电气工程专业英语翻译

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 specifications; 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 different 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 good 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 design. 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 variations 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 canoften 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 possible 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 satisfactory, 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. 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 engineers 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

rework (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-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 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

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 material reduced the heat losses and, together with relocating

one of the temperature sensors closer to the edge ring. resulted in