A Universal Gains Selection Method for Speed Observers of Induction Machine

Properties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response of the observer. System identification using least-squares estimation is implemented to determine the dynamic properties of the observer based on the estimation error signal. The influence of sampling time as well as signal length on the system identification has been studied. The results of gains selection using the proposed method have been compared with results obtained using the approach based on the placement of the poles of linearized estimation error equations. The introduced method delivers results comparable with analytical methods and does not require prior preparation specific to the implemented speed observer, such as linearization.

Multi-Agent System Observer: Intelligent Support for Engaged E-Learning

Moodle is a widely deployed distance learning platform that provides numerous opportunities to enhance the learning process. Moodle’s importance in maintaining the continuity of education in states of emergency and other circumstances has been particularly demonstrated in the context of the COVID-19 virus’ rapid spread. However, there is a problem with personalizing the learning and monitoring of students’ work. There is room for upgrading the system by applying data mining and different machine-learning methods. The multi-agent Observer system proposed in our paper supports students engaged in learning by monitoring their work and making suggestions based on the prediction of their final course success, using indicators of engagement and machine-learning algorithms. A novelty is that Observer collects data independently of the Moodle database, autonomously creates a training set, and learns from gathered data. Since the data are anonymized, researchers and lecturers can freely use them for purposes broader than that specified for Observer. The paper shows how the methodology, technologies, and techniques used in Observer provide an autonomous system of personalized assistance for students within Moodle platforms.

Is an Earthquake Felt Inside a Car?

The analysis of how an earthquake is felt was addressed with the data provided by citizens through a website dedicated to the perception of earthquakes in Italy (Data and Resources). The analysis focused on the perception of earthquakes by observers inside both parked and moving cars. These situations were compared with outdoor ones. The felt percentage of each situation was quantified for epicentral distance ranges and European Macroseismic Scale (EMS) degree. One of the main findings was the greatest sensitivity to shaking for people inside parked cars due to resonance phenomena of the automobile–observer system. The distribution of the intensity of perception in the car was analyzed as a function of the hypocentral distance and the magnitude of the earthquake. It was possible to define the attenuation trends of these intensities. The comparison of these trends with those of the equations for estimation of response spectral ordinates allowed us to have an evaluation of the frequency values of the seismic waves that caused the vibrations felt, which were found to agree with the typical frequencies of the car–observer system, as highlighted by independent studies. The results of this analysis show the possibility to include the perception of the earthquake inside a parked and moving car among the diagnostics used in the definition of macroseismic intensity degree of the EMS.

Application of an Estimation Method in the Lure System

The presence of set-valued mapping affects the stability of the output of the lure system, adding to the difficulty in observer design. To overcome the difficulty, the author mapped the system output error to the nonlinear term of the framer, creating a framer of the extended Luenberger structure, and analyzed the coordination of the error system by the monotonic system theory. On this basis, the interval observer was designed for the lure system. Then, the lure system and its observer systems were proved as asymptotically stable. Finally, it is proved that the observer system trajectory always followed the original state trajectory through the simulation under the different selections of set-valued mapping.

Learning the Ashby Box: an experiment in second order cybernetic modeling

Purpose W. Ross Ashby’s elementary non-trivial machine, known in the cybernetic literature as the “Ashby Box,” has been described as the prototypical example of a black box system. As far as it can be ascertained from Ashby’s journal, the intended purpose of this device may have been to exemplify the environment where an “artificial brain” may operate. This paper describes the construction of an elementary observer/controller for the class of systems exemplified by the Ashby Box – variable structure black box systems with parallel input. Design/methodology/approach Starting from a formalization of the second-order assumptions implicit in the design of the Ashby Box, the observer/controller system is synthesized from the ground up, in a strictly system-theoretic setting, without recourse to disciplinary metaphors or current theories of learning and cognition, based mainly on guidance from Heinz von Foerster’s theory of self-organizing systems and W. Ross Ashby’s own insights into adaptive systems. Findings Achieving and maintaining control of the Ashby Box requires a non-trivial observer system able to use the results of its interactions with the non-trivial machine to autonomously construct, deconstruct and reconstruct its own function. The algorithm and the dynamical model of the Ashby Box observer developed in this paper define the basic specifications of a general purpose, unsupervised learning architecture able to accomplish this task. Originality/value The problem exemplified by the Ashby Box is fundamental and goes to the roots of cybernetic theory; second-order cybernetics offers an adequate foundation for the mathematical modeling of this problem.

Controller and Observer Techniques for Twin Rotor MIMO System

This paper elaborates the controller and observer system with all mathematical modeling of Twin Rotor MIMO System (TRMS) which is eminently nonlinear system. TRMS is 2 DOF (Degree of Freedom) helicopter model which originated in company called Feedback Instrument Limited for controlling and experimenting of different algorithms. Two DOFs i.e. Yaw and Pitch control need to control by using controller, that imply to track a desired path. Nowadays, the Unmanned Aerial Vehicles (UAV) has been tremendously useful for road traffic by video surveillance and supervisions for public purposes. Because of capacity to hover, helicopters can be used in any environmental conditions. Hence, Scope of TRMS studies has been increasing.