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单片机类毕业论文设计-英文翻译.doc 是一篇关于实时嵌入式控制系统性能评估的文献。该论文提出了一种基于模型的方法论，旨在改进现有的嵌入式控制系统（ECS）设计流程，通过与嵌入式系统其他领域的设计方法相结合，提高设计效率和准确性。文章的摘要指出，作者并未开发全新的设计方法，而是建议对现有方法进行升级。他们建立了一个控制调度工具和硬件/软件（HW/SW）协同设计工具之间的转换桥梁。这一桥梁定义允许自动模型转换，从而在模拟中更精确地考虑实时软件以及硬件架构对控制性能的影响。通过比较模型评估结果与实际实现测量值，作者展示了这种方法的优势。关键词包括：建模、模型转换、嵌入式控制系统设计、实时系统。在引言部分，论文强调了嵌入式控制系统的广泛应用，从家用电器的简单温度控制到汽车刹车系统和飞机飞行控制系统等复杂且安全关键的领域。不同应用对ECS的实时执行、控制性能、能耗和成本等方面有不同的需求。现代硬件和软件设计技术提供了多种可能的设计选择，如分布式和网络化的硬件、多处理器系统、各种软件控制算法和实时操作系统（RTOS）等。设计可靠且高效的ECS是一项具有挑战性的任务，因为需要考虑的因素众多，包括实时性、控制精度、能耗优化以及成本控制等。为了解决这些挑战，论文提出的建模方法论通过自动化模型转换和整合不同设计阶段的工具，有助于在早期设计阶段就预测和优化系统的性能。文章接下来可能会详细探讨模型构建的过程，转换规则的设定，以及如何通过这种方法进行性能评估。此外，可能会涉及具体案例研究，展示如何将该方法应用于实际的ECS设计中，以及它如何帮助避免潜在的问题和改进设计效率。通过这种方式，论文为读者提供了一种实用的工具，以应对日益复杂的嵌入式控制系统设计挑战。

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河南科技大学本科毕业设计（论文）

单片机类毕业论文设计

英文资料翻译

A modeling-based methodology for evaluating the

performance of a real-time embedded control system

Klemen Perko, Remy Kocik, Redha Hamouche, Andrej Trost

ABSTRACT

This paper presents a modelling-based methodology for embedded control

system (ECS) design. Here, instead of developing a new methodology for ECS

design, we propose to upgrade an existing one by bridging it with a methodology

used in other areas of embedded systems design. We created a transformation

bridge between the control-scheduling and the hardware/software (HW/SW)

co-design tools. By defining this bridge, we allow for an automatic model

transformation. As a result, we obtain more accurate timing-behaviour

simulations, considering not only the real-time software, but also the hardware

architecture’s impact on the control performance. We show an example with

different model-evaluation results compared to real implementation

measurements, which clearly demonstrates the benefits of our approach.

KEY WORDS: Modeling, Model transformations, Embedded control systems

design, Real-time systems

1. Introduction

Embedded control systems (ECSs) are ubiquitous nowadays. They are used

河南科技大学本科毕业设计（论文）

in a broad spectrum of applications, from simple temperature control in

household appliances to complex and safety–critical automotive brake systems

or aircraft flight control systems. Different applications have different demands

with regards to the real-time execution, control performance, energy

consumption, price, etc., of the ECS being used. Modern technologies for

hardware (HW) and software (SW) design provide a variety of possibilities for

designing ECSs (e.g., distributed and networked HW, multi-processor systems, a

variety of SW control algorithms and real-time operating systems (RTOSs), etc.)

[1]. It is commonly acknowledged that the designing and verifying of reliable

and efficient ECSs for a particular application are challenging tasks.

1.1. Traditional control-system design

The aim of designing an ECS is to build a computing system that is able to

control the behavior of a physical system, e.g., a plant. Such a plant is made up

of interconnected mechanical, electrical and/or chemical elements. A typical

ECS consists of electronic sensors for data acquisition from the plant, a

computing system for processing the control algorithm, and electronic actuators

to drive the plant.

The ECS design process involves different actors and areas of expertise

(control theory, signal processing, real-time SW and HW engineers). Each of

these engineers is familiar with their own modeling languages, models, design

tools, etc. This heterogeneity introduces cuts in the design process. Model

transformations are needed between each design step; however, they are often

carried out manually and, as a result, are prone to mistakes and subject to

interpretation, which of course depends on the skill of the designer. The

traditional form of ECS design is performed in two separated domains – the

control SW domain and the HW domain – using specific design tools and their

respective system models. In the first domain, control engineers define the

control laws and the SW engineers write the code that executes the operations

河南科技大学本科毕业设计（论文）

required by the control laws. A so-called control-scheduling co-design is

performed. Decisions made in the real-time (RT) software design affect the

control design, and vice versa. For instance, different SW scheduling policies

have different impacts on the latency distributions in the control loops and,

consequently, on their performance. Also, the control-loop performance directly

affects (by constraining) the SW execution parameters (i.e., sampling periods,

task-execution jitter, etc.).

In the second domain the HW engineers design an HWplatform that will

execute the control SW. The connections of all the sensors and actuators to the

platform are made via the available communication channels. However, because

the HW platform is designed separately, control engineers cannot estimate its

impact on the control-loop performance. For instance, the data from sensors and

to actuators can pass through one or more communication channels. A HW

engineer can, in general, choose from among a variety of communication

protocols, and each type introduces different latencies and jitter, which therefore

affects the SW execution. The control engineer cannot, however, evaluate the

effect of these latencies before the system is actually implemented. Hence, the

desired performance of the system may not be achieved, and it is necessary to

change and tune the control laws (calibration phase) in order to compensate for

the impact of these communication and execution delays. The fact that the

calibration has to be performed on an actual plant can be very expensive and

time-consuming, especially when the desired performance cannot be achieved

using the current HWplatform and a redesign is required. Another shortcoming

of traditional ECS design is the inability of control and SW engineers to exploit

some of the advantages offered by modern HW technologies. For instance,

control loops running in parallel, instead of the traditional sequential execution,

could give better performance. Parallel execution can be achieved with the use

of multi-processor or distributed platforms.

Modern ECS design techniques rely heavily on system modeling, which

河南科技大学本科毕业设计（论文）

provides a means to examine how various components work together and to

estimate the impact of the ECS’s implementation on control performance before

it is actually implemented. This makes it possible to correct the initial control

laws in order to compensate for the implementation impacts early in the design

cycle. Another important aspect of modeling is the ability to explore different

possible system implementations (design-space exploration). Appropriate

modeling can significantly shorten the design cycle of an ECS [2].

To overcome the problems introduced by the heterogeneity of design

models and tools, different methodologies and tools were developed [3]. These

methodologies usually provide a means to create a uniform ECS model, simulate

and evaluate its behavior, formally transform it towards an implementation, etc.

1.2.Proposed control system design

To improve and accelerate the traditional ECS design we propose the

merging of these separated domains. On the basis of this merging, all the actors

in the design process could better collaborate and exchange their data during the

design process, they could do a more thorough design-space exploration and the

design cycle could be made significantly shorter. Instead of developing a new

methodology for ECS design, we propose to upgrade the traditional SW-based

control-system design approach with efficient modeling and design of the HW

platforms. Recently, several methodologies have been developed that concern

HW/SW co-design. These methodologies enable the efficient design of SW and

HW on embedded systems in terms of SW execution speed, HW resources usage,

system flexibility, future upgradeability, final design costs, etc. We propose

creating a formal bridge between the existing tools for control-scheduling

co-design and HW/SW co-design. This bridge makes possible model

transformations and the exchange of simulation results between tools for

control-scheduling co-design and HW/SW co-design.

The bridge is based on a formal transformation of models between different

河南科技大学本科毕业设计（论文）

design tools. Our foundation for the control scheduling co-design methodology

is work presented in [4] and its associated tool, MoDEST, which is presented in

[5]. For the purpose of HW/SW co-design we have selected the methodology

presented in [6] with its associated abstract-system modeling tool, ASyMod,

which is presented in [7].With the bridge we are able to obtain more accurate

control-performance evaluations considering architectural details and even the

possibility to study mixed HW/SW implementations of the control system.

Evaluating the impact of implementation in the early design stages reduces the

number of design-lifecycle iterations and shortens the time needed for a final

calibration of the control laws.

In the next section we present the related methodologies, followed by short

descriptions of the MoDEST and ASyMod tools and their metamodels. In

Section 3 we describe the formal rules for model transformation and the

implementation of the bridge. In Section 4, two examples of an embedded

controller are presented. By comparing simulation results to measurements on a

real implemented system, we show the benefits of our approach. Finally, the

paper is concluded in Section 5.

1.3.Related methodologies and tools

The increasing need to optimize ECSs in terms of their control performance,

RT constraints and cost efficiency has led to limited computational resources

combined with their efficient exploitation and has, as a consequence, encouraged

the emergence of new research areas.

Domain-specific tools for control-scheduling co-design have been

developed recently. These tools support implementation modeling and analysis

in terms of control performance. Several of the tools are based on Matlab, which

is traditionally used by control engineers for the design of control laws. The

AIDA [8] toolset is a model-based environment for the design and analysis of

control systems, used either in stand-alone form or with Matlab. The toolset

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