Solar Tracking Fuzzy Control System Using Micro Controller Engineering Essay

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Abstract- our paper focuses on how to improve efficiency of solar cells. A micro controller, sensors and input/output interface are integrated with a tracking mechanism to increase the energy generation efficiency of solar cells. In order to track the sun, improve solar energy efficient light sensitive resistors (LDRs) are used. To achieve optimal solar tracking, a fuzzy algorithm is developed. AVR Microcontroller is used to perform solar tracking.

Index Terms-solar tracking, two-axis tracking, AVR Microcontroller, fuzzy control.


The green energy also called the regeneration energy, has gained much attention nowadays. The green energy can be recycled, such as solar energy, water power, wind power, biomass energy, terrestrial heat, sea waves, morning and evening tides, etc. Among them, solar energy is the most powerful resource that can be used to generate power. So far the efficiency of generating power of solar energy is relatively low. Thus, how to increase the efficiency of generating power of solar energy is very important.

A solar panel receives the most sunlight when it is perpendicular to the sun's rays, but the sunlight direction changes regularly with changing seasons and weather. Currently, most solar panels are fixed, i.e., the solar array has a fixed orientation to the sky and does not turn to follow the sun. To increase the unit area illumination of sunlight on solar panels, we designed a solar tracking electricity generation system. The design mechanism holds the solar panel and allows the panel to perform an approximate 3-dimensional (3-D) hemispheroidal rotation to track the sun's movement during the day and improve the overall electricity generation. This system can achieve the maximum illumination and energy concentration and cut the cost of electricity by requiring fewer solar panels, therefore, it has great significance for research and development.

In this paper, the main goal is to design and implement a solar tracking control system using AVR Microcontroller.

The light sensitive resistors are used. Feedback signals are delivered to the assigned chip through an A/D converter. Then we developed a fuzzy controller and implement it on the controller.


A comparison between the tracking system and the fixed system is made. From the experimental results, the proposed tracking system is verified more efficiently in generating energy than the fixed system.


Our high-performance solar tracking system has multiple functions and uses two motors as the drive source, conducting an approximate hemispheroidal 3-D rotation on the solar array (see Figure 1). The two drive motors are decoupled, i.e., the rotation angle of one motor does not influence that of the other motor, reducing control problems. Additionally, the tracker does not have the problems common to two axis mechanical mechanisms (that one motor has to bear the weight of the other motor). This implementation minimizes the system's power consumption during operation and increases efficiency and the total amount of electricity generated.

The solar tracking system we designed based on the considerations described previously.

The mechanism must support the solar panel and allow the panel to conduct 3-D rotation within a certain amount of space. The array-type mechanism has two advantages:

High photoelectric conversion efficiency- because the flexible panel of the solar tracker array can conduct 3-D rotation, tracking the sun in real time, the system efficiently performs photoelectric conversion and production.

Simple, energy-saving controls-the two rotational dimensions of the array solar tracker are controlled by two independent drive sources. The rotation angles are decoupled and neither one has to bear the weight of the other one. Additionally, the overall movement inertia is dramatically reduced.


We used the AVR Microcontroller to perform solar tracking. The design combines AVR processor with a two-axis motor tracking controller to integrate peripherals such as microprocessor, memory, and I/O. This integration accelerates development while maintaining design flexibility, reduces the circuit board costs with a single-chip solution, and simplifies product testing.


We implemented the system's logic AVR control circuit. Figure 2 shows the tracking control flow chart. The system starts when we turn on the tracking control circuit's power supply switch. The tracking control circuit performs system tracking, energy saving, and system protection, as well as a designed control mode and external anti-interference measures. External interference includes weather influences, such as wind, sand, rain, snow, hail, salt damage (i.e., salt erosion on the mechanism)'.


The tracking sensor is composed of four similar CdS sensors, which are located at the east, west, south, and north to detect the light source intensity in the four orientations. The CdS sensor forms a 45° angle with the light source. At the CdS sensor positions, brackets isolate the light from other orientations to achieve a wide-angle search and quickly determine the sun's position (see Figure 4). The four sensors are divided into two groups, east/west and north/south. In the east/west group, the east and west CdS sensors compare the intensity of received light in the east and west. If the light source intensity received by the sensors is different, the system obtains signals from the sensors' output voltage in the two orientations. The system then determines which sensor received more intensive light based on the sensor output voltage value interpreted by voltage type A/D converter (ADC).

The system drives the step motor towards the orientation of this sensor. If the output values of the two sensors are equal, the output difference is zero and the motor's drive voltage is zero, which means the system has tracked the current position of the sun. The north/south sensors track the position of the sun similarly.


Fig 5.System Architecture

As shown in Figure 5 processor is the control center and integrates our two-axis control chip. The system determines which data is fed back to the using a photography sensor. It conducts the tracking control rule operation to calculate the angle required by the motor and adjusts motor's current angle. It also moves the solar panel to achieve optimal power.

We designed a tracking sensor to determine the orientation of the solar light source. The signals fed back by the sensor form the basis of the controller input. The control design outputs the signals to control the two axis step motor and the solar tracking control system.


The fuzzy sets concept was proposed by Zadeh in 1965. The fuzzy algorithm can make human knowledge into the rule base to control a plant with linguistic descriptions. It relies on expert experience instead of mathematical models. The advantages of fuzzy control include good popularization, high faults tolerance, and suitable for nonlinear control systems.

A fuzzy controller design has four parts, fuzzification, control rule base, fuzzy inference, and defuzzification. The block diagram of the fuzzy control system is shown in Fig. 7.

At first, the sun light illuminates on a light sensitive resistor of the solar tracking device. Then a feedback analog signal will be produced and transformed into a digital signal through an analog/digital converter. When the voltage on the eastward-westward direction or the southward-northward direction is different, the differences will be delivered into the fuzzy controller. Then, the fuzzy controller produces pulses to motor drivers and the motor drivers produce PWM signals to control step motors for tuning desired angles. Note that if the differences of sensors are zero, i.e., the sun is vertical to the solar panel, so the fuzzy controller does not work. Since the sun moves very slow, the fast rotating speed of the solar tacking device is with high speed rotation not necessary. By fuzzy control, some advantages such as necessary. By fuzzy control, some advantages such as reducing consumption power of step motors and fast and reducing consumption power of step motors and fast and smooth fixed position can be achieved. Therefore, the fuzzy control algorithm has enough ability to complete this goal.

Since the corresponding light sensitive resistors can operate independently, it can be seen as independent control. For one motor control, the error of output voltages of corresponding sensors can be set as input variables. The rotation time of the stepping motors for clockwise and counterclockwise are output variables. The membership functions are shown in Fig. 7 and 8. Five fuzzy control rules are used, as shown in the following.

In this paper, product inference is applied for fuzzy inference. The center of gravity method is adopted for

defuzzification to achieve a practical operation value. The defuzzification is shown in (3).

This defuzzification method is implemented by digital circuits.


The paper presents a solar tracking control system. The tracking controller based on the fuzzy algorithm is designed and implemented on AVR controller embedded system. Set up on the solar tracking system, the light sensitivity resistors are used to determine the solar light intensity. The proposed solar tracking system can track the sun light automatically. Thus, the efficiency of solar energy generation can be increased.