State-of-the-art in control engineering

AbstractThe paper deals with new trends in research, development and applications of advanced control methods and structures based on the principles of optimality, robustness and intelligence. Present trends in the complex process control design demand an increasing degree of integration of numerical mathematics, control engineering methods, new control structures based of distribution, embedded network control structure and new information and communication technologies. Furthermore, increasing problems with interactions, process non-linearities, operating constraints, time delays, uncertainties, and significant dead-times consequently lead to the necessity to develop more sophisticated control strategies. Advanced control methods and new distributed embedded control structures represent the most effective tools for realizing high performance of many technological processes. Main ideas covered in this paper are motivated namely by the development of new advanced control engineering methods (predictive, hybrid predictive, optimal, adaptive, robust, fuzzy logic, and neural network) and new possibilities of their SW and HW realizations and successful implementation in industry

Advanced Information System for Safety-Critical Processes

The paper deals with the design and implementation of an intelligent modular information system (IMIS) for modeling and predictive decision making supervisory control of some important critical processes in a nuclear power plant (nuclear reactor) using selected soft computing methods. The developed IMIS enables monitoring critical states, safety impact analysis and prediction of dangerous situations. It also recommends the operator possibilities how to proceed to ensure safety of operations and humans and environment. The proposed complex IMIS has been tested on real data from a nuclear power plant process primarily used as supervisory information for decision making support and management of critical processes. The core of the proposed IMIS is a general nonlinear neural network mathematical model. For prediction of selected process variables an artificial neural network of multilayer perceptron type (MLP) has been used. The effective Levenberg-Marquardt method was used to train the MLP network. Testing and verification of the neural prediction model were carried out on real operating data measurements obtained from the NPP Jaslovske Bohunice

New Software Tool for Modelling and Control of Discrete-Event and Hybrid Systems Using Petri Nets

The main aim of the proposed paper is to design a new software tool for modelling and control of discrete-event and hybrid systems using Arduino and similar microcontrollers. To accomplish these tasks a new tool called PN2ARDUINO based on Petri nets is proposed which is able to communicate with the microcontroller. Communication with the microcontroller is based on the modified Firmata protocol hence the control algorithm can be implemented on all microcontrollers that support this type of protocol. The developed software tool has been successfully verified in control of laboratory systems. It can also be used for education and research purposes as it offers a graphical environment for designing control algorithms for hybrid and mainly discrete-event systems. The proposed tool can improve education and practice in the field of cyber-physical systems (Industry 4.0)

Transition of cavitating flow to supercavitation within Venturi nozzle – hysteresis investigation

Cavitation is usually considered as undesirable phenomena. On the other hand, it can be utilized in many applications. One of the technical applications is using cavitation in water treatment, where hydrodynamic cavitation seems to be effective way how to reduce cyanobacteria within large bulks of water. The main scope of this paper is investigation of the cavitation within Venturi nozzle during the transition from fully developed cavitation to supercavitation regime and vice versa. Dynamics of cavitation was investigated using experimental data of pressure pulsations and analysis of high speed videos, where FFT of the pixel intensity and Proper Orthogonal Decomposition (POD) of the records were done to identify dominant frequencies connected with the presence of cavitation. The methodology of the high speed (HS) records semiautomated analysis using the FFT was described. Obtained results were correlated and above that the possible presence of hysteresis was discussed

FPGA as a tool for hardware realization of feedback control

The presented paper deals with the development of robust control algorithm based on reflection vectors methodology. This approach of controller design is guaranteeing stability, robustness and high performance. The presented method was successfully tested for stable, unstable and strong oscillating processes and for systems with parametrical model uncertainty. The proposed algorithm can be effectively realized using field-programmable gate array (FPGA) structure as it is shown in the case study – the hardware realization using FPGA technology for DC motor. All presented simulations and co-simulations were realized in MATLAB-Simulink

Self-tuning controllers based on orthonormal functions

summary:Problems of the system identification using orthonormal functions are discussed and algorithms of computing parameters of the discrete time state- space model of the plant based on the generalized orthonormal functions and the Laguerre functions are derived. The adaptive LQ regulator and the predictive controller based on the Laguerre function model are also presented. The stability and the robustness of the closed loop using the predictive controller are investigated