Design of Feedback Control Systems by Raymond T. Stefani: Chapter 26 Summary
Design of Feedback Control Systems is a textbook for advanced undergraduate and graduate students in electrical and mechanical engineering. It covers the theory and practice of designing feedback control systems using modern analytical tools, especially MATLABÂ®. The fourth edition of this book has been updated to include new topics such as robust control, digital control, and state-space methods.
Chapter 26 of this book focuses on the design of digital control systems using discrete-time methods. It introduces the concepts of sampling, z-transforms, stability analysis, and frequency response for discrete-time systems. It also discusses the design of digital controllers using root locus, frequency response, and state-space techniques. The chapter provides several examples and exercises to illustrate the application of these methods to practical problems.
If you want to learn more about the design of feedback control systems using digital methods, you can read Chapter 26 of Design of Feedback Control Systems by Raymond T. Stefani[^2^]. You can also access the PDF version of this chapter online for free.Some of the advantages of digital control systems over analog ones are:
Digital control systems are more accurate and reliable, as they are less affected by noise, drift, and component variations.
Digital control systems are more flexible and adaptable, as they can be easily modified and updated by changing the software.
Digital control systems are more compatible with modern technologies, such as computers, sensors, and communication networks.
Some of the challenges of digital control systems are:
Digital control systems require sampling and quantization, which introduce errors and limitations in the representation of continuous signals.
Digital control systems have inherent delays and computational constraints, which affect the performance and stability of the system.
Digital control systems need to deal with nonlinearities and uncertainties in the plant and the environment, which require robust and adaptive control techniques.
Sampling and quantization are two processes that are essential for digital control systems. Sampling is the process of converting a continuous-time signal into a discrete-time signal by taking measurements at regular intervals. Quantization is the process of converting a continuous-valued signal into a discrete-valued signal by assigning each measurement to a finite set of levels.
Sampling and quantization introduce errors and limitations in the representation of continuous signals. The sampling error is the difference between the original signal and the sampled signal, which depends on the sampling frequency and the signal bandwidth. The quantization error is the difference between the sampled signal and the quantized signal, which depends on the number of bits and the range of values. These errors affect the accuracy and resolution of the digital control system.
One way to reduce the sampling error is to use a higher sampling frequency, which allows more information to be captured from the original signal. However, this also increases the computational load and the memory requirements of the digital controller. One way to reduce the quantization error is to use more bits, which allows more levels to be assigned to each measurement. However, this also increases the hardware complexity and the communication bandwidth of the digital controller. 061ffe29dd