The book covers the main topics from the wide area of wheeled mobile robotics, explaining all applied theory and application. The book gives the reader a good foundation, enabling them to continue to more advanced topics. Several examples are included for better understanding, many of them accompanied by short MATLAB script code making it easy to reuse in practical work. The book includes several examples of discussed methods and projects for wheeled mobile robots and some advanced methods for their control and localization. It is an ideal resource for those seeking an understanding of robotics, mechanics, and control, and for engineers and researchers in industrial and other specialized research institutions in the field of wheeled mobile robotics. Beginners with basic math knowledge will benefit from the examples, and engineers with an understanding of basic system theory and control will find it easy to follow the more demanding fundamental parts and advanced methods explained.
COBISS.SI-ID: 11671636
This paper presents the design and implementation of a unique control system for a smart hoist, a therapeutic device that is used in rehabilitation of walking. The control system features a unique human–machine interface that allows the human to intuitively control the system just by moving or rotating its body. The paper contains an overview of the complete system, including the design and implementation of custom sensors, dc servo motor controllers, communication interfaces and embedded-system based central control system. The prototype of the complete system was tested by conducting a 6-runs experiment on 11 subjects and results are showing that the proposed control system interface is indeed intuitive and simple to adopt by the user.
COBISS.SI-ID: 11361364
Gradual drifts in data streams are usually hard to detect and often do not necessarily trigger the evolution of new fuzzy rules during model adaptation steps in order to represent the new, drifted data distribution(s) appropriately in the fuzzy model. Over time, they thus lead to oversized rules with untypically large local errors (typically also worsening the global model error), as representing joint local data distributions before and after a drift happened likewise. We therefore propose an incremental rule splitting concept for generalized fuzzy rules in order to autonomously compensate these negative effects of gradual drifts. Our splitting condition is based 1.) on the local error of rules measured in terms of a weighted contribution to the whole model error and 2.) on the size of the rules measured in terms of the volume of the associated clusters. The splitting technique relies on the eigen-decomposition of the rule covariance matrix to adequately manipulate the largest eigenvector and eigenvalues in order to retrieve the new centers and contours of the two split rules. The splitting concepts are integrated in the generalized smart evolving learning engine for fuzzy systems (termed as Gen-Smart-EFS) and successfully tested on two real-world application scenarios. Results show clearly improved error trend lines over time when splitting is applied, compared to the case when it is not applied: reduction of the mean absolute model error by about one third (rolling mills) and about one half (engine test benches).
COBISS.SI-ID: 11812180
In this paper, continuous tracking-error model-based predictive control is presented. The controller’s optimal actions are obtained from an explicit solution of the optimization criteria, which enables fast real-time applications. Due to its design in continuous time, its usage is not limited to the uniform sampling restrictions of a host computer, as is usually the case in discrete time design. Therefore, better performance is obtained in applications with non-uniform sampling, which is natural in many situations due to imperfect sensors, mismatched clocks, nondeterministic control delays or because of the unknown time of the pre-processing. The controller-design parameters are insensitive to the sampling time period, which contributes to simpler applications and grater robustness of the controller.
COBISS.SI-ID: 11592276
Original research paper in the SCI journal, describing the upgrades and enhancements of the existent mathematical models of the electric arc furnace (EAF) processes, i.e. thermal, chemical and mass-transfer. The model is developed according to fundamental physical laws and is validated on operational measurements of the EAF. The model is intended to be used in simulation studies, for control design purposes and for optimization of the steel-melting process.
COBISS.SI-ID: 11444820