Jaroslav Hlava

Advanced Modelling and Control using a Laboratory Plant with Hybrid Processes

Abstract Advanced control theory is usually associated with the use of abstract mathematical tools. It requires much time and a good theoretical background to understand and explain these tools. In ordinary university courses or in continuing professional education organized by employers, it is not easy to meet these requirements. Widely used system simulation and virtual experiments can be a good aid to increase clarity, but they cannot fully demonstrate the problems that a control designer or user may encounter in practical implementation. A laboratory scale plant has been designed for this purpose in the framework of research activities focused on hybrid systems. It exhibits most of the hybrid phenomena typical of process control applications. The plant is also equipped with industrial control hardware, so that educational (as well as research) experiments can be carried out implementing advanced hybrid control algorithms in conditions close to real world applications. The instrumentation provides a remote web access facility. A mathematical and technical description of the pilot plant is included here, and this will enable readers to consider whether a similar device could be useful for their own educational and/or research purposes. Some examples of experimental results are also given.

A LABORATORY SCALE PLANT WITH HYBRID DYNAMICS AND REMOTE ACCESS VIA INTERNET FOR CONTROL ENGINEERING EDUCATION

Abstract The major challenge in modern control engineering education is to bring the increasingly sophisticated theory closer to those students who will follow industrial careers. Hybrid system theory addresses practical needs, but its potential is usually not understood by people from industry. Presented laboratory scale plant designed for original educational experiments with hybrid systems is a contribution to introducing this theory at a practical level. The paper includes a description of the plant structure, an outline of the mathematical model and suggested control experiments. The proposed internet access solves the lack of such laboratory set-ups. Web services architecture provides a standards-based access to all who want to learn about the principles of hybrid systems through remote experiments.

Modeling and predictive control of a nonlinear power plant reheater with switched dynamics

This paper is focused on modeling and predictive control of a power plant reheater. The motivation for this research is the necessity to achieve tighter power plant control in the wide range load following operation. The reheater under consideration consists of a series of three heat exchangers and two of them can be fully or partially bypassed. Accurate first principles model of the reheater is developed in the first part of the paper. Good approximation of the distributed parameter behavior is obtained by dividing the dynamics of the individual heat exchangers into several control volumes. Resulting high order model is considerably nonlinear. Moreover, switching of its dynamic behavior occurs because of the bypassing of the individual reheat stages. Thus, this reheater represents a non-trivial control challenge. Model predictive controller is designed in the second part. It is based on a piecewise affine model. Piecewise affine model is used both to approximate reheater nonlinearity and to describe the switches of reheater dynamics. The performance of the predictive controller is compared with the classical control system. Considerable performance improvement can be observed.

Model predictive control of power plant superheater — Comparison of multi model and nonlinear approaches

Model predictive control of a three stage power plant superheater is investigated in this paper. This power plant subsystem consists of three heat exchangers and three attemperator sprays. Its dynamics is nonlinear and significantly load dependent. In the paper, the responses to large load demand changes (between 50 and 100% of boiler rated power) typical of todays deregulated market conditions are considered. The ability of the predictive control system based on switched linear models and full nonlinear model to keep the steam temperature constant during such large transients is evaluated and the relative merits of the nonlinear vs. multi model approach are compared.

Hybrid modelling and control of a power plant three-stage reheater

Abstract The problem of modeling and control of a three-stage steam reheating process in a steam power plant is considered in this paper. Mathematical model of this process is marked by considerable nonlinearity. Moreover, switching of dynamic behavior occurs because individual reheat stages are bypassed depending on the value of manipulated variable. For both of these reasons, there is a little chance that replacing the traditional control system based on cascade PID/PI loops with advanced control methods such as MPC based on single linearized model may bring any performance improvement. However, both of these features make the steam reheating process a suitable object of modeling with a hybrid model in the form of a switched piecewise affine (PWA) system. Hybrid MPC based on this model then becomes a promising candidate approach to control. This paper describes the results of PWA modeling of the steam reheating process. A good agreement of responses between PWA model and nonlinear first principles model is shown. Following the development of this model, the design of a hybrid MPC controller is outlined.

Aggregated control of electrical heaters for ancillary services provision

Aggregated control of large groups of electrical space heaters becomes possible under emerging smart communication and metering infrastructure. This paper explores the possibility of using coordinated control of such groups as a part of the virtual power plant portfolio for the purpose of ancillary services provision. The main focus is on secondary control service. Several control strategies are considered for the coordinating controller. It is shown that aggregate response of large groups of heaters can meet the requirements on secondary control under different control strategies. On the other hand the peculiar dynamics of aggregate response of a large group of thermostatically controlled electrical space heaters with its oscillatory character, direct feed-through and hysteretic nature of individual thermostats presents a challenge even for advanced control approaches like MPC. For this reason, there is a still long way to go before a fully implementable coordinating controller that has a real chance of being applied in practice is designed.

Application of PID controller based on the localization method for ancillary service provision

The work deals with usage of classical PID controller to maintain balance between electricity consumption and production using concepts of smart grid and virtual power plant. Aggregated control of large groups of thermostatically controlled loads can be used for ancillary services provision. The focus is on secondary control and peak-shaving, which are a part of the power balance problem. Calculation of PID controller parameters are based on the localization method. The main idea of the localization method is using a derivatives vector of the controlled variable for manipulated variable calculation. The highest derivative implicitly contains full information about plants state at the current moment. The dynamics of individual building with heaters is described by second order equivalent thermal parameters (ETP) model. The obtained results show that aggregate response of large population of electrical space heaters can meet the requirements on both of the problems. Nevertheless, there are still a lot of issues remaining open: influence of the hysteresis parameter, and using suitable sampling time in order to lower demand on the communication infrastructure.

Evaluation of a simplified multi model predictive controller for a three stage power plant superheater based on projection of controller output onto the admissible set

Research focused on model predictive control (MPC) with low computational demands and good real time predictability usually exploits the properties of the explicit model predictive control. However, if the control problem is complex and the number of constraints and free control moves is high, explicit MPC can be even worse in the terms of computation time and real time predictability than standard MPC using on-line optimization. The purpose of this paper is to evaluate the application potential of a different approach to MPC with low computational demands: constraining the controller output by projection. This method was proposed by Tatjewski several years ago. However, it has found relatively little application. In this paper this method is extended to the case of switched multi linear MPC and evaluated using a case study of MPC control of a three stage power plant superheater. It is shown that even in the case of this relatively complex controlled plant, this simple method is able to achieve fairly good results. That is why it can be considered a suitable candidate approach for designing MPC controllers with low computational demands in applications with constraints on process control inputs and their rates of change.

Time delay systems applications in textile industry - Modelling of sliver drafting process

Abstract The paper deals with the textile sliver drafting process. It is shown that this process can be modelled as a non-linear time delay system with distributed delays. This model is linearized and distributed delays are converted into equivalent lumped delay system. An easy to apply method of distributed delay to lumped delay reduction is outlined as a by-product of this procedure. The main result of the paper is a model of important textile engineering process with time delays that has never been described in control engineering literature and that can be used as a basis for controller design. Thus, the paper opens a way of time delay systems theory applications to the field of textile engineering.

Multiple model predictive control of grid connected solid oxide fuel cell for extending cell life time

Solid oxide fuel cells (SOFC) can be used for both distributed electricity generation and cogeneration purposes. They have higher efficiency and certain other advantages over proton exchange membrane fuel cells. However an important weak point of SOFC cells is their lifetime and durability. In particular, high temperature and fuel utilization variations resulting from load changes contribute to stack damage and significantly decrease the cell lifetime. In this paper, a model predictive control scheme for extending the cell lifetime is proposed. It makes use of the ability of predictive control to respect range and rate constraints. SOFC stack damage is prevented by satisfying temperature, fuel utilization and air utilization operational constraints. The cell behavior is significantly nonlinear. However as nonlinear MPC still has many issues, the nonlinearity was accounted for by using MPC scheme based on multiple linear models. The control scheme considers grid connected fuel cell and the main control objective is to deliver the desired power while respecting all constraints related to cell lifetime. Simulation results show that proposed life extending controller is able to control SOFC in a wide operational range and it gives good tradeoff between the cell life time and control system performance.