Helga Silaghi

Procedural and software development of a Liapunov-based stability analysis method for interpolative-type control systems

Non-linear control systems stability and as a particular case the stability of interpolative-type control structures (as fuzzy, neural or pure interpolative control systems) is an intensively studied problem, due to its multiple applicative valences. In the specialized literature there are some approaches regarding the fuzzy system stability [1]. Referring the control systems with interpolative controllers, there are just a few studies and the existing work is limited to the stability study of the interpolation method [3]. The present paper approaches a methodological procedure and the basic idea of a software tool for the stability analysis based on direct Liapunov method applied to control systems with fuzzy and interpolative controllers.

Control of flow rate with fuzzy logic for ball mill

This paper presents a ball mill model. Starting with this mathematic model it is possible to achieve simulation results based on Matlab Simulink scheme. In this study, a fuzzy controller was designed for control flow rate inside the mill to avoid overfilling or emptying the mill. Finally, some simulation results are shown.

Evaluation of hilbert space techniques and lagrange's method for the analysis of dissipated power in DC circuits

The basic circuit laws of DC circuits are interpreted in this paper by defining suitable functionals in terms of dissipated power. It is then shown that the minimum of dissipated power determined by taking the derivative of these functionals verifies the first Kirchhoffs law. This allows interpreting the circuit equations by using the second Kirchhoffs law and the minimum power principles. In order to estimate the extreme values of dissipated power for DC circuits with modifiable parameters, and the relation between the variation in one or all the resistances of the networks and the variation of dissipated power we use the Lagranges method. Numerical examples obtained with Mathematica are provided to show the practical applications and comparison between of two proposed principles of DC circuits.

Design framework for risk mitigation in industrial PLC control

Programmable logic controllers (PLCs) are increasingly used in industrial automation projects. By their nature, in these applications safety is a crucial requirement. However, risk prevention adds costs to the PLC system, which means that a balance between costs and risks have to be found. A convenient compromise between these two criteria is provided by risk mitigation, but only to an acceptable risk level. By reviewing the fundamental definitions and concepts of system safety, and with the support of a simple example, the paper provides a framework for addressing these issues. Exploring the systematic design of safety-critical PLC systems helps to show how design engineers can verify that their projects will be safe.

Approach of PID controller tuning for ball mill

The object of this paper is to investigate the dynamics of the closed loop of a cement mill and to introduce an approach for tunning robust PID controllers. Based on the analyze of the dynamic behavior of the cement mill, a robust PID controller is designed and then simulated. The simulation results confirm that the given approach provides high performances of the cement mill.

Dependability Analysis of PLC I/O Systems Used in Critical Industrial Applications

Programmable logic controllers (PLCs) are widely used in control applications. The growth of control requirements has created new challenges upon PLCs. Dependability attributes, like reliability and safety, became essential parameters in the PLC systems design. Since 90% of the PLC faults belong to its I/O modules, the dependability of the PLCs I/O modules represents a major issue.

DC electrical drive control with fuzzy systems

This paper presents a solution to the problem of principle DC electric drives powered by static converters, at low speed and load torques. Maintaining control performance for a broad range of speed variation involves adjustment of system parameters depending on operating conditions. It is designed an adaptive algorithm based on fuzzy logic to meet these challenges. Finally, some simulation results with adaptive fuzzy engine are presented.

Analysis of two-phase asynchronous motor with non-orthogonal windings in dynamic regime

This paper presents a dynamic regime analysis of the starting and function of the two-phase asynchronous motor with two non-orthogonal stator windings. Simulation results are obtained when the axis of the auxiliary winding is moved with 30 degrees in decreasing and increasing way. The answer concerning optimal choice of the two-phased motor for household applications is given by the results of the dynamic analysis.

Voice command of an industrial robot in a noisy environment

This paper presents a study of voice command in industrial automation. Some tests were conducted on the voice recognition in a noisy environment. Compared to the laboratory environment, the signal was affected by the noise from different sources, such as: electrical motors, machine tools, human operators. An example with noise produced by an induction machine is presented. Finally, some simulation results of voice recognition in a noisy environment are presented.

INTELLIGENT CONTROL OF ELECTRICAL DRIVE SYSTEM USED FOR ELECTRIC VEHICLES

Abstract An electric vehicle (EV) uses an electric motor for traction and chemical batteries, superconductors, combustion cells and / or inertial masses as energy sources. To avoid problems regarding the accuracy of the mathematical model of the system, the use of artificial intelligence in electric drives is a viable alternative. Among other advantages of using artificial intelligence in the electric drive system, it can be emphasized that its application reduces the design time and leads to avoiding problems with the introduction of the mathematical model in the system control algorithm. This paper presents several case studies of electrical vehicles and some considerations about intelligent control of EVs. Finally some experimental results that compare classical control system with fuzzy logic control system for EV are presented.