Eduard Petlenkov

Design and implementation of fractional-order PID controllers for a fluid tank system

In this paper, we investigate the practical problems of design and digital implementation of fractional-order PID controllers used for fluid level control in a system of coupled tanks. We present a method for obtaining the PIλDμ controller parameters and describe the steps necessary to obtain a digital implementation of the controller. A real laboratory plant is used for the experiments, and a hardware realization of the controller fit for use in embedded applications is proposed and studied. The majority of tasks is carried out by means of the FOMCON (“Fractional-order Modeling and Control”) toolbox running in the MATLAB computing environment.

Fractional-order controller design and digital implementation using FOMCON toolbox for MATLAB

In this paper, we present the suite of tools of the FOMCON (“Fractional-order Modeling and Control”) toolbox for MATLAB that are used to carry out fractional-order PID controller design and hardware realization. An overview of the toolbox, its structure and particular modules, is presented with appropriate comments. We use a laboratory object designed to conduct temperature control experiments to illustrate the methods employed in FOMCON to derive suitable parameters for the controller and arrive at a digital implementation thereof on an 8-bit AVR microprocessor. The laboratory object is working under a real-time simulation platform with Simulink, Real-Time Windows Target toolbox and necessary drivers as its software backbone. Experimental results are provided which support the effectiveness of the proposed software solution.

Incorporation of fractional-order dynamics into an existing PI/PID DC motor control loop.

The problem of changing the dynamics of an existing DC motor control system without the need of making internal changes is considered in the paper. In particular, this paper presents a method for incorporating fractional-order dynamics in an existing DC motor control system with internal PI or PID controller, through the addition of an external controller into the system and by tapping its original input and output signals. Experimental results based on the control of a real test plant from MATLAB/Simulink environment are presented, indicating the validity of the proposed approach.

Recognition of the Surgeon's Motions During Endoscopic Operation by Statistics Based Algorithm and Neural Networks Based ANARX Models

Abstract The problem of recognition and short time prediction of the surgeons hand motions during surgical endoscopic operation are approached in the present contribution using neural network based nonlinear modeling techniques and statistics based segmentation of the operating room. It is shown that proposed technique provide precise recognition of surgeons motions.

Neural Networks Based ANARX Structure for Identification and Model Based Control

This article is devoted to the training and application of neural networks based additive nonlinear autoregressive exogenous (NN-based ANARX) model. Training of NN-based ANARX model with MATLAB is discussed in detail and illustrated by examples. Dynamic state feedback linearization control algorithm is then applied for control of unknown nonlinear system

A novel taylor series based approach for control computation in NN-ANARX structure based control of nonlinear systems

This paper presents an alternative approach for control computation in a closed loop of discrete-time nonlinear system and NN-ANARX based dynamic output feedback. Proposed technique is based on an application of Taylor series expansion for computation of control directly from neural network based model. Two modifications of the algorithm are proposed for both single-input single-output and multi-input multi-output nonlinear systems. The effectiveness of the proposed approach is demonstrated on numerical examples.

Adaptive Output Feedback Linearization for a Class of NN-based ANARX Models

Present paper is devoted to the design of an adaptive output feedback controller for nonlinear system modelled by neural networks based Additive Nonlinear Autoregressive Exogenous structure. Off-line and on-line parameter identification of the neural networks based Additive Nonlinear Autoregressive Exogenous model using standard training algorithms are discussed in detail and illustrated by numerical simulations. The main contribution of this paper is in combining neural networks based adaptation with dynamic output feedback linearization technique.

State-space control of nonlinear systems identified by ANARX and Neural Network based SANARX models

A state-space technique for control of nonlinear SISO systems identified by an Additive Nonlinear Autoregressive eXogenous (ANARX) model is presented. Two cases are shown. In the first case system model is given explicitly in the form of ANARX structure. In the second case controlled system is identified by Neural Network based Simplified Additive NARX (NN-SANARX) model linearized by dynamic feedback. The neural network based model is represented in the discrete-time state-space form. The effectiveness of the approach proposed in the paper is demonstrated on numerical examples with SISO and MIMO systems.

Application of self organizing Kohonen map to detection of surgeon motions during endoscopic surgery

Segmentation of the surgeonpsilas hand movements during the surgery into more primitive parts and recognition of those parts using Kohonen map is discussed in present paper. Main advantages of the proposed approach are that it allows to take into account dynamical characteristics of the hand movements and exclude probability of human error in building etalon segmentation. Ability to recognize current action of the surgeon has a crucial importance in developing a robot able to assist surgeon during the endoscopic surgical operation. One of the possible ways is to predefine a set of possible surgeonpsilas actions and provide a recognition algorithm explored in the framework of present contribution.

Implementation and real-time simulation of a fractional-order controller using a MATLAB based prototyping platform

Design and implementation of fractional-order controllers are important problems in contemporary control design practice. In this paper, we discuss issues associated with hardware implementation and real-time simulation of a particular fractional-order controller. The simulation is performed in MATLAB, which is interfaced with the controller by means of a data acquisition board. We provide design steps necessary to obtain a digital implementation of a fractional-order lead-lag compensator as well as the description of the used controller and data acquisition board. An example, illustrating the use of the prototyping platform, is provided.