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1. Wireless Technologies for Transmission of Data
Wireless data transmission involves the exchange of information between devices
without the use of physical cables, relying on electromagnetic waves for communication. This
process employs modulation techniques to encode data onto carrier waves. Technologies like
radio
frequency
(RF)
communication,
microwave
communication,
and
infrared
communication leverage different parts of the electromagnetic spectrum for diverse
applications. The essential components include a transmitter converting data into a suitable
format, a channel for signal propagation, and a receiver to demodulate and process the
received signal. Challenges in wireless transmission include potential interference, security
concerns, and considerations for signal strength and range. The main wireless technologies
for transmission of data are as follows:
1. Zigbee
2. Z-wave
3. Bluetooth
4. WIFI
1. Zigbee Technology:
Zigbee is a wireless communication standard designed for short-range, low-power,
and low-data-rate communication between devices. It is commonly used in applications such
as home automation, industrial automation, and healthcare monitoring.
1. Network Topology:
- Zigbee uses a mesh network topology, allowing devices to communicate with each
other through intermediate nodes.
2. Low Power Consumption:
- Zigbee is designed for low-power consumption, enabling battery-operated devices to
operate for extended periods.
3. Frequency Bands:
- Zigbee operates in the 2.4 GHz frequency band, divided into 16 channels.
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4. Security:
- Zigbee incorporates security features, including encryption and authentication, to
ensure secure communication.
5. Data Rate:
- Zigbee supports low data rates suitable for applications with modest communication
requirements.
6. Applications:
- Zigbee is widely used in various applications, such as smart homes, industrial
automation, and healthcare.
7. Interoperability:
- Zigbee Alliance ensures interoperability by defining standards, leading to compatibility
among Zigbee devices.
2. Z-Wave Technology:
Z-Wave is a wireless communication protocol designed primarily for home automation
applications. It operates in the sub-1GHz frequency range and is known for its low power
consumption, long-range capabilities, and interoperability among different devices.
1. Frequency and Range:
- Z-Wave operates in the sub-1GHz frequency band, typically around 900 MHz, which
provides better penetration through walls and longer communication range.
2. Mesh Networking:
- Z-Wave devices form a mesh network, allowing them to relay messages and extend the
network's coverage.
3. Interoperability:
- Z-Wave Alliance certifies devices to ensure interoperability, making it easier for
consumers to build a smart home ecosystem with various Z-Wave-compatible devices.
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4. Security Features:
- Z-Wave incorporates security measures such as AES-128 encryption to protect
communication between devices.
5. Topology and Routing:
- Z-Wave networks typically use a star topology, with each device communicating directly
with a central controller. Some variations allow for more complex network topologies.
6. Energy Efficiency:
- Z-Wave devices are designed for low power consumption, enabling battery-operated
devices to operate for extended periods.
7. Applications:
- Z-Wave is commonly used in home automation for applications like smart lighting,
security systems, climate control, etc.
3. Bluetooth Technology:
Bluetooth is a short-range wireless communication technology designed for exchanging
data between devices over short distances. It operates in the 2.4 GHz frequency band and is
commonly used for connecting devices such as smartphones, headphones, and IoT devices.
1. Frequency Band:
- Bluetooth operates in the 2.4 GHz ISM (Industrial, Scientific, and Medical) band, which
is a globally available frequency band for industrial, scientific, and medical use.
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2. Bluetooth Versions:
- Bluetooth has gone through several versions, with each version introducing
improvements in terms of data rate, range, and power consumption. For example,
Bluetooth 5 introduced features like longer range and higher data throughput.
3. Bluetooth Profiles:
- Bluetooth profiles define how different Bluetooth devices communicate and what kind
of operations they can perform. Common profiles include Hands-Free Profile (HFP),
Advanced Audio Distribution Profile (A2DP), and Human Interface Device (HID).
4. Pairing and Security:
- Bluetooth devices use pairing mechanisms for establishing a secure connection. Security
features include encryption and authentication.
5. Low Energy (Bluetooth LE):
- Bluetooth Low Energy (LE) is a power-efficient version of Bluetooth designed for lowpower devices like fitness trackers and IoT sensors.
6. Mesh Networking:
- Bluetooth Mesh enables devices to create large-scale networks suitable for smart home
and industrial applications.
7. Interference and Coexistence:
- There are interference issues and coexistence challenges in Bluetooth networks,
especially in scenarios with multiple devices.
8. Applications:
- Bluetooth is extensively used in various applications, including audio streaming, data
transfer, location-based services, and IoT.
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4. Wi-Fi Technology:
Wi-Fi (Wireless Fidelity) is a popular wireless communication technology widely used for
local area networking and internet access. It operates in the 2.4 GHz and 5 GHz frequency
bands and is known for its high data rates and versatility. Here's an overview of Wi-Fi
technology, along with references to relevant research papers:
1. Frequency Bands:
- Wi-Fi operates in the 2.4 GHz and 5 GHz frequency bands, providing different channels
for communication.
2. Standardization:
- The IEEE 802.11 family of standards defines Wi-Fi specifications. Standards like
802.11b/g/n operate in the 2.4 GHz band, while 802.11a/n/ac/ax operate in the 5 GHz
band.
3. Modulation Techniques:
- Wi-Fi uses various modulation techniques like Quadrature Amplitude Modulation
(QAM) to transmit data at different rates.
4. Multiple Access and Collision Avoidance:
- Wi-Fi employs Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) to
manage access to the wireless medium.
5. Security Protocols:
- Wi-Fi networks use security protocols like WEP, WPA, and WPA2/WPA3 to protect data
during transmission.
6. Mesh Networking:
- Wi-Fi mesh networks enable devices to communicate with each other directly, forming
a self-healing and scalable network.
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7.Quality of Service (QoS):
- Wi-Fi supports QoS mechanisms to prioritize different types of traffic, ensuring a better
user experience for real-time applications.
8. Beamforming and MIMO:
- Multiple Input Multiple Output (MIMO) and beamforming technologies enhance Wi-Fi
performance by improving signal strength and reliability.
9. IoT and Wi-Fi:
- Wi-Fi is increasingly used in IoT applications.
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2. PID CONTROLLER
A Proportional-Integral-Derivative (PID) controller serves as a feedback mechanism
extensively employed in industrial control systems. This controller calculates an error value
by comparing a measured process variable with a desired setpoint and aims to minimize this
error by adjusting the process through manipulation of a variable. The PID algorithm involves
three constant parameters, often referred to as three-term control: proportional (P), integral
(I), and derivative (D) values. In simple terms, these parameters can be associated with time,
where P addresses the present error, I handles the accumulation of past errors, and D predicts
future errors based on the current rate of change. The combined and weighted sum of these
three actions is utilized to modify the process through a control element, such as adjusting
the position of a control valve, a damper, or the power supplied to a heating element.
2.1 PID Controller Theory
The PID control scheme derives its name from the three correcting terms—
proportional, integral, and derivative, whose sum constitutes the manipulated variable (MV).
The output of the PID controller, denoted as 𝑢(𝑡), results from the combination of these three
terms. Controller manufacturers organize these terms into different algorithms or controller
structures, namely Interactive, Noninteractive, and Parallel algorithms. In some cases,
controller software configuration options enable users to select between these algorithms.
The PID algorithms encompass distinct approaches to adjusting the control output, offering
flexibility and adaptability in various control scenarios.
2.1.1
Interactive Algorithm
𝑢(𝑡) = 𝐾c [𝑒(𝑡) + 1 /𝑇i ∫0t 𝑒(𝜏)𝑑𝜏 ] × [1 + 𝑇d *(𝑑 /𝑑𝑡 𝑒(𝑡))]
Fig 2.1.1: Interactive Algorithm
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2.1.2 Noninteractive Algorithm
𝑢(𝑡) = 𝐾c [𝑒(𝑡) + 1 /𝑇i*∫0t 𝑒(𝜏)𝑑𝜏 + 𝑇d *(𝑑 /𝑑𝑡 𝑒(𝑡))]
Fig 2.1.2: Non Interactive Algorithm
2.1.3 Parallel Algorithm
( )=
p
( )+
i
∫ 0t ( )
Fig 2.1.3: Parallel Algorithm
Where,
𝐾𝑝 = 𝐾𝑐 : 𝑃𝑟𝑜𝑝𝑜𝑡𝑖𝑜𝑛𝑎𝑙 𝐺𝑎𝑖𝑛
𝐾𝑖 = 𝐾𝑐 / 𝑇𝑖 : 𝐼𝑛𝑡𝑒𝑔𝑟𝑎𝑙 𝐺𝑎𝑖𝑛
𝐾𝑑 = 𝐾𝑐 *𝑇𝑑:𝐷𝑒𝑟𝑖𝑣𝑎𝑡𝑖𝑣𝑒 𝐺𝑎𝑖𝑛
𝑒(𝑡) = 𝑟(𝑡) − 𝑦(𝑡)
+
d
(
( ))
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2.2 Proportional Term
The proportional term in a PID controller generates an output value proportional to
the current error. This response is modulated by multiplying the error by a constant Kp,
referred to as the proportional gain constant. The proportional term equation is given by
Pout = 𝐾p *𝑒(𝑡)
A higher proportional gain leads to a more substantial change in the output for a given error
alteration. However, an excessively high gain can induce system instability. Conversely, a
lower gain results in a less responsive controller with a smaller output response to a
significant input error. If the gain is too low, the control action might be insufficient when
addressing system disturbances. Tuning practices emphasize that the proportional term
should contribute significantly to the overall output change for effective control system
performance.
Fig 2.2: The effect of add 𝐾𝑝 (𝐾𝑖 , 𝑎𝑛𝑑 𝐾𝑑) held constant
2.3 Integral Term
The integral term in a PID controller contributes in proportion to both the magnitude
of the error and the duration of the error. This term involves the integral of the instantaneous
error over time, representing the accumulated offset that should have been corrected earlier.
The accumulated error is then multiplied by the integral gain 𝐾𝑖 and added to the controller
output. Mathematically, the integral output is given by
𝐼out = 𝐾i ∫ 𝑒(𝜏)𝑑𝜏 from 0 to 𝑡.
The integral term serves to accelerate the process towards the set-point, effectively
eliminating any residual steady-state error associated with a pure proportional controller.
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However, because the integral term responds to accumulated errors from the past, it can lead
to the present value overshooting the set-point value.
Fig 2.3: The effect of add 𝐾i (𝐾p, 𝑎𝑛𝑑 𝐾d) held constant
2.4 Derivative Term
The derivative term in a PID controller is computed by determining the slope of the process
error over time and multiplying this rate of change by the derivative gain 𝐾d. Mathematically,
the derivative output is given by
𝐷out = 𝐾d (𝑑/𝑑𝑡)𝑒(𝑡).
The magnitude of the derivative gain, 𝐾d, determines the contribution of the derivative term
to the overall control action. The derivative action is advantageous in predicting system
behaviour, leading to improvements in settling time and system stability. However, since an
ideal derivative is not causal, PID controller implementations typically incorporate additional
low-pass filtering for the derivative term to limit high-frequency gain and mitigate noise in
the system.
Fig 2.4: The effect of add 𝐾d (𝐾p, 𝑎𝑛𝑑 𝐾i) held constant
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2.5 Ziegler-Nichols PID Tuning Method
Fig 2.5: The Control system with Gain 𝐾p
The Ziegler-Nichols closed-loop tuning method utilizes the critical gain value, 𝐾𝑐𝑟,
and the critical period of oscillation, 𝑃𝑐𝑟, to determine the proportional gain 𝐾𝑝 for tuning
PID controllers. This method, although simple, provides a starting point for controller tuning
and can be refined for better approximations. The process involves determining the ultimate
gain value, 𝐾𝑐𝑟, by finding the proportional-only gain that induces indefinite oscillation at
steady state, with integral (I) and derivative (D) gains set to zero. The critical period, 𝑃𝑐𝑟,
represents the time required for one complete oscillation at steady state. These two
parameters, 𝐾𝑐𝑟 and 𝑃𝑐𝑟, are crucial in finding the loop-tuning constants (P, PI, or PID) for
the controller. The Ziegler-Nichols closed-loop tuning method is particularly effective for
systems with feedback, emphasizing robustness and optimization of the proportional gain for
improved controller performance. It is important to note that this method is limited to
processes that cannot operate in an open-loop environment.
Tuning Procedure:
1. Remove Integral and Derivative Action:
- Disable integral action by setting integral time (𝑇𝑖) to ∞ or its largest permissible value.
- Set the derivative controller (𝑇𝑑) to zero, eliminating derivative action.
2. Create a Small Disturbance:
- Introduce a minor disturbance into the loop by altering the setpoint.
- Adjust the proportional gain (𝐾𝑝), either increasing or decreasing it, until oscillations
exhibit a constant amplitude.
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3. Record Key Values:
- Note the gain value at which oscillations have a consistent amplitude (𝐾𝑐𝑟).
- Record the period of oscillation (𝑃𝑐𝑟).
4. Apply Ziegler-Nichols Equations:
- Plug the recorded values (𝐾𝑐𝑟 and 𝑃𝑐𝑟) into the Ziegler-Nichols closed-loop equations.
- Determine the necessary settings for the controller based on the equations, providing the
proportional gain (𝐾𝑝) and potentially other tuning parameters.
Fig 2.5.1: System tuned using the Ziegler-Nichols closed-loop tuning method
Table 2.5: Closed-Loop Calculation of (𝐾𝑝. 𝑇𝑖 . 𝑇𝑑)
The PID controller tuned by this method gives
Gc(s)= Kp[i+1/Ti * s +Td *s]
= 0.6 Kcr (1+i/0.5 Pcr *s +0.125 Pcr *s)
= 0.075 Kcr * Pcr (s+4/Pcr)2/s
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2.6 PID Controller MATLAB Simulation
Fig 2.6.1: Simulation
Gs=6/(s+1)(s+2)(s+3)
Kp= 6
Ki=6.33
Kd=1.422
Fig 2.6.2: Simulation result
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