Detailed characteristics and advantages of fuzzy PID control system design

In medical testing equipment, maintaining a stable temperature environment that simulates the human body is essential for accurate results. This paper presents a temperature control system based on STM32 as the main controller, with the DRV8834 motor driver chip used to control the Peltier cooler for heating and cooling the heat sink. However, traditional temperature control methods often suffer from inertia-related errors, making it difficult to achieve both high precision and fast response. To address this, a fuzzy adaptive PID control strategy is implemented, allowing online adjustment of PID parameters (Kp, Ki, Kd) to optimize the control pulse output and regulate the drive enable signal. Simulation using Simulink and experimental results demonstrate that the fuzzy PID control system achieves high accuracy and rapid response, effectively meeting the requirements of precise temperature regulation. Temperature control is a critical aspect in many industrial applications, including chemical processing, metallurgy, power engineering, and food manufacturing. In medical devices, it is often necessary to simulate body temperature for component testing. The Peltier device, driven by the DRV8834 DC motor driver, enables both heating and cooling functions, but its temperature response is nonlinear, time-varying, and subject to significant delays. To handle these challenges, the system uses a digital temperature sensor (DS18B20) to continuously monitor and compare the actual temperature with the setpoint. When the temperature is below the target, the system activates the heating module, sending a positive voltage through the DRV8834 to drive the Peltier for heating. Conversely, when the temperature exceeds the setpoint, the DRV8834 outputs a reverse current to activate the cooling function. This process ensures that the system maintains minimal temperature fluctuations and high-precision control. The hardware design of the fuzzy PID temperature control system includes the STM32 microcontroller, DS18B20 temperature sensor, and DRV8834 driver. The STM32 handles complex PID calculations with its high clock speed and rich peripheral resources, while the DRV8834 provides efficient motor control with features like overcurrent protection and sleep mode. The system also incorporates a PWM-based control mechanism to adjust the duty cycle, enabling precise regulation of the Peltier's operation. In the software design, the system initializes the STM32, DS18B20, and display modules before performing fuzzy PID calculations. The error (e) and error change rate (ec) are input into a fuzzy rule table, which then determines the appropriate PID parameter adjustments. These values are defuzzified to produce Kp, Ki, and Kd, which are used to control the PWM output and, in turn, the Peltier’s operation. Fuzzy logic is applied by dividing the input and output variables into seven linguistic levels (NB, NM, NS, Z, PS, PM, PB), with triangular membership functions used for simplicity and efficiency. A set of fuzzy control rules is established to ensure optimal system performance, balancing between quick error elimination and stability. Simulations in Simulink compare the performance of the fuzzy adaptive PID with conventional PID control. The results show that the fuzzy method significantly reduces overshoot and improves response time, achieving faster stabilization with minimal oscillation. The transfer function of the Peltier system is modeled as a first-order inertial system with time delay, and the simulation confirms the superior performance of the fuzzy adaptive approach. In conclusion, this system successfully integrates a low-cost DC motor driver with a fuzzy PID control algorithm to achieve accurate and stable temperature regulation. The use of STM32 allows efficient development and implementation, making the system suitable for various applications such as medical devices and household appliances. Its flexibility and robustness make it a promising solution for real-time temperature control in dynamic environments.

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Standard	IEC; ISO9000; ISO9001; IATF16949
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