Synchronizing of Stabilizing Platform Mounted on a Two-Wheeled Robot

This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance.

Section: Introductionmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

“…The Arduino training kit is an alternative way to create a prototype electric wheelchair. In the initial study of prototype development, it can be seen from research on the development of related systems such as motor control systems [11], [12], [13], the development of Autonomous Electric Vehicle using ultrasonic sensors for detecting objects, using the GPS system for navigation and using solar panels to help recharge [14], In addition, the car parking distance controller using ultrasonic sensors [15], includes applications to create small-scale robots that use three degrees of freedom (3-DoF) joints for controlling with a servo motor system [16], Balance robot [17], [18], [19], [20], [21], [22], a line-following robot using a camera sensor pixy II [23], and other related applications such as construction of temperature monitoring system for baby incubator based on visual basic [24], etc.…”

Section: Introductionmentioning

confidence: 99%

Design and Construction of Electric Wheelchair with Mecanum Wheel

Thongpance

Chotikunnan

2023

This research aimed to design and construct an electric wheelchair with mecanum wheels that can move in any desired direction and speed based on the joystick controller. This represents a significant improvement over traditional electric wheelchairs, which are limited to linear movement in a single direction. The research contribution of this study is the development of an electric wheelchair with mecanum wheels that allows for improved mobility and independence for wheelchair users. The design includes a joystick controller and the use of an average filter to improve the processing of the joystick. This represents a significant improvement over traditional electric wheelchairs, which are limited to linear movement in a single direction. The design and construction of the electric wheelchair followed the ISO 2570-2555 guidelines and utilized Arduino DUE as the main processor for controlling the rotation of the wheels. The gain of speed and angle of the analog joystick were determined using the technique of finding the resultant vector to control the direction and speed of the wheels. The resulting electric wheelchair had a standard structure and was able to move in the desired direction and speed based on the movement of the joystick controller, demonstrating the success of the design and construction in achieving its objective. In conclusion, the development of joystick control for electric wheelchairs is important and allows for the creation of significantly novel and improved designs such as the electric wheelchair with mecanum wheels presented in this research.

“…The friction and backlash models' parameters are typically unknown for servomechanism systems, which causes system uncertainty [6], [7]. High steady-state error is caused by friction, while unwanted vibration is caused by blowback [8], [9].…”

Section: Introductionmentioning

confidence: 99%

A New Self-Tuning Nonlinear PID Motion Control for One-Axis Servomechanism with Uncertainty Consideration

Shamseldin

Abdelghany

2023

This paper introduces a new study for one-axis servomechanism with consideration the parameter variation and system uncertainty. Also, a new approach for high-performance self-tuning nonlinear PID control was developed to track a preselected profile with high accuracy. Moreover, a comparison study between the proposed control technique and the well-known controllers (PID and Nonlinear PID). The optimal control parameters were determined based on the COVID-19 optimization technique. The parameters of the servomechanism system changed randomly at a preselected range through the online simulation. The change of these parameters acts as the nonlinearity resources (friction, backlash, environmental effects) and system uncertainty. A comparative study between the linear and nonlinear models had been accomplished and investigated. The results show that the proposed controller can track several operating points with high accuracy, low rise time, and small overshoot.