Proportional Integral Derivative Method Research Articles

Synchronization of a 4D Hyperchaotic System with Active Disturbance Rejection Control and Its Optimization via Particle Swarm Algorithm

In this paper, a synchronization study is proposed by using a 4D hyperchaotic system model to be used in secure data transfer applications. Active Disturbance Rejection Control (ADRC) method is used for synchronization process. To prove the success of ADRC method, it is compared with Proportional-Integral-Derivative (PID) control method. The coefficients of both control methods are optimized with Particle Swarm Optimization (PSO) algorithm. Synchronization system is modelled and tested in Matlab/Simulink environment. ADRC and PID methods are tested in simulation environment for the cases without disturbance and under disturbance. It can be seen from the test results that the ADRC method managed to keep the system synchronous without being affected by any disturbances. On the other hand, it is clearly seen that the PID method cannot maintain the synchronization of system under disturbance effects.

Development of an IoT-Based Egg Incubator with PID Control System and Web Application

The rapid development of technology significantly impacts various aspects of life, including the field of livestock farming. The advancement of technology is expected to enhance the rate and effectiveness of production, particularly in the hatching of chicken eggs or chick breeding. The existing technology relies on manual on/off systems and manual monitoring, hindering successful egg-hatching rates and percentages. Therefore, this research aims to explain the development of an automated egg incubator using a Proportional Integral Derivative (PID) control system with hypertuning parameters, as well as temperature and humidity monitoring, along with a protection system based on voltage sensors, all integrated with the Internet of Things (IoT). The PID control is employed to regulate the temperature of the egg incubator, ensuring stability according to the predetermined set point temperature. The IoT system in this study comprises an ESP32 node as a microcontroller connected to a sensor, using Firebase and User app for monitoring the egg incubator. The study employed PID control with parameter values Kp=10, Ki=3, and Kd=8. The research yielded time-efficient egg incubation and prevention of turning delays. The DHT21 sensor achieved a 90% success rate in detecting room temperature (38°C) and humidity (77%-84%) within the incubator, while PID control effectively maintained the target temperature. The ACS712 sensor accurately detected current in the heater, power supply, and motor. The Kodular application can display sensor readings. The future implication is developing a more adaptive PID method toward changes and nonlinear dynamics.

IMPLEMENTASI SISTEM KONTROL PENGGERAK MOTOR STEPPER PADA PROSES MOLDING MICROPLASTIC BERBASIS PID MENGGUNAKAN PLC DAN ARDUINO

The current industry has entered an era where every production process incorporates automation and data exchange in its manufacturing. This era is known as Industry 4.0. Industry 4.0 has had a significant impact on various industrial sectors, particularly in the production of plastic goods using techniques such as injection molding. This process is capable of producing more precise products. In the injection molding process, a well-controlled system is needed to guide plastic pellets according to the intended mold design, utilizing actuators like stepper motors. This research aims to apply the PID (Proportional-Integral-Derivative) method to control stepper motors in microplastic molding processes. The proposed system has been successfully implemented and can produce products according to the planned specifications. The most suitable PID parameter values for controlling the stepper motor are Kp = 14, Ki = 0.007, and Kd = 7000. Changing the setpoint value from 2500 to 2700 has an impact on the molding results, with the best results achieved at a setpoint value of 2700. A setpoint value of 2700 ensures that the mold and nozzle are in the correct, tight position, allowing the molding process to proceed smoothly in line with the provided design.

KONTROL FREKUENSI BEBAN MENGGUNAKAN METODE ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) PADA SISTEM HYBRID WIND MIKROHIDRO DAN DIESEL

This study aims to analyze and compare the performance of three frequency load controller methods in a hybrid generator consisting of three types of energy generation, namely microhydro, diesel and wind. The controller methods being compared are the PID (Proportional Integral Derivative) method, ANFIS (Adaptive Neuro-Fuzzy Inference System), and Fuzzy. This analysis was carried out to improve the efficiency and stability of the hybrid generating system by optimizing the frequency load controller. Frequency instability can occur due to load fluctuations, changes in environmental conditions, or system disturbances. Therefore, the use of an effective and adaptive controller method is very important in maintaining the stability and reliability of the hybrid generator system. The analytical method used in this study involved data collection and computer modeling. The required data includes information on load variations, energy production, and environmental conditions. Furthermore, the PID, ANFIS, and Fuzzy methods are applied to the data to build a frequency load controller model. The results of the analysis show that the three controller methods have different performance in maintaining frequency stability in the hybrid generator system. The PID method provides a fast and accurate response to load fluctuations, but is less adaptive to environmental changes. While the ANFIS method is able to adapt well to changes in system conditions, it requires time for model training. Fuzzy methods can provide control that is more adaptive and tolerant to disturbances, but may require more complex tuning. However, in general, the use of intelligent controller methods such as ANFIS and Fuzzy can improve the performance of hybrid generators by producing more adaptive and stable controls. This research has important implications for the development of more efficient and reliable hybrid power systems. By choosing the right controller method, hybrid power plants can provide energy in a more stable and environmentally friendly manner, and reduce dependence on limited fossil resources. Therefore, this research can make a significant contribution to the development of renewable energy and sustainable development in the future.

Penerapan Metode Fuzzy Logic-PID Sebagai Kontrol Gerak Robot Berkaki Enam (Hexapod)

Robotics technology is currently developing rapidly and has become one of the sophistications that are relied upon by every country, one of which is Indonesia. One of the activities for the development of robotics technology in Indonesia is the Indonesian Robot Contest (KRI). KRI was held as an event for students' creativity in designing robots. One of the divisions contested at KRI is the Indonesian Search and Rescue Robot Contest (KRSRI) division. In the KRSRI division, it is required to make a legged robot that can navigate the motion of walking in the competition area and pass obstacles on the track. Of course, a navigation motion control system is needed that can regulate the movement of the legged robot's steps properly, so that the robot can pass the path in the arena. In this study, the answer to this problem is the application of legged robot navigation motion control using the Fuzzy Logic-PID method. The Fuzzy Logic-PID method is a combination of two methods between the Fuzzy Logic Controller method and the Proportional Integral Derivative (PID) control method. The Fuzzy method’s role is to produce constant values ??P, I, and D based on the error value and the incoming error delta. Furthermore, the resulting constant value is used in the calculation of the PID control. From the experimental data, the Fuzzy method has been able to produce a PID constant value and the PID method can also be applied to regulate the robot's motion steps. The test results on trials using obstacles and without obstacles were successful, except for uphill obstacles with a success percentage of 60% successfully passing incline obstacles and 40% failing to pass uphill obstacles.

Optimal tuning proportional integral derivative controller on direct current motor using reptile search algorithm

<span lang="EN-US">This paper presents the reptile search algorithm (RSA) method to optimize the proportional integral derivative (PID) parameters on direct current (DC) motors. RSA was adopted from crocodile hunting behavior. Crocodile behavior is modeled in two important steps: surrounding and attacking prey. The RSA method was applied using twenty-three classical test functions. The search method of the proposed RSA method with other existing algorithms such as particle swarm optimization (PSO), and differential evolution (DE). Integral multiplied by absolute error (ITAE) and integral of time multiplied squared error (ITSE) were used as comparisons in measuring the performance of the RSA method. The results show that the proposed method, namely RSA, has better efficiency. Optimization of PID parameters with RSA on DC motor control shows superior performance. From the experiment, the ITSE average value of the RSA method is 4.17% better than the conventional PID method.</span>

433Mhz based Robot using PID (Proportional Integral Derivative) for Precise Facing Direction

This research endeavor aims to evaluate the effectiveness of the robot's direction control system by employing PID (Proportional Integral Derivative) output and utilizing wireless communication LoRa E32 433MHz. The experimental robot used in this study was a tank model robot equipped with 4 channels of control. LoRa was implemented in the robot control system, in conjunction with an Android control application, through serial data communication. The LoRa E32 module system was selected based on its established reliability in long-range communication applications. However, encountered challenges included the sluggishness of data transmission when using LoRa for transferring control data and the decreased performance of the robot under Non-Line of Sight conditions. To overcome these challenges, the PID method was employed to generate control data for the robot, thereby minimizing the error associated with controlling its movements. The PID system utilized feedback from a compass sensor (HMC5883L) to evaluate the setpoint data transmitted by the user, employing Kp, Ki, and Kd in calculations to enable smooth movements toward the setpoint. The findings of this study regarding the direct control of the robot using wireless LoRa E32 communication demonstrated an error range of 0.6% to 13.34%. A trial-and-error approach for control variables determined the optimal values for Kp, Ki, and Kd as 10, 0.1, and 1.5, respectively. Future investigations can integrate additional methodologies to precisely and accurately determine the PID constants (Kp, Ki, and Kd) mathematically.

A novel PID type iterative learning controller optimized by two‐dimensional infinite horizon linear quadratic iterative learning control for batch processes

AbstractAlthough a proportional integral derivative type iterative learning control (PIDILC) scheme can achieve good performance, its application is limited by open‐loop structure, parameter tuning, and initial state. In this paper, a novel PIDILC optimized by two‐dimensional infinite horizon linear quadratic regulator (PIDILC‐2D‐IHLQR) is proposed. First, by synthesizing the advantage of the conventional PIDILC method and proportional integral derivative (PID) strategy, a novel closed‐loop PIDILC scheme is obtained. Then, a novel two‐dimensional infinite horizon linear quadratic regulator (2D‐IHLQR) is developed to optimize the parameters of the PIDILC strategy. The limitations of parameter tuning and initial state are solved by this PIDILC‐2D‐IHLQR method. Therefore, the proposed method not only solves the aforementioned limitations but also inherits the advantages of PIDILC algorithm, PID method, and the novel 2D‐IHLQR scheme. Moreover, a stability condition is given based on Lyapunov theory and it can help judge whether the selection of control parameters meets the stability condition. The effectiveness of the proposed method is demonstrated by the case study on an injection modelling process.

Implementation of Automatic DC Motor Braking PID Control System on (Disc Brakes)

The vital role of an automated braking system in ensuring the safety of motorized vehicles and their passengers cannot be overstated. It simplifies the braking process during driving, enhancing control and reducing the chances of accidents. This study is centered on the design of an automatic braking device for DC motors utilizing disc brakes. The instrument employed in this study was designed to accelerate the vehicle in two primary scenarios - before the collision with an obstacle and upon crossing the safety threshold. It achieves this by implementing the Proportional Integral Derivative (PID) control method. A significant part of this system comprises ultrasonic sensors, used for detecting the distance to obstructions, and rotary encoder sensors, which are utilized to measure the motor's rotational speed. These distance and speed readings serve as essential reference points for the braking process. The system is engineered to initiate braking when the distance value equals or falls below 60cm or when the speed surpasses 8000rpm. During such events, the disc brake is activated to reduce the motor's rotary motion. The suppression of the disc brake lever is executed pneumatically, informed by the sensor readings. Applying the PID method to the automatic braking system improved braking outcomes compared to a system without the PID method. This was proven by more effective braking results when the sensors detected specific distance and speed values. Numerous PID tuning tests achieved optimal results with K_p = 5, K_i = 1, and K_d = 3. These values can be integrated into automatic braking systems for improved performance. The PID method yielded more responsive braking outcomes when applied in distance testing. On the contrary, the braking results were largely unchanged in the absence of PID. Regarding speed testing, the PID method significantly improved the slowing down of the motor speed when it exceeded the maximum speed limit of 8000 rpm. This eliminates the possibility of sudden braking, thus maintaining the system within a safe threshold. The average time taken by the system to apply braking was 01.09 seconds, an indication of its quick responsiveness. This research is a valuable addition to control science, applying the PID control method to automatic DC motor braking. It provides valuable insights and concrete applications of PID control to complex mechatronic systems. It is also noteworthy for its development and optimization of suitable PID parameters to achieve responsive and stable braking. The study, therefore, offers a profound understanding of how PID control can be employed to manage braking systems on automatic DC motors, thereby advancing knowledge and application of control in control science and mechatronics.

Improving The Quality of Coffee Beans Using Electronic Fermenters To Increase The Economic Value Of Coffee

Coffee is one of the most popular commodities, including in the international market. The process in developing the Robusta coffee commodity and increasing its economic value is to make fermented coffee into wine coffee. Coffee wine fermentation is traditionally placed in a closed place or container without temperature control and pH value checking. This study aims to create a fermentor system that can control temperature, detect pressure in the fermentor and determine the pH value in the fermentation process. Temperature control in the fermenter uses the PID (Proportional Integral Derivative) method. The PID controller determines the setpoint of 31oC. The actuators of the system are a series of thermocouples and TRIAC which control the light of an incandescent lamp which is a source of heat to raise the temperature in the fermenter. The fermentation process is complete when the pH value has touched 4. The results of this study produced fermented coffee which had a pH value of 4 using a fermenter for approximately 4 weeks, while for the traditional method without temperature control it took approximately 6 weeks. Testing the caffeine content in coffee before fermentation was 2.43% and the caffeine content after fermentation was 2.00%.

Online PID Tuning Strategy for Hydraulic Servo Control Systems via SAC-Based Deep Reinforcement Learning

Proportional–integral–derivative (PID) control is the most common control technique used in hydraulic servo control systems. However, the nonlinearity and uncertainty of the hydraulic system make it challenging for PID control to achieve high-precision control. This paper proposes a novel control strategy that combines the soft actor-critic (SAC) reinforcement learning algorithm with the PID method to address this issue. The proposed control strategy consists of an upper-level controller based on the SAC algorithm and a lower-level controller based on the PID control method. The upper-level controller continuously tunes the control parameters of the lower-level controller based on the tracking error and system status. The lower-level controller performs real-time control for the hydraulic servo system with a control frequency 10 times higher than the upper controllers. Simulation experiments demonstrate that the proposed SAC-PID control strategy can effectively address disturbances and achieve high precision control for hydraulic servo control systems in uncertain working conditions compared with PID and fuzzy PID control methods. Therefore, the proposed control strategy offers a promising approach to improving the tracking performance of hydraulic servo systems.

A novel two‐dimensional PID controller design using two‐dimensional model predictive iterative learning control optimization for batch processes

AbstractIt is known that the key indicators of batch processes are controlled by conventional proportional–integral–derivative (PID) strategies from the view of one‐dimensional (1D) framework. Under such conditions, the information among batches cannot be used sufficiently; meanwhile, the repetitive disturbances also cannot be handled well. In order to deal with such situations, a novel two‐dimensional PID controller optimized by two‐dimensional model predictive iterative learning control (2D‐PID‐MPILC) is proposed. The contributions of this paper can be summarized as follows. First, a novel two‐dimensional PID (2D‐PID) controller is developed by combining the advantages of a PID‐type iterative learning control (PIDILC) strategy and the conventional PID method. This novel 2D‐PID controller overcomes the aforementioned disadvantages and extends the conventional PID algorithm from one‐dimension to two‐dimensions. Second, the tuning guidelines of the presented 2D‐PID controller are obtained from the two‐dimensional model predictive control iterative control (2D‐MPILC) method. Thus, the proposed approach inherits the advantages of both PID control, PIDILC strategy, and 2D‐MPILC scheme. The superiority of the proposed method is verified by the case study on the injection modelling process.

An adaptive control method for the covers on the south roof of Chinese solar greenhouses: A case study of insulation blankets

The Chinese solar greenhouse (CSG) enables farming activities in colder conditions and extends the harvest time. It is a crucial component of Chinese agricultural facilities. Rolling/unrolling the cover on the south roof is critical for modifying the greenhouse environment and improving the production efficiency of CSGs. However, since the structure of CSGs is constantly being updated, the existing winding equipment is inadequate because it causes deformation of covers. This study used as insulation blankets an example to proposed an adaptive control method of the rolling cover of CSGs. Deformation and force analysis showed that the fundamental reason for the deformation of the insulation blanket and the winding mechanism was the uneven load distribution in the length direction. A segmented winding mechanism and multi-motor scheme were used to reduce the deformation of the insulation blanket. A fuzzy proportional–integral–derivative (PID) control algorithm was developed to adjust the speed of the slave motors adaptively to roll/unroll the insulation blanket. The simulation results showed that the shorter winding mechanism resulted in lower torsional deformation. Experiments using a scale model demonstrated that the proposed double-motor scheme and fuzzy PID control method provided good performance for rolling/unrolling the insulation blanket. The double-motor scheme can significantly improve the operation efficiency of rolling insulation blankets. The running time of the double-motor scheme was 12.81% lower than that of the single-motor scheme, the average absolute position deviation was 41.95% lower, and the average absolute standard deviation was 44.51% lower. The proposed fuzzy PID control strategies enable the closed-loop control of the deceleration motor and the adjustment of the displacement deviation to reduce the deformation of the insulation blanket according to the feedback received from the slave motor. Unlike the conventional PID control, the fuzzy PID control automatically adjusts the system parameters to eliminate the system error. The control accuracy and stability of the fuzzy PID method have reached a good level, and the applicability is better than that of the conventional PID method. In the scale model experiments, the average position deviation remained within ±1 mm, and the average standard deviation was 1.32 mm. The proposed adaptive control method for the cover on the south roof of CSGs is highly suitable for practical applications. The study also provides application examples and theoretical references for the automation of rolling covers in greenhouses worldwide.

Composite synchronization of three inductor motors with a circular distribution by a fuzzy proportional–integral–derivative method in a vibration system

Abstract. In this article, the composite synchronization of three inductor motors with a circular distribution by a fuzzy PID (proportional–integral–derivative) method in a vibration system is investigated. The composite synchronization motion is comprised of self-synchronization and controlled synchronization motions. In the self-synchronization section, the electromechanical coupling dynamical model of the vibration system is established by introducing an inductor motor model into the dynamic model. The responses of the vibrating system are calculated, and the synchronous condition and stability criterion are both derived. With the controlled synchronization section, a master–slave controlling strategy and fuzzy PID method are applied on the controlling model. The stability of the control system is proved by the Lyapunov stability theory. A series of simulations are employed to demonstrate the practicability of the designed method. Finally, some experiments are conducted to verify the effectiveness of the proposed control method in practical application. The proposed control method exhibits a superior ability to satisfy the control of multiple motors, to be accurate in targeting the rotational speed arrival, and to be strongly robust against uncertainties and disturbances. The composite synchronization theory introduces a novel concept to design and develop types of vibration equipment.

Mecanum 4 Omni Wheel Directional Robot Design System Using PID Method

Robot or Artificial Intelligence (AI) can be interpreted as a machine with some computer intelligence and controlled by a computer, and has physical abilities like humans. One of the drives of robots that is often used is a DC motor, a DC motor is a motor with an electronic device that converts electrical energy into kinetic energy or motion. However, DC motors often experience a decrease due to the existing load, so that the speed becomes not constant, so it is necessary to design a controller. The controller used is Proportional Integral Derivative (PID). In the PID there are several parameters such as , , and which are selected or determined so that the plant characteristics match the desired criteria. The general parameters are rise-time, settling-time, maximum, overshoot, and steady-state error for a given input. From the results of the DC motor speed control test using the PID method which was carried out by trial and error testing of the four DC motors, the best PID value was obtained with ; ; ; and with the Rise Time system message: 14.7452; Overshoots: 0.6667; Settling Time: 52.0100; Undershot: 0; Settling Min: 136; Peaks: 151; Settling Max : 151; and Peak Time: 65.

Research on active disturbance rejection control technique for underwater welding robot based on model compensation

PurposeAn active disturbance rejection controller (ADRC) based on model compensation is proposed in this paper. The method should first be taken a nominal model of the robot to compensate. Subsequently, the uncertain external disturbance is estimated and compensated is used an expansion state observer (ESO) in real time, which can reduce the estimating range of observation for ESO. The purpose of this paper is to suggest a novel method to improve the system tracking performance, as well as the dynamic and static performance index.Design/methodology/approachA welding robot is a complicated system with uncertainty, time-varying, strong coupling and a nonlinear system; it is more complex as if it is used in an underwater environment, and it is difficult to establish an accurate dynamic model for an underwater welding robot. Aiming at the tracking control of an underwater welding robot, it is difficult to achieve the control performance requirements by the conventional proportional integral derivative method to realize automatic tracking of the seam.FindingsThe simulation experiment is carried out by MATLAB/Simulink, and the application experiment is recorded. The experimental results show that the control method is correct and effective, and the system’s tracking performance is stable, and the robustness and tracking accuracy of the system are also improved.Originality/valueThe seam gets plumper and smoother, with better continuity and no undercut phenomenon.

Otomatisasi Pengontrol Temperatur Suhu Untuk Mesin Pengering Pelet Menggunakan Kontroler Autonics TK4S Dengan Metode PID

A pellet dryer machine is a tool that makes it easy to dry pellets so it doesn't have to require sunlight to dry the pellets. Various methods have also been widely used to control the temperature on the machine. One of the obstacles experienced is controlling the temperature so that it remains stable and has a good response time. In this journal, a pellet drying machine with PID (proportional integral derivative) method will be designed to keep the temperature stable. The temperature that makes the setpoint is 100°C. In the design carried out, it is by comparing sistems that are given Proportional control, Proportional and Integral (PI) control and Proportional Derivative (PD) control. For the controller used, it is an Autonics TK4S type controller. In the control, PID tuning will be carried out which will later be carried out variations of each Kp, Ki, and Kd values.

Moisture Control System in Mustard Plants Using the PID Method

Irrigating paddy fields is a very important process for plant growth. When the process of irrigating rice fields is carried out by means of continuously flowing water and the soil moisture value is only based on estimates, there are many possibilities for the moisture value not to be measured where this causes the plants to take a long time to grow and the plants will rot or fail to harvest if the humidity value is too high. So a final project was designed with the title Humidity Control System in Mustard Plants Using the PID Method. The way this system works is by placing 5 humidity sensors at five different points to read soil moisture values ​​and each sensor is connected to the Arduino Mega 2560 microcontroller. The controller used in this irrigation system is Proportional Integral Derivative (PID) to get humidity values according to the needs of the plant. The design and construction of an automatic irrigation system in this study was successfully carried out using the PID method, the corresponding Kp parameter values ​​for the system were obtained, namely Kp = 4.328, Ki = 2.634, and Kd = 3.217. This automatic irrigation system can reach the moisture point of the mustard plant, which is 60% with a steady state error of 0.387% and a rise time 79 seconds. The test was carried out for 7 days and by comparing the average plant height in the manual watering area and the automatic watering area. The average growth of plant height in the manual watering area and the automatic watering area has a difference of 1.2 cm. Because this system only focuses on water irrigation where plants also need other nutrients for growth besides water.

Modelling and control design of the electrostatic linear comb actuator

Control design plays a major part in electrostatic linear comb actuator (ELCA) systems. Most existing control methods of ECLA mainly focus on traditional PID method. However, proportional–integral–derivative (PID) controller is only appropriate for the reference to be known as constant. In this article, the problem of establishing the dynamic model and designing the controller is investigated for ECLA working in the time-varying reference. The tracking effectiveness is constructed for ECLA systems based on the consideration of roots of the equivalent differential equation in tracking error model. Moreover, the convergence velocity is also tuned by changing the parameters in the presented control scheme. Simulation results guarantee the performance of the nonlinear control scheme as well as dynamic model to be established.

A novel robust reset controller implemented through field programmable gate array for oxygen ratio regulation of proton exchange membrane fuel cell

This paper considers the nonlinear proton exchange membrane fuel cell model to precisely describe the system dynamics and presents a robust reset control method for regulating oxygen rate and optimizing the operation of the fuel cell system during fast load variations. The proposed reset law eliminates overshoot, shortens settling time, and thus improves the behavior of the closed-loop system, while achieving these goals is impossible by any linear controller. Due to the ability of field programmable gate array (FPGA) in providing high speed and efficient processing through software as well as near-real-time performance verification, the proposed control method is implemented through FPGA to confirm operational capability and high speed flexibility of controller. The results of the implementation of the proposed method and comparison with the hybrid fuzzy proportional integral derivative method exhibit smooth dynamic response, error reduction in terms of various criteria and better capability in tracking the desired oxygen rate despite the drastic changes in load current.