控制系统设计：PID控制与诊断指南

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"控制系统设计指导：使用计算机理解和诊断反馈控制器" 在控制系统的设计和应用领域，基础知识自20世纪初就已经奠定。控制系统的概念，如炮台瞄准或水温调节，与我们今天所使用的并无太大差异。尽管随着时间的推移和技术的进步，数字处理器改变了我们实施控制算法的方式，但许多情况下，算法的本质并未改变。比例积分微分（PID）控制在过去的四五十年间，其工作原理基本保持不变。控制系统的广泛应用使其在教育体系中占据了一席之地。大多数工程大学都提供相关课程，甚至有些专业要求学生进行基础训练。考虑到这些原则的持久性和大量受过培训的工程师参与其中，我们可能会期待大多数从业者对基础有深入理解。然而，实际情况似乎并非如此。 "Control System Design Guide"是由George Ellis撰写的第四版专著，由Kollmorgen Corporation出版，是Butterworth-Heinemann的 imprint of Elsevier的一部分。这本书自1991年首次出版以来，历经多次修订，最新的第四版于2012年发布，反映了该领域的最新进展。本书旨在帮助读者理解和诊断反馈控制器，利用计算机作为工具来优化控制系统的性能。书中可能涵盖了以下内容： 1. 控制系统的基本原理：包括负反馈、稳定性分析、频率响应和时域分析等基础概念。 2. PID控制器的工作机制：解释了比例、积分和微分三个部分如何协同工作，以实现精确控制。 3. 数字控制的实现：讨论了如何使用数字处理器来模拟传统的模拟控制策略，并探讨其优点和挑战。 4. 系统建模与仿真：介绍了如何构建数学模型，并通过计算机仿真来预测和优化系统行为。 5. 控制器参数调整：讲述了如何通过试错法或优化算法来调整PID参数，以达到最佳性能。 6. 面向实际应用的设计考虑：包括噪声处理、系统干扰抑制和抗振性设计等方面。 7. 故障诊断和故障安全设计：讨论如何检测系统异常并确保在故障条件下系统的安全运行。此外，书中可能还涉及了版权和许可信息，提醒读者在复制或传播内容时必须获得出版商的书面许可，并提供了获取许可的途径。《控制系统设计指导》不仅提供了控制系统设计的基础理论，还强调了如何将这些理论应用于实际问题的解决，是工程师和学生深入理解控制系统的宝贵资源。通过阅读此书，读者能够提升在控制系统设计和诊断方面的技能，更好地应对实际工程挑战。

3. Always follow national, state, local, and professional safety code regulations.

4. Always follow the safety guidelines instituted at the plant where the equipment will be

operated.

5. Always use appropriate safety equipment, for example, protective eyewear, hearing protec-

tion, safety shoes, and other protective clothing.

6. Never attempt to override safety devices such as limit switches, emergency stop switches,

light curtains, or physical barriers.

7. Always keep clear from machines or processes in operation.

8. Provide reliable protection, such as mechanical stops and emergency off switches, so that

unanticipated behavior from the controller cannot harm you or anyone else, and cannot

damage equipment.

Remember that any change of system parameters (for example, tuning gains), components,

wiring,

or any other function of the control system may cause unexpected results, such as

system instability or uncontrolled system excitation.

Remember that controllers and other control system components are subject to failure. For

example, a microprocessor in a controller may experience catastrophic failure at any time.

Leads to or within feedback devices may open or short together at any time. Failure of

a controller may cause unexpected results, such as system instability or uncontrolled system

excitation.

This book presents observers, the use of which within control systems poses certain risks,

including that the observer may become unstable or otherwise fail to observe signals to an

accuracy necessary for proper system operation. Ensure that observers behave properly in all

operating conditions.

If you have any questions concerning the safe operation of equipment, contact the equipment

manufacturer, plant safety personnel, or local governmental ofﬁcials, such as the Occupational

Health and Safety Administration.

Always operate control systems safely!

2 Section I

CHAPTER 1

Introduction to Controls

Chapter Outline

1.1 Visual ModelQ Simulation Environment 4

1.1.1 Installation of Visual ModelQ 4

1.1.2 Errata 4

1.2 The Control System 5

1.2.1 The Controller 5

1.2.2 The Machine 6

1.3 The Controls Engineer 6

Control theory is used for analysis and design of feedback systems, such as those that regulate

temperature, ﬂuid ﬂow, motion, force, voltage, pressure, tension, and current. Skillfully used,

control theory can guide engineers in every phase of the product and process design cycle.

It can help engineers predict performance, anticipate problems, and provide solutions.

Colleges teach controls with little emphasis on day-to-day problems. The academic community

focuses on mathematical derivations and on the development of advanced control schemes; it

often neglects the methods that are commonly applied in industry. Students can complete

engineering programs that include courses on controls and still remain untutored on how to

design, model, build, tune, and troubleshoot a basic control system. The unfortunate result is

that many working engineers lay aside analysis when they practice their profession, relying

instead on company history and trial-and-error methods.

This book avoids the material and organization of most control theory textbooks. For example,

design guidelines are presented throughout; these guidelines are a combination of industry-

accepted practices and warnings against common pitfalls. Nontraditional subjects, such as

ﬁlters and modeling, are presented here because they are essential to understanding and

implementing control systems in the workplace. The focus of each chapter is to teach how to

use controls to improve a working machine or process.

The wide availability of personal computers and workstations is an important advance for control

system designers. Many of the classical control methods, such as the root locus method, are

graphical rather than analytical. Their creators sought to avoid what was then the overwhelming

number of computations required for analytical methods. Fortunately, these calculations no

longer present a barrier. Virtually every personal computer can execute the calculations required

Control System Design Guide. DOI: 10.1016/B978-0-12-385920-4.00001-1

by analytical methods. With this in mind, the principles and methods presented herein are

essentially analytical, and the arithmetic is meant to be carried out by a computer.

1.1 Visual ModelQ Simulation Environment

Most engineers understand the foundations of control theory. Concepts such as transfer

functions, block diagrams, the s-domain, and Bode plots are familiar to most of us. But how

should working engineers apply these concepts? As in most disciplines, they must develop

intuition, and this requires ﬂuency in the basics. In order to be ﬂuent, you must practice.

When studying control system techniques, ﬁnding equipment to practice on is often difﬁcult.

As a result, designers often rely on computer simulations. To this end, the author developed, as

a companion to this book, Visual ModelQ, a stand-alone, graphical, PC-based simulation

environment. The environment provides time-domain and frequency-domain analysis of

analog and digital control systems. Dozens of Visual ModelQ models were developed for this

book. These models are used extensively in the chapters that follow. Readers can run these

experiments to verify results and then modify parameters and other conditions to experiment

with the concepts of control systems.

Visual ModelQ is written to teach control theory. It makes convenient those activities that are

necessary for studying controls. Control law gains are easy to change. Plots of frequency-

domain response (Bode plots) are run with the press of a button. The models in Visual ModelQ

run continuously, just as real-time controllers do. The measurement equipment runs

independently, so you can change parameters and see the effects immediately.

1.1.1 Installation of Visual ModelQ

Visual ModelQ is available at www.qxdesign.com. The unregistered version is available free of

charge. The unregistered version can execute all the models used in this book. Readers may

elect to register their copies of Visual ModelQ at any time; see www.qxdesign.com for details.

Visual ModelQ runs on PCs using Windows XP and Windows 7. Download the installation

package for Visual ModelQ V7.0 or later; the ﬁles are typically installed to C:\Program

Files\QxDesign, Inc\VisualModelQ7.0. Visual ModelQ installs with both a User’s Manual and

a Reference Manual. After installation, read the User’s Manual. Note that you can access the

Reference Manual by pressing the F1 key. Finally, check www.qxdesign.com from time to time

for updated software.

1.1.2 Errata

Check www.qxdesign.com for errata. It is the author’s intention to regularly update the

Web page as corrections become known.

4 Chapter 1

1.2 The Control System

The general control system, as shown in Figure 1.1, can be divided into the controller and the

machine. The controller can be divided into the control laws and the power converter. The

machine may be a temperature bath, a motor, or, as in the case of a power supply, an inductor/

capacitor circuit. The machine can also be divided into two parts: the plant and the feedback

device (s). The plant receives two types of signals: a controller output from the power converter

and one or more disturbances. Simply put, the goal of the control system is to drive the plant in

response to the command while overcoming disturbances.

1.2.1 The Controller

The controller incorporates both control laws and power conversion. Control laws, such as

proportional-integral-differential (PID) control, are familiar to control engineers. The process

of tuning d setting gains to attain desired performance d amounts to adjusting the parameters

of the control laws. Most controllers let designers adjust gains; the most ﬂexible controllers

allow the designer to modify the control laws themselves. When tuning, most control engineers

focus on attaining a quick, stable command response. However, in some applications, rejecting

disturbances is more important than responding to commands. All control systems should

demonstrate robust performance because even nearly identical machines and processes vary

somewhat from one to the other, and they change over time. Robust operation means control

laws must be designed with enough margin to accommodate reasonable changes in the plant

and power converter.

Virtually all controllers have power converters. The control laws produce information, but

power must be applied to control the plant. The power converter can be driven by any available

power source, including electric, pneumatic, hydraulic, or chemical power.

Control

laws

Power

converter

Plant

Feedback

Sensor

Disturbance

ResponseCommand

Power

Feedback

Controller

Machine

Figure 1.1:

The general control system.

Introduction to Controls 5

1.2.2 The Machine

The machine is made of two parts: the plant and the feedback. The plant is the element or

elements that produce the system response. Plants are generally passive, and they usually

dissipate power. Examples of plants include a heating element and a motor coupled to

its load.

Control systems need feedback because the plant is rarely predictable enough to be controlled

open loop d that is, without feedback. This is because most plants integrate the power

converter output to produce the system response. Voltage is applied to inductors to produce

current; torque is applied to inertia to produce velocity; pressure is applied to produce ﬂuid

ﬂow. In all these cases, the control system cannot control the output variable directly but must

provide power to the machine as physics allows and then monitor the feedback to ensure that

the plant is on track.

1.3 The Controls Engineer

The focal task of many controls engineers is system integration and commissioning. The most

familiar part of this process is tuning the control loops. This process can be intimidating. Often

dozens of parameters must be ﬁne-tuned to ensure that the system meets the speciﬁcation.

Sometimes that speciﬁcation is entirely formal, but more often it is a combination of formal

requirements and know-how gained with years of experience. Usually, experienced engineers

are required to judge when a system is performing well enough to meet the needs of the

application.

For some control systems, each installation may require days or weeks to be correctly

commissioned. In a complex machine such as a rolling mill, that process can take months. Each

section of the machine must be carefully tuned at the site. So even after the design of the

machine is complete, the expertise of a controls engineer is required each time a unit is

installed.

Although most controls engineers focus on installation, their job should begin when the

machine is designed. Many companies fail to take advantage of their controls experts early in

a project; this is short-sighted. A controls engineer may suggest an improved feedback device

or enhancements to a machine that will help overcome a stubborn problem. Ideally, the project

manager will solicit this input early, because changes of this nature are often difﬁcult to make

later.

The controls engineer should also contribute to the selection of the controller. There are many

controls-oriented factors that should be taken into account. Does the controller implement

familiar control laws? For digital controllers, is the processor fast enough for the needs of the

application? Is the complexity/ease-of-use appropriate for the support team and for the

6 Chapter 1

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