Papers by Keyword: PID Control

Abstract: Dynamic robots capable of navigating confined and unpredictable environments are increasingly needed in industrial applications. This study aimed to design and evaluate a two-legged wheeled self-balancing robot platform to achieve stable and efficient motion in narrow and dynamic settings. The robot was built using an Arduino Mega 2560 microcontroller, MPU6050 IMU sensor, TD8129MG servo motors, and LN298N motor drivers, with balance maintained by a proportional-integral-derivative (PID) controller. Static stability tests confirmed reliable balance at a -2.00° pitch angle with optimized PID gains of K_p = 120, K_i = 0.1, and K_d = 150. Dynamic experiments under duty cycles of 59%, 78%, and 98% showed that the 78% configuration provided the optimal compromise, enabling smooth motion at 0.23 m/s with minimal oscillations, while lower duty cycles caused instability and higher cycles introduced excessive vibrations. These results demonstrate that the developed robot effectively balances speed and stability, offering a compact and maneuverable solution for industrial tasks in constrained spaces. The study concludes that this platform provides a strong foundation for practical applications, with future work directed toward advanced control strategies and autonomous navigation to enhance adaptability and energy efficiency in real-world environments.

Abstract: Lower limb exoskeletons assist individuals with mobility impairments by providing support and aiding rehabilitation. However, precise trajectory tracking remains a challenge due to variations in user movement and nonlinear gait dynamics. Traditional control methods, such as PID controllers, require continuous tuning and struggle with long-term adaptability. This study proposes a PID-based Iterative Learning Control (PID-ILC) approach for a 2-DOF lower limb exoskeleton, which refines control inputs over successive gait cycles to improve tracking accuracy. MATLAB simulations demonstrate that the PID-ILC strategy significantly reduces tracking errors over iterations, leading to smoother and more accurate joint movements. The results confirm that iterative learning enhances exoskeleton performance by improving motion precision and adaptability. This approach minimizes manual tuning efforts and provides a more effective solution for rehabilitation applications.

Abstract: An adaptive control system is an advanced method for controlling the speed of a moving motorized vehicle. Using this intelligent control system, the driver can easily control the speed of the car according to his wishes or the prevailing situation. The adaptive control system consists of a sensor attached to a moving vehicle which then registers the speed of the car and provides input to the processing unit. The controller is designed according to the force exerted by the car to drive a certain distance in a certain time. This time, the control uses a PID controller. This method is followed for various tunings of Kp, Ki, and Kd values for the P, PI, PID, and IPD structures for a cruise control system using MATLAB. The PID used in this experiment is intended to control the speed to make it more stable and optimal.

Abstract: This paper presents the research of model-base design and control of Remotely Operated Vehicle (ROV) built in VietNam Automation & Mechatronics Laboratory (VIAMLAB). This is one of the most important types of underwater robots used in water environments for many purposes, especially for navy and marine industries. The design keeps our tethered ROV self-stabilized in the horizontal plane. It is also equipped with thrusters and sensor feedbacks, allowing 6 degrees-of-freedom motion. Moreover, cameras and grabber integrated into ROV support underwater survey tasks. In addition, the paper also simulates controllers with the main task of keeping depth for ROV. The controllers designed and surveyed here include: PID, optimal control (LQR), standard model control (MRAC) and combination controller between LQR and MRAC. The performance of the algorithm will be evaluated through simulation results using Matlab / Simulink.

Abstract: DC servo systems which are utilized in many industries require efficient and robust control strategies for achieving specific duties accurately. An integral sliding mode control (ISMC) is designed for position control of DC servo-driven conveyor system in this work. The ISMC which maintains the robustness, linearization and systematic design procedure of the conventional sliding modes is aimed to solve robust position control problem under load uncertainties. Performance and robustness of the ISMC are compared with the PID controller. Numerical and experimental results are presented to demonstrate the validity, feasibility and effectiveness of the designed control technique.

Abstract: Sliding Mode Variable Structure(SMC) based on index approaching rate to control tension is used in this paper,because the lead sheet uncoiler electro-hydraulic tension control system parameters exist many problems,such as:time-varying,coupling multiple interference and so on.Through Matlab/Simulink simulation tool to make simulationanalysis for the electro-hydraulic proportional tensio control model,and comparing with PIDcontrol.The simulation results shows that SMC control is better than PID control.The system can be strongly adaped to parameters time-varying interference and has strong robustness.

Abstract: In light of the difficulty for the multi-variable fuzzy controller to formulate a sophisticated set of rules concerning multi-dimensional controlling, this project proposes a parallel connection fuzzy PID controller, each PID employing two fuzzy controllers to carry out parameter tuning. This project applies the parallel connection PID fuzzy controller in controlling the jacking system of the multi-hydraulic cylinders. Through the AMESim/Simulink connector, joint simulation is achieved for the hydraulic system and the controlling system. The result of the simulation reveals that this application effectively improves the dynamic and static performance of the system, as well as synchronization precision in the jacking of the hydraulic cylinders.

Abstract: In this paper, the authors describe and demonstrate how a Five fingered gripper can be designed and simulated to provide both gross motion and fine motion to the fingers. Satisfactory motion responses for the finger simulation are achieved. The fine motion including force feedback and the gross motions, which orientate the fingers into their approximate configuration is provided by an advance PID control strategy. The fingers are to be controlled in a manner which mimics the kinematics and dynamics of the five fingers of a human hand. This mimicry is required to design the correct motions necessary to handle engineering components. In order to evaluate the design philosophy and capability of the five fingered gripper, a challenging assembly process has been identified. The five fingered gripper assembly was built using Solidworks software tool, and it’s mechanical assembly representation was established in SimMechanics. The advance PID control is very effectively used to control the trajectory of the fingers. The simulation results have been demonstrated that the radius of finger movement is achieved in stable response. The signal error towards closed less than 1% which it indicates the response dynamic system response is stable.

Abstract: The purpose of this paper is to develop an intelligent mobile robot using image processing technology. The mobile robot is composed of a visual tracking system, a loading platform, a balance control system, a PC-based controller, four ultrasonic sensors and a power system. We develop a PC based control system for image processing and path planning. The mobile robot can track a moving target and adjust the loading platform by the balance control system simultaneously. The Image processing based on OpenCV use two different tracking methods, MTLT (Match Template Learning Tracking) and TLD (Tracking, Learning and Detection), to track moving targets. The efficiencies of both methods for tracking the moving target on the mobile robot are compared in this paper. The loading platform control system uses HOLTEK Semiconductor Company's HT66F Series 8-bit microprocessor as the processor, and receives the feedback data from the FAS-A inclinometer sensor. The controller of the loading platform uses the PID control law according to the feedback signals of the inclinometer sensor, and controls the rotation speed of the platform motor to tune the balance level. Keywords— Intelligent mobile robot, Image processing, OpenCV, MTLT, TLD, HOLTEK, FAS-A inclinometer sensor, PID control.

Abstract: This paper presents the comparison of positioning control between conventional PID controller and fuzzy PID controller. The controllers are applying into the ball screw system driven by DC motor to observe and analyze the change of the positioning output responses. The DC motor is used because it is easy to setup and control, has precise rotation and most importantly is low cost. As for ball screw mechanism itself, has smooth motion, not easy to wear out and high mechanical efficiency. The problem is arise when the used of conventional PID controller in the ball screw system driven by DC motor shows less adaptability to the changes of system parameter. Therefore, the objective of this project is to design an adaptive fuzzy PID controller to overcome the limitation of conventional PID controller. The performances between the conventional PID controller and fuzzy PID controller will be compared in order to validate the robustness of the fuzzy PID controller. So this project is to compare the robustness of two proposed controllers by comparing the results of ball screw table position when the parameter mass of load is set to vary. The experiment is started with designing the algorithms of fuzzy PID control and conventional PID controller, then the designed algorithm is applied onto the experimental that has been setup. The performances especially the transient response and steady state error between the controllers will be collected and compared by conducting the point to point positioning, tracking and variation of load weight experiments.