𝐏𝐒𝐎 𝐒𝐥𝐢𝐝𝐢𝐧𝐠 𝐌𝐨𝐝𝐞 𝐁𝐚𝐬𝐞𝐝 𝐕𝐚𝐫𝐢𝐚𝐛𝐥𝐞 𝐒𝐭𝐞𝐩 𝐏&𝐎 𝐌𝐏𝐏𝐓 𝐢𝐧 𝐌𝐀𝐓𝐋𝐀𝐁

𝐏𝐒𝐎 𝐒𝐥𝐢𝐝𝐢𝐧𝐠 𝐌𝐨𝐝𝐞 𝐁𝐚𝐬𝐞𝐝 𝐕𝐚𝐫𝐢𝐚𝐛𝐥𝐞 𝐒𝐭𝐞𝐩 𝐏&𝐎 𝐌𝐏𝐏𝐓 𝐢𝐧 𝐌𝐀𝐓𝐋𝐀𝐁

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧

The PSO Sliding Mode Based Variable Step P&O MPPT in MATLAB is a solar PV control model developed in MATLAB/Simulink to improve maximum power extraction from a PV panel under changing irradiance conditions.

This model combines three important techniques:

• Particle Swarm Optimization

• Sliding Mode Control

• Variable Step Size P&O MPPT

The main purpose of this system is to tune the sliding mode controller parameters using PSO and generate an adaptive step size for the P&O MPPT algorithm. This helps the PV system track the maximum power point more effectively during irradiance variation.

𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

This MATLAB/Simulink model includes a 250 W solar PV panel, boost converter, load, P&O MPPT controller, sliding mode controller, and PSO optimization algorithm.

Section	Description
PV Source	Solar PV panel used as the input power source
Converter	Boost converter for voltage conversion
MPPT Method	Variable Step Size P&O MPPT
Controller	Sliding Mode Controller
Optimization	PSO algorithm tunes controller gains
Output	PV power, voltage, current, load voltage, and load current

𝐌𝐚𝐢𝐧 𝐒𝐲𝐬𝐭𝐞𝐦 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬

Parameter	Value / Detail
PV Panel Rating	250 W
Temperature	25°C
Irradiance Levels	1000, 800, 600, 400 W/m²
Irradiance Change Time	Every 0.2 seconds
Simulation Time	0.8 seconds
Discrete Sample Time	1e-06 seconds
Converter Type	Boost Converter
MPPT Type	Variable Step Size P&O

𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬

The system works in a simple step-by-step manner:

• The PV panel receives irradiance and temperature input.

• PV voltage and PV current are measured.

• The measured voltage and current are given to the MPPT controller.

• The Sliding Mode Controller generates the variable step size.

• The P&O MPPT uses this step size to adjust the duty cycle.

• The boost converter receives the duty cycle and controls the PV operating point.

• The PV system tracks maximum power under changing irradiance.

𝐏𝐒𝐎 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐭𝐚𝐢𝐥𝐬

In this model, the PSO algorithm is used to find the best controller gain values for the sliding mode controller.

PSO Parameter	Value
Algorithm	Particle Swarm Optimization
Population Size	4
Maximum Iterations	10
Number of Decision Variables	5
Function Evaluations	Around 40 to 44
Optimized Controller	Sliding Mode Controller

𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞𝐝 𝐂𝐨𝐧𝐭𝐫𝐨𝐥𝐥𝐞𝐫 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬

The PSO algorithm tunes five sliding mode controller parameters.

Optimized Gain	Purpose
Ka	Sliding mode control tuning parameter
Kb	Controller response adjustment
Kc	Control surface tuning
Kd	Dynamic response improvement
Ke	Step size scaling and final adjustment

After PSO execution, the optimized gain values are stored in the model workspace and used by the final Simulink model.

𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲

The control strategy is based on PSO tuned Sliding Mode Control and Variable Step Size P&O MPPT.

𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐅𝐥𝐨𝐰:

• PV voltage and current are measured continuously.

• Sliding mode controller checks the change in PV voltage and current.

• PSO-optimized gains improve the controller behavior.

• The controller generates an adaptive step size.

• The P&O MPPT updates the duty cycle.

• The boost converter adjusts the PV operating condition.

• Maximum power extraction is improved during irradiance changes.

𝐖𝐡𝐲 𝐕𝐚𝐫𝐢𝐚𝐛𝐥𝐞 𝐒𝐭𝐞𝐩 𝐒𝐢𝐳𝐞 𝐈𝐬 𝐔𝐬𝐞𝐟𝐮𝐥

Fixed Step P&O	Variable Step P&O
Uses constant step size	Changes step size automatically
May respond slowly	Faster tracking response
More oscillation near MPP	Reduced oscillation near MPP
Less flexible during irradiance change	Better for changing irradiance
Simple but less adaptive	More intelligent and efficient

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬

The simulation is tested under step-changing irradiance. As irradiance decreases, the PV power and current also decrease. The controller helps the PV system maintain proper MPPT operation.

Time Range	Irradiance	Expected PV Response
0 to 0.2 s	1000 W/m²	Maximum PV power around 250 W
0.2 to 0.4 s	800 W/m²	PV power decreases smoothly
0.4 to 0.6 s	600 W/m²	Current and power reduce further
0.6 to 0.8 s	400 W/m²	Lower power output with stable tracking

𝐎𝐮𝐭𝐩𝐮𝐭 𝐖𝐚𝐯𝐞𝐟𝐨𝐫𝐦𝐬 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬

The model provides clear output results for:

• PV Power

• Boost Converter Power

• PV Voltage

• Boost Converter Voltage

• PV Current

• Boost Converter Current

• Load Power

• Load Voltage

• Load Current

Output	Observation
PV Power	Changes according to irradiance level
PV Voltage	Maintains controlled operating voltage
PV Current	Reduces when irradiance decreases
Boost Converter Voltage	Adjusted according to duty cycle
Boost Converter Power	Follows PV power variation
Load Response	Shows stable power delivery behavior

𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬

• PSO-based optimization of sliding mode controller gains

• Variable step size P&O MPPT for improved tracking

• Sliding Mode Controller for robust control action

• Boost converter based PV power conversion

• PV voltage and current measurement for MPPT control

• Tested under multiple irradiance conditions

• MATLAB/Simulink model with clear waveform analysis

• Suitable for learning advanced MPPT control techniques

𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬

Feature	Benefit
PSO Optimization	Finds suitable controller gain values
Sliding Mode Control	Improves robustness and tracking behavior
Variable Step P&O	Balances fast response and low oscillation
Boost Converter	Helps regulate PV output voltage
MATLAB/Simulink Model	Easy to analyze, test, and modify
Irradiance Variation Test	Shows real-time MPPT tracking performance

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

This model is useful for:

• Solar PV MPPT control studies

• Renewable energy system analysis

• Power electronics converter control

• Optimization-based controller tuning

• Sliding mode controller learning

• MATLAB/Simulink based PV system development

• Advanced MPPT algorithm comparison

𝐖𝐡𝐨 𝐂𝐚𝐧 𝐔𝐬𝐞 𝐓𝐡𝐢𝐬 𝐌𝐨𝐝𝐞𝐥?

User Type	Usefulness
Students	Learn MPPT, PSO, and sliding mode control basics
Researchers	Analyze optimized MPPT controller performance
Engineers	Study PV boost converter control under irradiance change
MATLAB Users	Understand Simulink-based solar PV implementation
Renewable Energy Learners	Explore intelligent PV power tracking methods

𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧

The PSO Sliding Mode Based Variable Step P&O MPPT in MATLAB model provides a smart and effective way to improve solar PV maximum power tracking. By using PSO to tune the sliding mode controller gains, the system generates a better variable step size for the P&O MPPT algorithm.

This helps the PV system respond effectively under changing irradiance conditions and improves the understanding of optimized MPPT control using MATLAB/Simulink.