电气工程专业英语翻译

1、 Step 7. Try an optimal design. If the trial-and-error compensators do not give entirely satisfactory performance, consider a design based on optimal control. The symmetric root locus will show possible root locations from which to select locations for the control poles that meet the response specif

2、ications; you can select locations for the estimator poles that represent a compromise between sensor and process noise. Plot the corresponding and its robustness to parameter changes. You can modify the pole locations until a best compromise results. Returning to the symmetric root locus with diffe

3、rent cost measures is often a part of this step. or computations via the direct functions Iqr and Iqe can be used. Another variation on optimal control is la propose a find structure controller with unknown parameters. formulate a performance cost function. and use parameter optimization to find a g

4、ood set of parameter values.Compare the optimal design yielding the most satisfactory frequency response with the transform-method design you derived in Step 5. Select the better of the two before proceeding to Step 8. Step 8 Build a computer model, and compute (simulate) the performance of the desi

5、gn. After reaching the best compromise among process modification, actuator and sensor selection, and controller design choice, run a computer, run a computer model of the system. This model should include important nonlinearities such as actuator saturation, realistic noise sources, and parameter v

6、ariations you expect to find during operation of the system. The simulation will often identify sensitivities that may lead to going back to Step 5 or even Step 2. Design iterations should continue until the simulation confirms acceptable stability and robustness. As part of this simulation you can

7、often include parameter optimization, in which the computer tunes the free parameters far best for best performance. In the early stages of design, the model you simulate will be relatively simple; as the design progresses, you will study more complete and detailed models. At this step it is also po

8、ssible to compute a digital equivalent of the analog controller. Some refinement of the controller parameters may be required to account for the effects of digitization. This allows the final design to be implemented with digital processor logic. If the results of the simulation prove the design sat

9、isfactory, go to Step 9; otherwise return to Step 1. Step 9. Build a prototype. As the final test before production, it is common to build and test a prototype- At this point you verify the quality of the model, discover unsuspected vibration and other modes, and consider ways to improve the design.

10、 Implement the controller using an embedded software/hardware. Tune the controller if necessary. After these tests, you may want to reconsider the sensor, actuator, and process and return to Step 1-unless time, money, or ideas have run out.This outline is an approximation of good practice; other eng

11、ineers will have variations on these themes. In some cases you may wish to carry out them in a different order, to omit a step, or to add one. The stages of simulation prototype construction vary widely, depending on the nature of the system. For systems where a prototype is difficult to test and re

12、work (for example, a satellite) or where a failure is dangerous (for example, active stabilization of a high-speed centrifuge or landing a human on the moon), most of the design verification is done through simulation of some sort. It may take the form of a digital numerical simulation, a laboratory

13、-scale model, or a full-size laboratory model with a simulated (for example, feedback control for an automotive fuel the simulation step is often skipped entirety; design verification and refinement are accomplished by working with prototype. One of the issues raised above (Step 6) was the important

14、 consideration for changing the plant itself. In many cases, proper plant modifications can provide additional damping or increase in stiffness, change in mode shapes, reduction of system response to disturbances, reduction of Coulomb friction, and change in thermal capacity or conductivity, and so

15、on. It is worth elaborating on this byway of specific examples from the authors' experiences. In a semiconductor processing example, the edge ring holding the wafer was identified as a limiting factor in closed- loop control. Modifying the thickness of the edge ring and using a different coating

16、 material reduced the heat losses and, together with relocating one of the temperature sensors closer to the edge ring. resulted in significant improvement in control performance. In another application, thin film processing, simply change the order of the two incoming flows resulted in significant

17、improvement in uniformity of the film. In an application on vapor deposition using RF plasma, the shape of the target was modified lo be curved to counter the geometry effects of the chamber and yielded substantial improvements in deposition uniformity. As the last example, in a hydraulic spindle co

18、ntrol problem adding oil temperature control with ceramic insulation and a temperature sink for the bell housing resulted in several orders of magnitude reduction in disturbances not achievable by feedback control alone. One can also mention aerospace applications where the control was an after thou

19、ght. and the feedback control problem became resulted in poor closed-loop performance. The usual approach of designing the system has been proved to be inefficient and flawed. A better approach that is gaining momentum is to get the control engineer involved from the onset of a project to provide ea

20、rly feedback on how hard it is to control the system. The control engineer can provide valuable feedback on choice of actuators and sensors and even suggest modifications to the plant. It is often much more efficient to change the plant design while it is on the drawing board before "any metal

21、has been bent". Closed-loop performance studies can then be performed on a simple model of the system early on. Implicit in the process of design is the well-known fact that designs within a given category often draw on experience gained from earlier models. Thus good designs evolve rather than

22、 appear in their best form after the first pass. 1)Understand the process and its performance requirements. 2) Select the types and numbers of sensors considering location, technology, and noise. 3) Select the types and number of actuators considering location, technology, noise and power. 4 ) Make

23、a linear model of the process , actuator, and sensor .5 ) Make a simple trial design based on the concepts of lead-lag compensation or PID control.If satisfied , go to step 8.6 ) Consider modifying the plant itself for improved closed-loop control.7 ) Make a trial pole-placement design based on opti

24、mal control or other criteria.8 ) Simulate the design , including the effects of nonlinearities , noise , and parameter variations. If the performance is not satisfactory,return to Step 1 and repeat.Consider modifying the plant itself for improved closed-loop control.9 ) build a prototype and test i

25、t if not satisfied , return to step 1 and repeat . 步骤7。尝试一个最优的设计。如果试错补偿器给不出完全令人满意的性能,考虑基于最优控制的设计。对称的根轨迹将显示可能的根位置选择的位置控制杆,满足响应规范;您可以选择位置的估计量柱代表传感器和过程噪声之间的妥协。将相应的和它的健壮性用于参数更改。你可以修改极点位置直到一个最好的折衷结果。使用不同的成本度量返回对称根位置通常是这一步骤的一部分。或者通过直接函数Iqr和Iqe来计算。另一个在最优控制上的变化是，提出一个具有未知参数的结构控制器。制定绩效成本函数。并使用参数优化来找到一组良好的参数值。

26、 比较优化设计的最满意的频率响应与转换方法设计您在步骤5中派生。在继续步骤8之前，选择更好的两个。 步骤8构建一个计算机模型，并计算(模拟)设计的性能。在处理过程修改中，执行机构和传感器选择，以及控制器的设计选择，运行计算机，运行计算机模型。这个模型应该包括重要的执行机构饱和等非线性,现实的噪声源,你希望找到和参数变化时系统的操作。模拟通常会识别出可能导致回到第5步甚至第2步的敏感问题。设计迭代应该继续，直到模拟确认了可接受的稳定性和健壮性。作为这个模拟的一部分，您可以经常包含参数优化，在这种情况下，计算机对自由参数进行优化，以获得最佳性能。在设计的早期阶段，您模拟的模型将相对简单;随着设计的

27、进行，您将学习更加完整和详细的模型。在这个步骤中，也可以计算一个模拟控制器的数字等价物。为了解释数字化的影响，可能需要对控制器参数进行一些细化。这使得最终的设计可以用数字处理器逻辑实现。  如果仿真结果证明设计满意，就进入第9步;否则返回第1步。  步骤9。构建一个原型。作为最终测试前生产,共同构建和测试原型在这一点上你验证模型的质量,发现未知的振动和其他模式,并考虑如何改进设计。使用嵌入式软件/硬件实现控制器。必要时调优控制器。在这些测试之后，您可能需要重新考虑传感器、执行器和过程，并返回到步骤1，除非时间、金钱或想法已经耗尽。 这个大纲近似于良好的实践;其他的工程师将会

28、对这些主题有不同的变化。在某些情况下，您可能希望以不同的顺序执行它们，省略步骤，或者添加一个步骤。根据系统的性质不同，模拟样机的各个阶段都有很大的不同。系统原型难以测试和返工(例如,一个卫星)或失败是危险的(例如,积极稳定的高速离心机或人类在月球上着陆),大部分的设计验证是通过某种形式的模拟。可能需要一个数字数值模拟的形式,一个实验室规模模型,或一个全尺寸的实验室模型模拟(例如,反馈控制的汽车燃料通常跳过仿真步骤完整;设计验证和改进是通过使用原型。 上面提到的一个问题(步骤6)是改变植物本身的重要考虑因素。在许多情况下,适当的植物可以提供附加阻尼或刚度的增加,修改模式形状的变化,减少干扰的系统

29、响应,减少库仑摩擦,和热能力或电导率的变化,等等从作者的经历中，我们可以详细地说明这一点。在半导体处理的例子中，晶圆片的边缘环被认为是闭环控制的一个限制因素。修改边缘环的厚度，使用不同的涂层材料，减少了热损失，并将其中一个温度传感器重新安置到边缘环上。结果在控制性能上有了显著的提高。在另一个应用中，薄膜处理简单地改变了两个输入流的顺序，使得电影的一致性得到了显著的改善。摘要在应用射频等离子体气相沉积的应用中，对目标的形状进行了修正，以对抗腔体的几何效应，并在沉积均匀性方面取得了实质性的改进。最后一个例子,在液压主轴控制问题添加与陶瓷绝缘油温度控制和温度水槽的钟形壳导致好几个数量级减少干扰不是单靠反馈控制可以实现的。人们还可以提到航空航天应用，在那里，控制是经过深思的。反馈控制问题导致了闭环性能的不佳。 设计这个系统的一般方法被证明是低效和有缺陷的。一个更好的方法是让控制工程师参与项目的开始，以提供对控制系统的困难程度的早期反馈。控制工程师可以对执行机构和传