Tvarování vstupu pro podtlumené systémy

The main aim of this paper is to provide possibility to test and validate multiple damping and input shaping methods for underdamped systems. Mathematical model for specific development and demonstration was created in Matlab Simscape environment. Additional Matlab Simulink system was modelled to achieve proper data acquisition and comparison in contrast to plain system without any special damping methods.Hlavním cílem této práce je poskytnout možnost testování a validace více metod tlumení a vstupních tvarů u podtlumených systémů. Matematický model pro specifický vývoj a demonstraci byl vytvořen v prostředí Matlab Simscape. Další systém Matlab Simulink byl modelován tak, aby dosáhl správného získávání a srovnání dat v porovnání s běžným systémem bez zvláštních metod tlumení

Advanced nonlinear modelling techniques for switched reluctance machines

This paper gives an overview of different modelling techniques to describe the nonlinear behaviour of both saturated switched reluctance machine (SRM) and power electronic converter. The current research contributes by comparing the de-coupled single-phase superposition method (lookup-tables) with a coupled analysis between drive model in Matlab/Simulink® and finite element model of the SRM motor. Experimental characterization techniques as well as finite element techniques are used to obtain the single-phase flux-linkage data. Transient electromagnetic analysis using the finite element method,coupled with a drive model and optimization strategy in Matlab/Simulink®, results in a more accurate SRM modelling. These results are more accurate because the mutual coupling between different phases is taken into account. Using this direct coupling, a complete analysis of the motor behaviour (local saturation, iron losses, …) can be modelled with the finite element software, keeping the complex drive and control strategy in Matlab/Simulink®.At every time step of the discrete solver, data is exchanged between the drive model and the coupled electric circuit of the finite element analysis.Simulation results are compared with measurements offlux-linkage, torque, phase current and iron losses. Pro’s and contra’s of the coupled and de-coupled modelling technique are discussed

Simulation of complex environments:the Fuzzy Cognitive Agent

The world is becoming increasingly competitive by the action of liberalised national and global markets. In parallel these markets have become increasingly complex making it difficult for participants to optimise their trading actions. In response, many differing computer simulation techniques have been investigated to develop either a deeper understanding of these evolving markets or to create effective system support tools. In this paper we report our efforts to develop a novel simulation platform using fuzzy cognitive agents (FCA). Our approach encapsulates fuzzy cognitive maps (FCM) generated on the Matlab Simulink platform within commercially available agent software. We firstly present our implementation of Matlab Simulink FCMs and then show how such FCMs can be integrated within a conceptual FCA architecture. Finally we report on our efforts to realise an FCA by the integration of a Matlab Simulink based FCM with the Jack Intelligent Agent Toolkit

Fully automatic worst-case execution time analysis for MATLAB/Simulink models

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”In today's technical world (e.g., in the automotive industry), more and more purely mechanical components get replaced by electro-mechanical ones. Thus the size and complexity of embedded systems steadily increases. To cope with this development, comfortable software engineering tools are being developed that allow a more functionality-oriented development of applications. The paper demonstrates how worst-case execution time (WCET) analysis is integrated into such a high-level application design and simulation tool MATLAB/Simulink-thus providing a higher-level interface to WCET analysis. The MATLAB/Simulink extensions compute and display worst-case timing data for all blocks of a MATLAB/Simulink simulation, which gives the developer of an application valuable feedback about the correct timing of the application being developed. The solution facilitates a fully-automated WCET analysis, i.e., in contrast to existing approaches the programmer does not have to provide path information

Control of the weakly damped System with the embedded system support

This paper deals with the experimental verification of the importance of embedded systems with an applied MEMS sensor in controlling weakly damped systems. The aim is to suppress actively residual oscillations. The model of a planar physical pendulum with a prismatic joint was chosen for the experiment. The sensor made by MEMS technology, in which three-axis gyroscope and three-axis accelerometer are integrated, has been used for sensing the angle of deflection of the load from the equilibrium position. The simulation model represents the crane arm with a moving carriag

Evaluation of Variability Concepts for Simulink in the Automotive Domain

Modeling variability in Matlab/Simulink becomes more and more important. We took the two variability modeling concepts already included in Matlab/Simulink and our own one and evaluated them to find out which one is suited best for modeling variability in the automotive domain. We conducted a controlled experiment with developers at Volkswagen AG to decide which concept is preferred by developers and if their preference aligns with measurable performance factors. We found out that all existing concepts are viable approaches and that the delta approach is both the preferred concept as well as the objectively most efficient one, which makes Delta-Simulink a good solution to model variability in the automotive domain.Comment: 10 pages, 7 figures, 6 tables, Proceedings of 48th Hawaii International Conference on System Sciences (HICSS), pp. 5373-5382, Kauai, Hawaii, USA, IEEE Computer Society, 201

IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink

This paper proposes an integrated development framework that enables co-simulation and operation of a Robot Operating System (ROS)-based self-driving system using MATLAB/Simulink (IDF-Autoware). The management of self-driving systems is becoming more complex as the development of self-driving technology progresses. One approach to the development of self-driving systems is the use of ROS; however, the system used in the automotive industry is typically designed using MATLAB/Simulink, which can simulate and evaluate the models used for self-driving. These models are incompatible with ROS-based systems. To allow the two to be used in tandem, it is necessary to rewrite the C++ code and incorporate them into the ROS-based system, which makes development inefficient. Therefore, the proposed framework allows models created using MATLAB/Simulink to be used in a ROS-based self-driving system, thereby improving development efficiency. Furthermore, our evaluations of the proposed framework demonstrated its practical potential

Testing of linear models for optimal control of second-order dynamical system based on model-reality differences

In this paper, the testing of linear models with different parameter values is conducted for solving the optimal control problem of a second-order dynamical system. The purpose of this testing is to provide the solution with the same structure but different parameter values in the model used. For doing so, the adjusted parameters are added to each model in order to measure the differences between the model used and the plant dynamics. On this basis, an expanded optimal control problem, which combines system optimization and parameter estimation, is introduced. Then, the Hamiltonian function is defined and a set of the necessary conditions is derived. Consequently, a modified model-based optimal control problem has resulted. Follow from this, an equivalent optimization problem without constraints is formulated. During the calculation procedure, the conjugate gradient algorithm is employed to solve the optimization problem, in turn, to update the adjusted parameters repeatedly for obtaining the optimal solution of the model used. Within a given tolerance, the iterative solution of the model used approximates the correct optimal solution of the original linear optimal control problem despite model-reality differences. The results obtained show the applicability of models with the same structures and different parameter values for solving the original linear optimal control problem. In conclusion, the efficiency of the approach proposed is highly verified