Gregor Dolanc

Identification of nonlinear systems using a piecewise-linear Hammerstein model

Abstract In the paper a method for nonlinear system identification is proposed. It is based on a piecewise-linear Hammerstein model, which is linear in the parameters. The model and the identification algorithm are adapted to allow the parameter identification in the presence of a special form of the excitation signal. The identification method is derived from a recursive least-squares algorithm, which is properly adapted to take into account the proposed model structure and the properties of the identification signal. The applicability of the approach is illustrated by an example in which a discontinuous nonlinear static function is connected to a dynamic block.

NOX selective catalytic reduction control based on simple models

Abstract In the paper, a new approach to the control of the selective catalytic reduction process of NO X is presented. The reduction process can be efficiently controlled using a combination of feed-forward and feed-back control structures. However, this approach requires expensive measurement equipment. It is shown that measurement of nitric oxide concentration at the input of the catalytic converter and measurement of the flue gas flow rate can be successfully substituted by corresponding “software sensors”. The software sensors are based on simple mathematical models and on measurements of excess oxygen concentration in flue gas and the fuel flow rate which are usually parts of already available standard combustion control system equipment. In the paper the complete derivation of the required mathematical models is given, and the proposed new control structure is described. The structure is tested using simulation and implemented on an industrial pilot plant.

Design of a nonlinear controller based on a piecewise-linear Hammerstein model

In the paper a new method for identification and control of nonlinear systems is presented. The method is based on a piecewise-linear Hammerstein model, which is linear in parameters, and enables approximation of systems with extremely nonlinear or even discontinuous static functions. The model can be obtained by making use of a specific identification method, which takes into account the proposed structure of the model, and the properties of the excitation signal. The derived model represents the starting point for development of a nonlinear controller, which is based on the pole-placement principles. The proposed method is illustrated by a simulation example representing identification and control of a nonlinear process with discontinuous static function.

Auto-tuning non-linear controller for industrial use

This paper presents an advanced control system named ASPECT for control of nonlinear or slowly time varying systems. The described control system was developed and implemented in programmable logic controller to meet industrial demands. The case study, which is control of gas-liquid separation unit, is intended to illustrate the operation and benefits of the controller.

Automatic guidance of an aircraft using predictive control in a visual servoing scheme

Abstract In this paper we have designed and implemented a predictive automatic flight controller for an airplane that takes as input the estimated pose obtained from the visual data and provides control outputs for an inner-loop augmented aircraft. In order to make the predictive controller suitable for flight control, it had to be modified. The most important modification was the introduction of the short term reference trajectories, linking the time-based and the position-based control strategy. Furthermore a controller switching mechanism was introduced to enable the aircraft to fly at different flight conditions. The parameters of the controller have been derived by experimental optimization. The tests have shown good overall tracking and disturbance rejection properties; the aircraft is able to perform various maneuvers and the touchdown in all the tested weather (wind, turbulence) conditions.

A Diesel-Powered Fuel Cell APU—Reliability Issues and Mitigation Approaches

The paper deals with reliability issues of a diesel-powered fuel cell auxiliary power unit (APU). The unit combines an autothermal diesel reformer and a proton exchange membrane fuel cell stack. The focal point is mitigation approaches for increasing the reliability of the complete APU system. These include control strategies on the one side, and electronic hardware solutions on the other. The measures, guarantying safe, reliable, and long-life operation, were developed, implemented and experimentally validated on a 3-kW net electric power APU system targeted for truck on-board applications.

A System for Model-Based Quality Assessment of Burn-Protective Garments

Fire protective garments are essential for a broad range of professionals, such as fire fighters, soldiers, and workers in process industries. An important step prior to the utilisation of a new garment is to assess its thermal protective characteristics by exposing it to real fire conditions. In this chapter we describe a professional system built around a mannequin equipped with a distributed array of thermocouples. After dressing the mannequin and exposing it to a flash fire the distribution of temperatures on the mannequin surface is recorded. From the temperature recording the heat flux that envelopes the mannequin surface is reconstructed first. To evaluate the possible reaction of skin subjected to the same flux, the skin heat transfer equation has to be solved next. The result of the experiment is a time distribution of injuries across the mannequin. In this chapter we extend the classic assessment procedure by questioning what the distribution of injuries would be if a broad range of individuals with different skin properties were subjected to the same flame conditions. A numerically efficient Monte Carlo simulation procedure which splits the overall computational load into off-line and on-line parts is proposed. The feasibility of the concept is demonstrated on an experimental run.

Design and Fabrication of a Complex LTCC-Based Reactor for the Production of Hydrogen for Portable PEM Fuel Cells

The development process for complex 3D ceramic structures in the integrated evaporator, mixer, reformer and combustor (EMRC) system for the production of hydrogen needed in portable polymer-electrolyte membrane (PEM) fuel cells is presented. Low-temperature co-fired ceramic (LTCC) technology was used to fabricate the ceramic structures of the system. The process started with the design and fabrication of each separate (stand-alone) component, which was developed and tested, and then optimized to fulfill the requirements for the integrated EMRC system. The final 3D ceramic structure consists of 45 LTCC tapes (Du Pont 951PX). The dimensions of the structure are 75 × 41 × 9 mm3 and the weight is about 73 g.

Identification and Control of Nonlinear Systems Using a Piecewise-Linear Hammerstein Model

This chapter introduces a new method for the identification and control of nonlinear systems, which is based on the derivation of a piecewise-linear Hammerstein model. The approach is motivated by several drawbacks accompanying identification and control via the classical type of Hammerstein models. The most notable drawbacks are the need for specific identification signals; the limited ability to approximate strongly nonlinear and discontinuous processes; high computational load during the operation of certain control algorithms, etc. These problems can be overcome by replacing the polynomial in the original model with a piecewise linear function. As a consequence, the resulting model opens up many new possibilities. In the chapter, first the new form, i.e., the piecewise-linear form of the Hammerstein model, is introduced. Based on this model, two new algorithms are derived and connected into a uniform design approach: first, a recursive identification algorithm, based on the well-known least-squares method, and second, a control algorithm that is a modification of the pole-placement method. Both algorithms are tested in an extensive simulation study and demonstrated on a case study involving control of a ferromagnetic material sintering process. Finally, some problems and limitations regarding the practical application of the proposed method are discussed.

On-line fuzzy identification for advanced intelligent controller

The paper presents the identification issues of the self-tuning nonlinear controller ASPECT* (advanced control algorithms for programmable logic controllers). The controller is implemented on a simple PLC platform with an extra mathematical coprocessor but is intended for the advanced control of complex processes. The model of the controlled plant is obtained by means of experimental modelling using an online learning procedure that combines model identification with pre-and post-identification steps that provide reliable operation. It is shown that acceptable performance of the system is obtained despite the difficult conditions it may encounter, such as nonlinearity of the plant, slowly varying parameters of the plant, high level noise etc.