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Tools and Methodologies for System-Level Design
Published in Louis Scheffer, Luciano Lavagno, Grant Martin, EDA for IC System Design, Verification, and Testing, 2018
Shuvra Bhattacharyya, Wayne Wolf
At present, Simulink [53], developed by the The MathWorks, is perhaps the most widely used commercial tool for model-based design of DSP hardware and software. Simulink provides a block-diagram interface and extensive libraries of predefined blocks; highly expressive modeling semantics with support for continuous time, discrete time, and mixed-signal modeling; support for fixed-point data types; and capabilities for incorporating code in a variety of procedural languages, including Matlab and C. Simulink can be augmented with various capabilities to enhance greatly its utility in DSP and multimedia system implementation. For example, various add-on libraries provide rich collections of blocks geared toward signal processing, communications, and image/video processing. The Real-time Workshop provides code generation capabilities to translate automatically Simulink models into ANSI C. Stateflow provides the capability to augment Simulink with sophisticated control flow modeling features. The Xilinx System Generator is a plug-in tool for Simulink, which generates synthesizable hardware description language code targeted to Xilinx devices. Supported devices include the Virtex-II Pro platform FPGA, which was described earlier in this chapter. The Texas Instruments Embedded Target links Simulink and the Realtime Workshop with the Texas Instruments Code Composer Studio to provide a model-based environment for design and code generation that is targeted to fixed- and floating-point programmable digital signal processors in the Texas Instruments C6000 series.
Introduction
Published in Fuewen Frank Liou, Rapid Prototyping and Engineering Applications, 2019
There are many different computational approaches to address different aspects of the design process, finite element analysis (FEA), kinematics and multi-body dynamics, electronic circuit design, CAD/immersive design, and virtual reality/topological modeling. These are all analytical prototyping methods. Model-based design is a high-fidelity mathematical model that accurately predicts the behavior of a dynamic system in real time. With more improvement in simulating physical properties, there is great potential for applications such as control system design, testing and optimization, and connecting the virtual world with the real world like hardware-in-the-loop, software-in-the-loop, and operator-in-the-loop.
Formalized Approach for the Design of Real-Time Distributed Computer Systems
Published in Katalin Popovici, Pieter J. Mosterman, Real-Time Simulation Technologies, 2017
Ming Zhang, Bernard Zeigler, Xiaolin Hu
Real-time distributed computer systems combine virtual environment (VE)– based systems, real-time peer-to-peer (P2P)–based systems, quality-of-service (QoS)–aware distributed computer systems, and hybrid systems (the systems that incorporate both real-time and non-real-time behaviors). Efficient system design for such systems requires a sound framework that can facilitate effective design modeling and simulation (M&S) as well as support for flexible testing of design alternatives. Traditional approaches to system design do not use formal system specification languages or formalisms and are based on accumulated domain knowledge. Thus, system design, in many cases, is separated from system implementation, system testing, and system validation. With the rapid advances of distributed real-time computer systems, the complexity of such systems is increasingly challenging traditional nonformalized design approaches. Therefore, formal design methods have been widely used for system design in recent years, and such efforts have been verified by many researchers as suitable for large-scale and complex systems. Among different formal approaches, it is worth noting that model-based system design has proved to be one of the most efficient methods to address the key concerns in complex system design [1–4]. Indeed, the model-based design approach uses a formal language to describe system design models, and such design models are then simulated to predict the performance of the system in real-world scenarios. In particular, the model-based formal design using Discrete Event System Specification (DEVS) [5–7] differentiates it from most other approaches because of its use of a unique integrative framework that can address most of the issues faced in complex system design, and in particular, distributed real-time computer systems.
Design, rapid manufacturing and modeling of a reduced-scale forwarder crane with closed kinematic chain
Published in Mechanics Based Design of Structures and Machines, 2022
Arturo D. López Rojas, Omar Mendoza-Trejo, Erick A. Padilla-García, Daniel Ortiz Morales, Carlos A. Cruz-Villar, Pedro La Hera
Considering the current state-of-the-art, it is necessary to start looking for different options to improve forestry cranes’ performance rather than continuing the traditional pathway of development. Model-based design has proven to be a powerful approach to improve performance in many systems by modifying their base design. It is well known that by modifying the inertial and kinematic terms of a system, the dynamic system performance will inevitably change. This is the main idea behind model-based design, to modify certain parameters to improve one or many performance criteria. In addition, the model-based design approach opens even greater opportunities to improve forestry cranes’ performance. For instance, by combining model-based design, gravity compensation and mathematical optimization, we can expect significant improvements in energy consumption, dexterity of human operators, ground damage and reduction of emissions. However, as mentioned in the introduction of this article, the success of this design approach depends on how well the model is stated and the elements that are taken into account in the model. For this reason, it is important to consider the closed-kinematic chain in the model, since there are more elements and dynamic effects that can be used to improve forestry cranes performance. Also, it is important to remember that redesigning starts by understanding the dynamic behavior of the system.
Modelling and platform application of the behaviour of a cyber physical production system
Published in International Journal of Computer Integrated Manufacturing, 2021
Simeng Song, Zengqiang Jiang, Jing Ma, Qi Li, Qiang Wang
Model-based design methods use formal models to realise the analysis, design and verification of complex systems (Bloch et al. 2017). In particular, these methods can define and describe the system and support the system analysis, design, and implementation, thereby helping the designers and system developers in different fields to understand system requirements.