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This book presents a guideline for EWMA filter design for
industrial wireless networked control system, both theoretically
and practically. The filter's key advantages are simple, effective,
low computational overhead. This book also provides a guideline for
practical implementation of EWMA filter for improving networked
control performance of various process plants. It further discusses
not only the advantages of the filter, but also the limitations and
how to avoid them when implementing the filter from practical point
of view.
This book presents a guideline for EWMA filter design for
industrial wireless networked control system, both theoretically
and practically. The filter's key advantages are simple, effective,
low computational overhead. This book also provides a guideline for
practical implementation of EWMA filter for improving networked
control performance of various process plants. It further discusses
not only the advantages of the filter, but also the limitations and
how to avoid them when implementing the filter from practical point
of view.
Recent advances in wireless technology have led to the emergence of
industry standards such as WirelessHART. These strategies minimise
the need for cumbersome cabling, thereby reducing costs. However,
applying them involves the challenge of handling stochastic network
delays, which can degrade control performance. To address this
problem, commonly used simple PID could be employed. However, PID
suffers from gain range limitations when used in a delayed
environment. Furthermore, model-based controllers are complex and
require exact models of the process and systematic system
identification for implementation. Therefore, to address these
issues, the book proposes control strategies that retain the
simplicity of PID in terms of ease of tuning and structure, while
improving on the performance of the closed-loop system with regard
to stochastic network delays and mismatches. Concretely, it
proposes and discusses three strategies, namely: Setpoint Weighting
(SW), Filtered Predictive PI (FPPI) and Optimal Fuzzy PID. In order
to optimise some of these controllers, two novel hybrid
optimisation algorithms combining the dynamism of the Bacterial
Foraging Algorithm (BFA) and advantages of both the Spiral Dynamic
Algorithm (SDA) and the Accelerated Particle Swarm Optimisation
(APSO) have been used. The strategies proposed here can also be
applied in stochastic control scenarios (not necessarily wireless)
characterised by uncertainties. This book will be useful to
engineers and researchers in both industry and academia. In
industry, it will be particularly useful to research and
development efforts where PID controllers and wireless sensor
networks (WSNs) involving both short and long term stochastic
network delay are employed. Thus, it can be used for real-time
control design in these areas. In the academic setting, the book
will be useful for researchers, undergraduate and graduate students
of instrumentation and control. It can also be used as reference
material for teaching courses on predictive and adaptive controls
and their application.
This book presents a detailed study on fractional-order, set-point,
weighted PID control strategies and the development of
curve-fitting-based approximation techniques for fractional-order
parameters. Furthermore, in all the cases, it includes the
Scilab-based commands and functions for easy implementation and
better understanding, and to appeal to a wide range of readers
working with the software. The presented Scilab-based toolbox is
the first toolbox for fractional-order systems developed in
open-source software. The toolboxes allow time and frequency
domains as well as stability analysis of the fractional-order
systems and controllers. The book also provides real-time examples
of the control of process plants using the developed
fractional-order based PID control strategies and the approximation
techniques. The book is of interest to readers in the areas of
fractional-order controllers, approximation techniques, process
modeling, control, and optimization, both in industry and academia.
In industry, the book is particularly valuable in the areas of
research and development (R&D) as well as areas where PID
controllers suffice - and it should be noted that around 80% of
low-level controllers in industry are PID based. The book is also
useful where conventional PIDs are constrained, such as in
industries where long-term delay and non-linearity are present.
Here it can be used for the design of controllers for real-time
processes. The book is also a valuable teaching and learning
resource for undergraduate and postgraduate students.
Recent advances in wireless technology have led to the emergence of
industry standards such as WirelessHART. These strategies minimise
the need for cumbersome cabling, thereby reducing costs. However,
applying them involves the challenge of handling stochastic network
delays, which can degrade control performance. To address this
problem, commonly used simple PID could be employed. However, PID
suffers from gain range limitations when used in a delayed
environment. Furthermore, model-based controllers are complex and
require exact models of the process and systematic system
identification for implementation. Therefore, to address these
issues, the book proposes control strategies that retain the
simplicity of PID in terms of ease of tuning and structure, while
improving on the performance of the closed-loop system with regard
to stochastic network delays and mismatches. Concretely, it
proposes and discusses three strategies, namely: Setpoint Weighting
(SW), Filtered Predictive PI (FPPI) and Optimal Fuzzy PID. In order
to optimise some of these controllers, two novel hybrid
optimisation algorithms combining the dynamism of the Bacterial
Foraging Algorithm (BFA) and advantages of both the Spiral Dynamic
Algorithm (SDA) and the Accelerated Particle Swarm Optimisation
(APSO) have been used. The strategies proposed here can also be
applied in stochastic control scenarios (not necessarily wireless)
characterised by uncertainties. This book will be useful to
engineers and researchers in both industry and academia. In
industry, it will be particularly useful to research and
development efforts where PID controllers and wireless sensor
networks (WSNs) involving both short and long term stochastic
network delay are employed. Thus, it can be used for real-time
control design in these areas. In the academic setting, the book
will be useful for researchers, undergraduate and graduate students
of instrumentation and control. It can also be used as reference
material for teaching courses on predictive and adaptive controls
and their application.
This book presents a detailed study on fractional-order, set-point,
weighted PID control strategies and the development of
curve-fitting-based approximation techniques for fractional-order
parameters. Furthermore, in all the cases, it includes the
Scilab-based commands and functions for easy implementation and
better understanding, and to appeal to a wide range of readers
working with the software. The presented Scilab-based toolbox is
the first toolbox for fractional-order systems developed in
open-source software. The toolboxes allow time and frequency
domains as well as stability analysis of the fractional-order
systems and controllers. The book also provides real-time examples
of the control of process plants using the developed
fractional-order based PID control strategies and the approximation
techniques. The book is of interest to readers in the areas of
fractional-order controllers, approximation techniques, process
modeling, control, and optimization, both in industry and academia.
In industry, the book is particularly valuable in the areas of
research and development (R&D) as well as areas where PID
controllers suffice - and it should be noted that around 80% of
low-level controllers in industry are PID based. The book is also
useful where conventional PIDs are constrained, such as in
industries where long-term delay and non-linearity are present.
Here it can be used for the design of controllers for real-time
processes. The book is also a valuable teaching and learning
resource for undergraduate and postgraduate students.
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