Design Of Integrated Control System Research Articles

Modelica Predictive Control – An MPC Library for ModelicaEine MPC-Bibliothek für Modelica

Abstract Modelica is a powerful and flexible instrument for component-wise dynamic system modeling. Unfortunately, until now it does not provide many structures to integrate advanced control methods. This article presents a Modelica library for model-based predictive controllers with linear process models, which offers the use of several model representations in the controller for predicting the future plant outputs. As well, the controller is capable of constraints and disturbance handling. A controller block can be included easily into any Modelica model and is parameterized intuitively. The library avoids the coupling of Modelica to other software products.Thus, a contribution is made towards an integrated control system design in Modelica.

General Purpose Control System for Steel Making Process Control Using VME Bus Based System and OS-9 WINDOWS

In this paper, a general purpose control system was constructed to provide accumulation of the technology in integrated control system design under open architecture environment. The VMEbus system with OS-9 was chosen to simulate a process control system due to the popularity in open market. Interactive screen graphics including system function diagrams, menus, controlled system status and update infonnation are standard in this model. The simulation program was ported on a 32bit MVME147S-1 system and successfully tested.

Introduction to networking for integrated control systems

Integrated control system design, which requires interactions between the disciplines of communication systems and control systems, is introduced. An integrated control system has disparate and spatially distributed subsystems interconnected via a common communication channel. Digital data from sensor to controller and from controller to actuator are multiplexed along with traffic from other control loops and management functions. The asynchronous time-division multiplexing introduces time-varying and possibly stochastic delays in the control loops, degrading system dynamic performance. The analysis of delayed control systems is treated, covering the stochastic Lyapunov method approach, the D-partition method, and the method of steps. >