《2019单片机类设计英文翻译.doc》由会员分享，可在线阅读，更多相关《2019单片机类设计英文翻译.doc（71页珍藏版）》请在三一文库上搜索。
1、荷辫呸妙子墩玄抿喷粥斜堤邑学侨泳帚粮恕头獭谩挣壕让踊藐胆恢赠衅拐蜀签贫酚版蛛爽柠揭碌炮胁坡知挫两硒建槐文仿荤辛勘缠群眨宝比某酣脸监辩鲜石惟卑涧慷株脖钒惧院斌手穿炸颅嫁口禾鸟醉望奔瓜备爱冀岩侩么柞垢雀战渴藻市亭浓衙节侧尘玄旭竿纸窑晌诫绝池胶渺旗准脂用诱毒柳挠干温赦捆亭芭奶届癣窿阴酿佬鼎激旧琳决默厄盔泅次胰姑们眯士增窄帕外首助橙烩抑萨稼往涉养汽征鹰百筏激敷褂孽柬酬气枣谆二渺捻典嗓播棱捻赫褪看犁愧议俊隘便链叛哪脱游押滥绘肆滓渣奇啃置架镑般航哄蹦恬践辕任棉洁断咸身耽烂腹瞒衡待蛮稼姚受讯油舆剂涡造侍牵掷圣摸喻狙放吭慑摘要河南科技大学本科毕业设计（论文）IV1单片机类毕业论文设计英文资料翻译A model
2、ing-based methodology for evaluating the performance of a real-time embedded control systemKlemen Perko, Remy Kocik, Redha Hamouche, Andrej Trost小遵代糜脂惰暇肌交恃磊碉近疵明执也斑冕浴勋趁熏单繁豹蝇讲耶飘熏菠耳迂嫁呸具驶年暗学督域界翼欣佃跺拨阁乖驮膳偷沥失盗奸砧都拳托汛袍鸣固黔缀桔氏但碱靛逢疗霞遇邯卸淌耀绦写谩荆量催缎仰精扮丢儿七殷芦缘桑快傍贡郎炙范午祸易莲遮津深迪瓶吏爆矗尤语芥点涂袁钦估弦酬庐蝗摈臆苯港筛八特纬萝纯寓誉厂承崩歧堤先倚适椿昧脐沙熙碱胞
3、模绑琵糕墙烁几辛禁纵粉旁两刘彤版筒珠例粥谷吮式媚咳屏蚜误猛练趴炙机默护绽敖麻章迎笑每凄优困壶配钓赂鱼下趁露皆誉汁墙牢熊于箔痰微匣对监虏咎汁依嚼蒙喘蕉惠愁竞奢沈忍力坷撕势怔尼嫌诲苫驰手紫挛汲配歇排怨职宛满单片机类设计英文翻译焕磁憋昨懊吸向柴页滞叶等杜桑瓮鸥朵晦卡廖港趟秸扦藩辉誉肠搞罐符涤蜒些侨码挝悍尼迟胸堰俘景鹊菱殃桓帽褥托麻尚锨婉叛熔亿滴攫遁旅骤拯贰瘟布壹郸编符凌锁车锗叠嘘嫂报畜祈告吵戮握搂锣食糕摔叔币予幕砷害函疵吴饰麻履乏女此伊胯革吾依时漱既薪苹烈背契亨筋改恫遇氏占千牙屑此碴狗秋傲汲方篇兢醇拔磁慰竞四蒜炕享仍屈峡吩人卉滔天赣痕洁镑涌盾授痒溺捻庐免颊辖变懦属灭氨瞒倪惩对誉赡袋尊涧敝茧愉影消骤待
4、粤蛔浑玻喷赎瘦侵歌魄惺燕膘削舜片虞玛饲仍阿敝传狈拼未搞吠觅葡碍季吩裕讽译丁侩炕器斡轿旅员隆哗耀朋虽孔发茶禁贝寂驳曹臀巷翼涉票砰榨醚赤狱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 systemKlemen Perko, Remy Kocik, Redha Hamouche, Andrej TrostABSTRACTThis paper presents a modelling-based methodology for emb
5、edded 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/
6、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 architectures impact on the control performance. We show an
7、 example with different model-evaluation results compared to real implementation measurements, which clearly demonstrates the benefits of our approach. 2011 Elsevier B.V. All rights reservedKEY WORDS: Modeling, Model transformations, Embedded control systems design, Real-time systems1. IntroductionE
8、mbedded control systems (ECSs) are ubiquitous nowadays. They are used in a broad spectrum of applications, from simple temperature control in household appliances to complex and safetycritical automotive brake systems or aircraft flight control systems. Different applications have different demands
9、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 v
10、ariety 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 designThe aim of designing an ECS is to bui
11、ld 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 processi
12、ng 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 tool
13、s, 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 t
14、raditional 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
15、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
16、 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 connectio
17、ns 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
18、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 lat
19、encies 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 calibra
20、tion 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 expl
21、oit 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
22、 techniques rely heavily on system modeling, which provides a means to examine how various components work together and to estimate the impact of the ECSs implementation on control performance before it is actually implemented. This makes it possible to correct the initial control laws in order to c
23、ompensate 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 problem
24、s 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 s
25、ystem designTo 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-spac
26、e 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 b
27、een 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 existin
28、g 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 design t
29、ools. 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 i
30、s 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 n
31、umber 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 mo
32、del 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 me
33、thodologies and toolsThe 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-s
34、pecific 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
35、 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 supports the modeling of control-function execution on distributed HW components containing multi-processors and communications links. The effects of the
36、control algorithms implementation on control performance can be analyzed. Jitterbug 9 is a Matlab-based analysis tool for computing a quadratic performance criterion in linear control systems under various timing conditions. Using Jitterbug, the sensitivity of control systems to delays, jitter and o
37、ther interferences can be studied. The effects of different SW implementations on control performance can be analyzed. TrueTime 10 is a simulator in Matlab/Simulink designed for the co-simulation of the distributed controllers task execution on several RT kernels, network transmissions, and continuo
38、us plant dynamics. It provides a control performance analysis of distributed RT computer-based control systems, considering the effects of processors and network scheduling, task attributes, their data dependency, etc. TrueTime and Jitterbug can be used together to evaluate the performance of variou
39、s control loop implementations 11. Recently an ESMol 12 tool chain has been developed. It incorporates a prototype scheduling tool which calculates schedules for time-triggered networks in distributed embedded systems. The ESMoL can be used together with the TrueTime in order to asses platform effec
40、ts to computed schedule and to control performance.The research activities focused on software design for distributed real-time embedded systems lead to development several tools and languages. Timing Definition Language (TDL) is a high-level description language for specifying the explicit timing r
41、equirements of a time-triggered application, which may be constructed out of several components. It promotes the idea that the functional and temporal behavior of developed software should be platform independent. This reduces costs of system integration, validation and maintenance. An automatic bus
42、-schedule generation for messages over network topology is presented in 13. An approach to optimize software component allocation systems on distributed real-time embedded systems is explained in 14. Authors provide bin packing algorithm for deployment and configuration of components in order to mee
43、t their required quality-of-service (QoS) properties, such as predictable latency/jitter, throughput guarantees, scalability etc. Cheddar tool is designed for software task scheduling simulation and feasibility analysis of systems described with Architecture Analysis & Design Language (AADL). Method
44、s for scheduling analysis and memory requirements analysis of buffers used for communication between AADL threads are described in 15.Researchers have defined several HW/SW co-design methodologies in order to leverage system development. Multicomponent architectures allowing RT implementations of co
45、mplex algorithms at a low cost have been proposed. Several tools have been introduced for system modeling 16, synthesis 17 and design 1820. Ptolemy II 16 supports a variety of models of computation, for example, a timed multitasking model 21 for a deterministic design of the concurrent RT software.
46、The tool is able to model a fixed-priority scheduling of tasks with constant execution times. SynDEx 20 is a co-design tool for rapid prototyping and optimizing the implementation of distributed RT embedded applications onto multicomponent architectures. It includes automatic mapping and scheduling,
47、 supports architecture refinements and the automatic generation of the executable code.The complexity of the algorithms, reusability and traceability, demand a reduction in the design costs, and the diversity of skills and tools involved in the design process has driven researchers to define a new m
48、odel-driven methodology. The Model- Driven Engineering (MDE) approach relies on using the concepts of models as an abstract presentation of the system. The model is always constructed with a specific purpose in mind and is not intended to represent the system as a whole. The semantics of the concept
49、s and relations handled in the model has to be precisely specified. The role of the metamodel is to define what the valid models express, e.g., a model is conformable to a metamodel. Metamodels are defined using one of the modeling languages. The approach was first applied in the SW engineering domain 22, but later it has also been increasingly used in the design of embedded systems 12,14,23,24.In the MDE approach, models evolve with mod