Sanda Dale

Interpolative-Type Control Solutions

The controllers with interpolative blocks can replace fuzzy controllers in control structures. This is possible because fuzzy controllers belong also to the interpolative-type controller category, meaning controllers which implements interpolative-type reasoning. That kind of replacement is not only a formal operation; it is also associated with further corrections that confer to the structures with interpolative controllers enough flexibility to obtain better performances. The possibility of performances improvement on a flexible structure is the main argument of the present paper. Another argument is the reduced calculus time, suited for the real-time implementation - it’s about “look-up table” type solutions and the possibility to obtain simple controllers with robustness properties. In order to illustrate the above affirmations, two case studies are developed in the paper: an electromechanical ball and beam nonlinear system and a positioning system with Lyapunov constraints and state limitations.

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.

Interpolative control algorithm applied on a 3D-mechatronic system

The study presented in the paper aims to investigate the control performances of an interpolative control algorithm applied on a complex nonlinear system. In the specified context, the study was made based on results obtained through simulations on a 3D-Crane. The results were compared with data obtained from a classical PID system that also incorporates the 3D-Crane.

Dead time compensation for interpolative-type, control systems

Signal transmission in control structures is usually characterized by propagation processes, i.e. existence of time delays. For the interpolative-type control structures the problem is often disregarded, especially in the design step. Undoubtedly, the effect consists in worse real performances that those designed. In this context, the present paper proposes and presents a solution able to compensate, via a discrete-time PD compensator, the effect of the dead times appeared on the feedback channels for both a fuzzy and an interpolative control structure. For systems with variable time delays an adaptive-interpolative type PD compensator is suited. Experimental results, obtained through simulation on a second order positioning system, validate the proposed solution. Finally, the paper discusses the issue of the accuracy of simulation. It is emphasized the manner in which the simulation can be done using initial segment generators for the elementary dead time transfer elements.

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.

Redundancy method used in PLC related applications

PLC related applications are more complex as far as more components are involved. If some error occurs, diagnosis can take some time, but a logical procedure will shorten the time needed to locate the fault. The probability of failure of different parts of typical PLC systems shows [1] that 95% of PLC systems are external faults and occur on plant items such as: sensors, actuators, transducers, limit switchers, and others. The possibility of determining the validity of the data gathered from all transducers of the control system assures a way of short time fault detection. Consequently, a fault-tolerant control system must be implemented using redundant structures, representing an alternative for malfunctioning element detection. This paper presents a method used to design and implement a control system based on redundant structures. A case study for the geothermal power plant at the University of Oradea was developed. The redundant structure considered was simulated using MathLab/Simulink and analyzed using different scenarios. Finally, a possible implementation of resulting control system structure is done using a programmable logical controller (PLC).

MATLAB-SIMULINK modeling for the Well Station of a Geothermal power Plant

In this paper, a MATLAB-SIMULINK-based model for the Well Station from the Geothermal Plant at the University of Oradea is developed. The Well Station component is in charge for producing (extracting) geothermal water that should be used for heating purposes in the university campus.

Numerical algorithms for Lyapunov stability analysis of interpolative control structures

The complexity and specificity of stability analysis applied to interpolative-type control structures makes the study of such property a difficult, almost impossible task - at least in the analytical manner. Therefore, a better solution could be represented by the numerical approach. In this context, this paper starts with developing some methods and techniques with applicability for analysis of the interpolative-type controllers, based on Lyapunov method perspective. These methodological aspects are gathered together into a specific procedural algorithm. Based on this algorithm, a set of MATLAB-SIMULINK programs able to offer, in a flexible and user-interactive way, a possible solution to Lyapunov-stability analysis for a class of interpolative-type control systems with linear or non-linear processes of 2nd and 3rd order are developed. The solution based on the implemented software packages was finally validated through some practical examples.

A simple method to develop interpolative controllers with robustness properties at step reference changes

The paper treats the problem of implementing a control structure with interpolative blocks, minimal from the structural point of view but in the mean time with robustness properties and capable to ensure adequate performances. To accomplish these statements a control structure with interpolative rule based controller is used. The controller has as input a synthetic measure of the command related to the phase-plane variables. The final interpolative solution is a flexible, easy to improve structure, with reduced calculus time, transparent during the design procedure, robust and without loss in performances. All the methodology is presented through a study case.

Fuzzy model based predictive control of nonlinear processes

A method of designing a nonlinear predictive controller based on relational fuzzy model is presented. The fuzzy model is incorporated as a predictor in a nonlinear model - based predictive controller, using internal model control scheme to compensate disturbances and modeling errors. A non-convex optimization problem must be solved at each sampling period. The algorithm is applied to temperature control in a heat exchanger.