Supervisor Control for a Stand–Alone Hybrid Generation System Using Fuel Cell and Photovoltaic Energy

This paper discusses a comprehensive supervisor control for a hybrid system that comprises the photovoltaic generation , hydrogen system ( Fuel cell ,Electrolyse ) and an ac load is developed in this paper. The objectives of the supervisor control are, primarily, to satisfy the load power demand and, second, allows to store the gas through the electrolyser. For these purposes, the supervisor controller determines the operation mode online of the solar generation subsystem , switching from power regulation to maximum power conversion . Decision criteria for the supervisor based on measurable system variables are presented (voltages, and currents) . Finally, the performance of the supervisor controller is extensively assessed through computer simulation using a comprehensive nonlinear model .

Behaviour equivalent max-plus automata for timed petri nets under open-loop race-policy semantics

Timed Petri nets and max-plus automata are well known modelling frameworks for timed discrete-event systems. In this paper we present an iterative procedure that constructs a max-plus automaton from a timed Petri net while retaining the timed behaviour. Regarding the Petri net, we essentially impose three assumptions: (a) the Petri net must be bounded, i.e, the reachability graph must be finite; (b) we interpret the Petri net with single server semantics; and (c) the Petri net operates according to the race policy, i.e., the earliest possible transition will fire and thereby possibly consume tokens required by other competing transitions. Under these assumptions we show that the proposed procedure terminates with a finite deterministic max-plus automaton that realises the same timed behaviour as the Petri net. As a variation of the plain race policy, we also consider that a subsequently designed supervisor may temporarily disable distinguished transitions. Again, we present a terminating procedure that constructs a behaviour equivalent deterministic max-plus automaton. We demonstrate by example how the latter automaton can be utilised as an open-loop model in the context of supervisor control.

Control of a stand-alone photovoltaic/battery bank system to supply energy to resistance load

<p><span lang="EN-US">In this paper, supervisor control for stand-alone hybrid power system to supply energy to resistance load is presented. The hybrid system is used to produce energy withoutinterruption and it consists of a photovoltaic generator (PV), and a battery bank. PV system work in parallel via DC/DC converter and the battery bank is used to store the excess of energy. The mathematical model topology, the identification of each subsystem and the control supervision of theglobal system are the contribution of this paper. Obtained results under Matlab/Simulink presented and discussed.</span></p>

Research and Development of Drone and Roadmap to Evolution

The history of drone dates far back. Human in those days must have had a yearn for the sky. This article first gives an overview of the history of research and development of drone including fixed wing and rotary wing, followed by, in particular, the history of development of rotary wing drone with the following four periods: before 1990 when radio control is at its dawn period; 1990 to 2010 when drone is at its dawn period; 2010 to 2015 when hobby-use drone is at its spread period; and 2016 and after when industrial-use drone is at its dawn period to growth period. In addition, this article presents the Japanese government’s roadmap, followed by a five-stage class of drone in terms of flight level and autonomy. In particular, autonomy will be discussed from the points of view of guidance, navigation, and control. Then with reference to an ideal state of drone in future, the article will discuss importance of the guidance system by fault tolerant control and supervisor control with implementation of the AI technology and the like.

Mobile robot control based on noninvasive brain-computer interface using hierarchical classifier of imagined motor commands

The study describes approaches of direct and supervisor control of a mobile robot based on a non-invasive brain-computer interface. An interface performs electroencephalographic signal decoding, which includes several steps: filtering, artefact detection, feature extraction, and classification. In this study, a classifier with hierarchical structure was developed and applied. Description of a committee of classifiers based on neural networks and support vector machines is given. The developed classifier demonstrated accuracy 50 ± 5% of single trial decoding of four classes of imaginary fine movements. Prospects of using non-invasive brain-computer interface for control of mobile robots was described. Key applications of the system are maintenance of immobilized patients and rehabilitation procedures both in clinic and at home.