Analysis of Digital Control Systems in Modern Industrial Applications

This essay provides a detailed analysis of digital control systems within industrial applications. It begins by outlining the fundamental concepts of digital control, including the conversion of analog signals to digital signals using ADC and DAC, and the role of Direct Digital Control (DDC). The essay explores the merits of digital control, such as improved sensitivity, affordability, and flexibility, while also acknowledging the complexities and costs associated with implementation. The discussion covers the importance of feedback control loops, the use of discrete-time signals, and the techniques employed for system modeling and analysis. The essay concludes that digital control is vital for improving product quality and reducing costs through automation, ultimately enhancing an industry's competitiveness.

Abstract
The essay seeks to determine the implementation and utilization of digital control in
industrial applications. The industrial applications are mostly analog mechanical
systems that process the input to yield output. For more quality products, the industries
have to produce the intended yield based on the design or consumer specifications.
This introduces the idea of digital control that provides either a feedback or feed forward
control system. The control system is digital and therefore there is need to convert the
analog signal to digital signals for processing and back to analog signal for use in the
industrial plants. The essay covers the important sections of the industrial digital control
analyzing the merits and caveat involved in the implementation of the systems. The
essay concludes that in as much as digital control is applied it is very expensive to use
a digital system for production. As a result, the direct digital control systems are
implemented to incorporate the analog sections of the plant and they use ADC and DAC
for conversion of signals.
Abbreviations
DAC- digital to analog converter
ADC- analog to digital converter
DDC- Direct Digital control
Introduction
In every industry, there are inputs and desired outputs. The inputs are fed into a
system that processes them to obtain the intended output. Unfortunately, the systems
are in an environment that exposes them to different kinds of disturbances. To make the
output desirable, there is need to have a feedback control loop that check if the output
obtained is as desired. When it is not, the loop takes back the output to the summer to
eradicate the error until the required output is obtained. There are key factors that are
desired in a control system such as stability, the transient response speed, accuracy,
and robustness. It is possible to model the dynamic systems that are in different
industrial application to design a control system that works for them. There are analog
and digital control systems implemented in the industrial application. The basis for the
type of control system is the continuous-time or discrete-time signal that is applied to
the system. This paper focusses on the discrete time signals that are used for digital
control systems. The digital signal is said to be a sequence of binary numbers to a
digital component such as a microprocessor, shift register, or semiconductor memory.
When a continuous time signal is input, it can be converted to a digital signal by
sampling and quantization (Mircea Cel Batran, 2015).

The analysis model of the continuous-time and the discrete-time systems can be
performed in time domain using differential equations or state space equations or in
frequency domain using the Laplace transfer functions or the S-transfer function. The
techniques implemented in this are the s-plane analysis and the design techniques such
as the Routh-Hurwitz stability criterion, root locus techniques, and bode plots. The
discrete time systems, on the other hand, use the impulse transform function in the Z-
plane such that the z-plane analysis and design techniques employed include the jury
stability test and the modified root locus techniques. These digital controls seek to
achieve the optimal performance in the form of maximum productivity, maximum profit,
minimal costs and utilization of energy. The control systems are regarded to ensure
high performance using the forward and feedback loop that may contain both the analog
and digital signals. They must provide a means for conversion from one form to another
to be used by each subsystem. This introduces the use of DAC and ADC. They are
implemented as shown in the illustration below,
The DAC conversion is performed from the binary number at the input whereby each bit
is properly weighted to obtain the voltage and the values obtained are summed up to
yield the analog output. The ADC performs a two-step process. The analog signal is first
converted to a sampled signal and the sampled signal is quantized to form a sequence
of binary numbers. The process of the ADC is as illustrated in the figure below,

There is a special control system known as the DDC. It has a very good performance
record. the digital control system is a feedback control system where the controller
action is attained numerically by a programmable digital device. The overall system is
considered a hybrid system or a sampled data system as it has a discrete time and
controller and the analog section with actuators, transducers, and analog processes.
This is the typical form of control systems in the common day industries. The illustration
below shows the interaction of the discrete and analog sections in a practical situation,

For the discrete control systems, it is noted that the process parameters and variables
are discrete and that they are changes at discrete moments in time. The changes are
defined in advance by the program of instructions as there are combinational logic
control and sequential control based on state of the system and amount of elapsed time
respectively (Alkhalaf, 2015).
Discussion
Some of the merit of employing digital control in the industrial applications are the
improved sensitivity to errors and other disturbances that result in the unwanted output.
The use of digital components which provide a higher performance and are very
affordable. The control algorithms for the control system can be altered or modified to
suit different needs. Unfortunately, these control systems tend to develop complex math
algorithms such that the users may require experts to modify the control systems if need
be. The use of digital systems provides for reduced overall cost, flexibility in response to
the design changes, immunity to disturbances and other noise factors, and as a result of
their performance they are more suited for use in the modern control systems (Zhang,
et al., 2014).
To design a digital controller, there are several methods involved to enable the
performance of forward or backward approximations. The differential equation of the
controller can be transformed to difference equations where this difference equation is
easily programmed as a control algorithm.
Conclusion
In a nutshell, the industries are more likely to implement the digital control systems in
their plants to ensure that they improve quality of their products. It is very important for
them to yield good products in a timely manner so as to stay above competition. The
implementation of the digital control system also reduces costs for the organization as
less human labor is need to do the manual control. The process is automated and
human resources are removed from hazardous areas (Caswell, 2011)

Works Cited
Alkhalaf, S., 2015. Improvement of Control system Performance by Modification of Time
Delay. International Journal of Advanced Computer Science and Applications, 6(2).
Caswell, J., 2011. Recommende Practices. A survey of Industrial Control Systems
Security, pp. 2-13.
Mircea Cel Batran, 2015. Industrial Control Systems- An Emerging Issue in Romania
National Defense. Journal of PROQUEST SciTech Journals, 18(2), pp. 2-6.
Zhang, X. et al., 2014. Cyberphysical Security of Industrial Control Systems based on
Wireless Sensor Networks. International Journal of Distributed Sensor Networks, Issue
43850, pp. 1-17.