Genetic algorithms are used to parameter identification of the model of oscillatory processes in complicated motion transmission of electric drives containing long elastic shafts as systems of distributed mechanical parameters. Shaft equations are generated on the basis of a modified Hamilton–Ostrogradski principle, which serves as the foundation to analyse the lumped parameter system and distributed parameter system. They serve to compute basic functions of analytical mechanics of velocity continuum and rotational angles of shaft elements. It is demonstrated that the application of the distributed parameter method to multi-mass rotational systems, that contain long elastic elements and complicated control systems, is not always possible. The genetic algorithm is applied to determine the coefficients of approximation the system of Rotational Transmission with Elastic Shaft by equivalent differential equations. The fitness function is determined as least-square error. The obtained results confirm that application of the genetic algorithms allow one to replace the use of a complicated distributed parameter model of mechanical system by a considerably simpler model, and to eliminate sophisticated calculation procedures and identification of boundary conditions for wave motion equations of long elastic elements.
In the paper, the kinematic structure of the transmission shaft between the driving motor and the working mechanism is studied. The analysis is based on electrical and mechanical similarities. The equivalent circuits, typical for electrical systems, are defined for the transmission shaft concerned. Modelling of the transmission shaft based on a formal analogy between the transmission shaft and the electric transmission line is also proposed. The results of a computer simulation and experimental test are presented. The results confirm the high conformity of the proposed mathematical model with the physical object.
In the paper, based on interdisciplinary approaches to modeling, a mathematical model of a part of an opened extra-high voltage electrical grid, which key elements are two long power transmission lines with distributed constants is presented. Within this framework the analysis of transient processes in power transmission lines in a single-line arrangement is carried out. The results of transient processes are displayed by means of figures; they are under ongoing research.
In remote locations, it is advisable to combine solar water pumping with electric energy storage and power supply for other forms of consumption. In such complex systems, individual subsystems feature their own local control, and the general automatic control of the system in different modes of its operation is carried out in accordance with an energy management strategy (EMS). In this paper, the functions of local and general control of the solar water pumping system with battery storage and external power supply are combined in the system of passivity-based control (PBC). The EMS is constructed in such a way that for all modes, only two PBC systems are developed, which are switched depending on the battery’s state of charge and the current levels of the two main disturbances—solar irradiation and electrical consumption. For each system, two control influence former (CIF) structures were synthesized and their operation was investigated by computer simulation. Despite the simplicity of CIFs’ implementation, due to the introduced interconnection and damping coefficients, such control allows the provision of the required voltage regulation with a static error up to 1%, sufficient quality of transients during disturbances and switching of the system structure, as well as system asymptotic stability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.