two moving windows of width T, on sliding time interval [t-T, t].

4

An adaptive identification method based on the modulating functions technique and exact state observers for modeling and simulation of a nonlinear MISO glass melting process

Byrski Witold, Drapała Michał, Byrski Jędrzej

International Journal of Applied Mathematics and Computer Science

|

2019

|

Vol. 29, no. 4

739--757

EN

The paper presents new concepts of the identification method based on modulating functions and exact state observers with its application for identification of a real continuous-time industrial process. The method enables transformation of a system of differential equations into an algebraic one with the same parameters. Then, these parameters can be estimated using the least-squares approach. The main problem is the nonlinearity of the MISO process and its noticeable transport delays. It requires specific modifications to be introduced into the basic identification algorithm. The main goal of the method is to obtain on-line a temporary linear model of the process around the selected operating point, because fast methods for tuning PID controller parameters for such a model are well known. Hence, a special adaptive identification approach with a moving window is proposed, which involves using on-line registered input and output process data. An optimal identification method for a MISO model assuming decomposition to many inner SISO systems is presented. Additionally, a special version of the modulating functions method, in which both model parameters and unknown delays are identified, is tested on real data sets collected from a glass melting installation.