Petr Horáček

Laboratory experiments for control theory courses: A survey

Abstract The paper summarizes current trends in building of a Control Laboratory supporting Control Engineering and Control Theory courses. The emphasis is put on the laboratory equipment, the scale models, and the software environment used for supporting the theoretical content of lectures and running the experiments in real-time. Classes of laboratory models are introduced considering the model complexity and common characteristics of a large variety of models developed over decades. Software tools supporting control experiments in real-time are summarized. The goal of the paper is to help those who intend to build a new control laboratory with practical experiments. Using experience of others saves time and money.

Optimal Planning of Ancillary Services for Reliable Power Balance Control

This paper presents an overview of a complex approach to optimal planning of ancillary services ensuring reliable power balancing of a transmission system in liberalized market conditions that is performed by a transmission system operator (TSO). To accomplish this goal analytical computations together with optimizations and Monte Carlo simulations are performed. The designed decision support tool serves the TSO not only for a year-ahead planning task but also for carrying out various analyses and sensitivity tests, e.g., how costs of ancillary services are related to the level of reliability. Attention is also paid to mutual substitutability of ancillary services and its impact on transmission system operation and corresponding expenses.

Laboratory Evaluation of Fuzzy Controllers

Abstract The paper discuss various possibilities of applying fuzzy set theory in Real-Time control. Three types of controllers are used for comparing their behaviour in control experiments on scale laboratory model of a real dynamic system. The objective of the first experiment is to compare the performance of a fuzzy logic, a PID and an LQ controller in terms of stability, response time and steady-state error in various control tasks. The second experiment evaluates fuzzy logic adaptation of a PID controller, utilizing some heuristic knowledge.

Hierarchical fuzzy controllers

Abstract The paper presents Fuzzy Logic Controllers (FLC) with hierarchically structured rule base as nonlinear blocks used in a control system for direct control or supervision of standard controllers. Unified approach based on Fuzzy Logic Neural Networks (FLNN) is used to reveal the essential functions of a FLC. The FLNN is then extended to the case where decomposition of a rule base leads to simplification of controller design and tuning. Two structures of hierarchically organized groups of rules are discussed. Singlestage decision making structure with groups of rules organized hierarchically according to their specificity and a multi-stage decision making architecture with chained rules. Data induced error backpropagation technique for fine tuning of parameters of the second structure is derived.

Criteria for evaluation of power balance control performance in UCTE transmission grid

In this paper two criteria for evaluation of power balance control performance in control areas of the UCTE interconnection are proposed: the mean value of Area Control Error (ACE) and the standard deviation of ACE. A methodology for assigning fair values of the two criteria to individual control areas is presented. This methodology ensures that the UCTE grid is operated in a safe manner and no area performs control at the expense of other areas. Since the fair values of the ACE standard deviation depend on a chosen model of ACEs coincidence, two cases were investigated: a model with no coincidence (optimistic one) and a model with full coincidence (pessimistic one).

Fuzzy Supervisory Control

Abstract Multimodel control methodology can be a good alternative in control of complex nonlinear systems. In this case, the selection of good controllers and the bump less transfer between different controllers are important. This paper presents a supervisory control based on the Takagi-Sugeno fuzzy model used as a two level controller. A learning phase is added to change the T-S fuzzy model parameters, shapes of membership functions of reference fuzzy sets, to achieve a better performance of the control system.

Disassembling Process Modelling and Operations Planning Under Imprecise Operation Time

Abstract The semi-automated disassembly of manufactured goods is a recycling procedure that is well suited for current economical and ecological conditions, if products are considered in their complete life-cycle. The present study limits itself to the description and modelling of a disassembly process, in order to determine a schedule of disassembling activities. The processing time of the automatic or manual disassembling activities is expressed by fuzzy sets, reflecting imprecision in activity duration due to incomplete knowledge about the state of the object to be disassembled. The study is managed within the context of a Man-Machine system that will evolve throughout the disassembling process.

Securing Electrical Power System Operation

Automation in power systems has a very long tradition. Just recall the flyball governor in a steam engine and it becomes clear that power people have been using control principles and instruments for more than a century. There are, however, new challenges in power generation and transmission concerning the security and efficiency of those services that require the attentions of both theoreticians and practitioners. These challenges are the subject of this chapter. The power failures that affect large grids from time to time show that system collapses are not simply a subject of academic debate. Power network operating reliability has become an issue that any country must make a top priority. The reliability of a power system depends for the most part on the quality of the decisions made, both automatically and manually. The term power system is very broad, and we focus here on the power system backbone, electric power transmission, and its operational reliability, particularly when automatic control plays a vital role. The content of the chapter remains interdisciplinary, spanning power systems, automation and economy, as changes resulting from the opening of the markets and permanent power system restructuring affect its operation.

Optimal planning strategy of ancillary services ensuring secure operation of power system

This paper presents an overview of a complex approach to optimal planning of ancillary services ensuring reliable power grid balancing in liberalized market conditions that is performed by the transmission system operator. To accomplish this goal analytical computations together with optimizations and Monte-Carlo simulations are used. Attention is also paid to mutual substitutability of ancillary services and its impact on the grid operation and related expenses.

Fuzzy Modeling and Control

The paper presents fuzzy modelling as a tool for design of nonlinear controllers. An architecture and function of a fuzzy logic controller (FLC) is described. Three implementations of FLCs are recognized: look-up table, fuzzy relational and fuzzy logic-neural network based systems. Fuzzy logic — neural networks (FLNN) are analyzed in greater details. Architectures suitable for a FLNN identification for plant and operator modelling are discussed, passive and active regimes for tuning of controller parameters are explained. Unsupervised and supervised identification techniques are described. Principles of direct inverse, model reference, internal model and optimal predictive fuzzy control are explained. Finally, commercial software and hardware tools for design, implementation and evaluation of fuzzy controllers are summarized.