Zdzisław Kowalczuk

Model based diagnosis for automotive engines-algorithm development and testing on a production vehicle

A complete diagnostic algorithm is presented for detecting and isolating faults of actuators and sensors of an automotive engine. The algorithm is built around the concept of analytical redundancy and utilizes structured parity equations. The parity equations rely on a nonlinear and dynamic model, obtained by identification using data from a single production vehicle with a 3.1 l V-6 engine. Tests performed with the diagnostic algorithm on the same vehicle show excellent performance under different fault conditions. Several important issues require further investigation, including long-term climatic effects, vehicle aging, car-to-car variations, the automation of the calibration procedure and implementation in the face of processor limitations. >

Autonomous Driver Based on an Intelligent System of Decision-Making

AbstractnThe paper presents and discusses a system (xDriver) which uses an Intelligent System of Decision-making (ISD) for the task of car driving. The principal subject is the implementation, simulation and testing of the ISD system described earlier in our publications (Kowalczuk and Czubenko in artificial intelligence and soft computing lecture notes in computer science, lecture notes in artificial intelligence, Springer, Berlin, 2010, 2010, In Int J Appl Math Comput Sci 21(4):621–635, 2011, In Pomiary Autom Robot 2(17):60–5, 2013) for the task of autonomous driving. The design of the whole ISD system is a result of a thorough modelling of human psychology based on an extensive literature study. Concepts somehow similar to the ISD system can be found in the literature (Muhlestein in Cognit Comput 5(1):99–105, 2012; Wiggins in Cognit Comput 4(3):306–319, 2012), but there are no reports of a system which would model the human psychology for the purpose of autonomously driving a car. The paper describes assumptions for simulation, the set of needs and reactions (characterizing the ISD system), the road model and the vehicle model, as well as presents some results of simulation. It proves that the xDriver system may behave on the road as a very inexperienced driver.

Intelligent decision-making system for autonomous robots

Intelligent decision-making system for autonomous robots The paper gives an account of research results concerning a project on creating a fully autonomous robotic decision-making system, able to interact with its environment and based on a mathematical model of human cognitive-behavioural psychology, with some key elements of personality psychology included. The principal idea of the paper is focused on the concept of needs, with a certain instrumental role of emotions.

Model of human psychology for controlling autonomous robots

This paper presents a mind model for controlling autonomous robot systems, based on human psychology. A cognitive system and a motivational system (emotions and needs) constitute its main parts. The motivational system controls the reactions of a robot with the use of changeable states of needs. Emotions control the behavior of the robot by modulating certain parameters of needs. The cognitive system controls both the memory of the robot and its data processing.

Computational Approaches to Modeling Artificial Emotion – An Overview of the Proposed Solutions

Cybernetic approach to modeling artificial emotion through the use of different theories of psychology is considered in this paper, presenting a review of twelve proposed solutions: ActAffAct, FLAME, EMA, ParleE, FearNot!, FAtiMA, WASABI, Cathexis, KARO, MAMID, FCM, and xEmotion. The main motivation for this study is founded on the hypothesis that emotions can play a definite utility role of scheduling variables in the construction of intelligent autonomous systems, agents and mobile robots. In this review we also include an innovative and panoptical, comprehensive system, referred to as the Intelligent System of Decision-making (ISD), which has been employed in practical applications of various autonomous units, and which applies as its part the xEmotion, taking into consideration the personal aspects of emotions, affects (short term emotions) and mood (principally, long term emotions).

Optimal asynchronous estimation of 2D Gaussian–Markov processes

In this article, we consider the problem of trajectory estimation of a continuous-time two-dimensional (2D) Gaussian–Markov processes based on noisy measurements executed in non-uniformly distributed time moments. In such a case, a discrete-time prediction has to be performed in each cycle of estimation (by means of a Kalman filter). This task can, however, be computationally expensive. To solve this problem, we derive explicit formulae for predicting the 2D process based on explicit forms of the matrix exponential. The effects of the resulting estimator are confronted with those of the classical Kalman filter. Simulated experiments illustrate the effectiveness of the proposed approach.

Knowledge management based on dynamic and self-adjusting fuzzy models

The objective of this paper is to present a knowledge management based on dynamic and self-adjusting fuzzy models. Specifically, the proposed approach is founded on a knowledge-based methodology and theories of dynamic systems and fuzzy sets. A preliminary design of our fuzzy model takes advantage of the experience from managing of IT projects. Relevant experimental data resulting from these projects are utilized for adjusting the membership functions of the fuzzy model applied in the knowledge-based decision-support system.

Advanced Modeling of Management Processes in Information Technology

This book deals with the issues of modelling management processes of information technology and IT projects while its core is the model of information technology management and its component models (contextual, local) describing initial processing and the maturity capsule as well as a decision-making system represented by a multi-level sequential model of IT technology selection, which acquires a fuzzy rule-based implementation in this work.In terms of applicability, this work may also be useful for diagnosing applicability of IT standards in evaluation of IT organizations. The results of this diagnosis might prove valid for those preparing new standards so that apart from their own visions they could, to an even greater extent, take into account the capabilities and needs of the leaders of project and manufacturing teams.The book is intended for IT professionals using the ITIL, COBIT and TOGAF standards in their work. Students of computer science and management who are interested in the issue of IT project and technology management are also likely to benefit from this study. For young students of IT, it can serve as a source of knowledge in the field of information technology evaluation. This book is also designed for specialists in modelling socio-technical systems.

Soft- and Hard-Decision Multiple-Model Estimators for Air Traffic Control

The problem of tracking civil maneuvering aircrafts in the provision of air traffic control (ATC) systems by means of multiple-model (MM) estimation is considered. By constructing an appropriate set of models of maneuvers it is possible to describe how different maneuvers influence the state estimation process performed by a Kalman filter (KF) based on a nonmaneuver model of motion. This methodology leads to a diagnostic subsystem, which supports an adaptive switched MM (SMM) state estimator of a hard-decision type, based on KFs designed to fit certain parts of the objects trajectory. With an equivalent set of dynamic models an alternative soft-decision approach uses an interacting MM (IMM) filter scheme. Both the SMM and IMM filters are evaluated by simulations based on the recommendations of EUROCONTROL.

KNOWLEDGE MANAGEMENT BASED ON FORMAL MODELS OF SOFTWARE PROJECT MANAGEMENT

The objective of this paper is to present a complete conception of decision support systems for software project management. The idea is founded on dynamic and self-adjusting fuzzy models. Specifically, the propsed approach is founded on the knowledge-based methodology and the theories of dynamic systems and fuzzy sets. The presented method can be used in manufacturing of knowledge-based Information Technology (IT) products. A preliminary design of a fuzzy model can take advantage of experience from managing projects. Relevant experimental data resulting from such projects can then be utilized for adjusting the membership functions of the fuzzy model applied in the knowledge-based decistion-support system.