Control of a self-balancing robot with two degrees of freedom via IDA-PBC

International Journal of Reconfigurable and Embedded Systems (IJRES), 2023

A two-wheeled self-balancing robot (TWSBR) is an underactuated system that is inherently nonlinear and unstable. While many control methods have been introduced to enhance the performance, there is no unique solution when it comes to hardware implementation as the robot's stability is highly dependent on accuracy of sensors and robustness of the electronic control systems. In this study, a TWSBR that is controlled by an embedded NI myRIO-1900 board with LabVIEW-based control scheme is developed. We compare the performance between proportional-integral-derivative (PID) and linear quadratic regulator (LQR) schemes which are designed based on the TWSBR's model that is constructed from Newtonian principles. A hybrid PID-LQR scheme is then proposed to compensate for the individual components' limitations. Experimental results demonstrate the PID is more effective at regulating the tilt angle of the robot in the presence of external disturbances, but it necessitates a higher velocity to sustain its equilibrium. The LQR on the other hand outperforms PID in terms of maximum initial tilt angle. By combining both schemes, significant improvements can be observed, such as an increase in maximum initial tilt angle and a reduction in settling time. This is an open access article under the CC BY-SA license.

International Journal of Control

Improving the robustness, vis-à-vis matched input disturbances of IDA-PBC (Interconnection Damping Assignment, Passivity Based Control) for a class of underactuated mechanical systems is addressed in this paper. The characterized class of systems is the one for which IDA-PBC yields a smooth stabilizing controller. Our main contribution consists in combining the so-called IDA-PBC controller with an adaptive control technique. Some sufficient stability conditions on matched input disturbances are given. The comparison of the stability robustness between the classical controller IDA-PBC and the proposed one is then provided. As illustration we propose to revisit the application of IDA-PBC controller to the Inertia Wheel Inverted Pendulum (IWIP) in the presence of matched disturbances. Simulation and real-time experimental results are presented as validations of the theoretical results.

The paper describes utilization of the classical problem of inverted pendulum and its application to realize self-balancing robot. It is a two wheel vehicle whose structural, mechanical and electronic components were assembled in such a manner that it produced an inherently unstable platform which is highly susceptible to tip off in one axis. The wheels of the robot were capable of independent rotation each driven by a high torque DC motor. Information about the angle of the device relative to the ground was obtained from a 6DOFIMU (Inertial Measuring Unit) sensor which comprises of an accelerometer and agyroscope. Information from the IMU was processed and filtered to obtain accurat evalues which were fed to the micro processor on board. The microprocessor processed the feedback using a PID algorithm to generate position control signals i.e. apply proportional force to the motors as given by the program logic in order to restore the balance or to bring it back to its original vertical position. Two wheeled balancing robots can be used in several applications with different perspectives such as intelligent gardeners and autonomous trolleys in hospitals, transportation in shopping malls, offices, airports, or an intelligent robot.

Two wheeled balancing robots are an area of research that may well provide the future locomotion for everyday robots. The unique stability control that is required to keep the robot upright differentiates it from traditional forms of robotics. The inverted pendulum principle provides the mathematical modelling of the naturally unstable system. This is then utilized to develop and implement a suitable stability control system that is responsive, timely and successful in achieving this objective. Completing the design and development phase of the robot requires careful consideration of all aspects including operating conditions, materials, hardware, sensors and software. This process provides the ongoing opportunity of implementing continued improvements to its perceived operation whilst also ensuring that obvious problems and potential faults are removed before construction. The construction phase entails the manufacture and assembly of the robots circuits, hardware and chassis with the software and programming aspects then implemented. The later concludes the robots production where the final maintenance considerations can be determined. These are essential for ensuring the robots continued serviceability.

Proceeding of the Electrical Engineering Computer Science and Informatics, 2014

A robot must employ a suitable control method to obtain a good stability. The Two-Wheeled Self Balancing Robot in this paper is designed using a MPU-6050 IMU sensor module and ATmega128 microcontroller as its controller board. This IMU sensor module is employed to measure any change in the robot's tilt angle based on gyroscope and accelerometer readings contained in the module. The tilt angle readings are then utilized as the setpoint on the control methods, namely PD (Proportional Derivative), PI (Proportional Integral), or PID (Proportional Integral Derivative). Based on the conducted testing results, the PID controller is the best control strategy when compared to the PD and PI control. With parameters of Kp = 14, Ki = 0005 and Kd = 0.1, the robot is able to adjust the speed and direction of DC motor rotation to maintain upright positions on flat surfaces.

Webology, 2022

A self-balancing robot is a mobile robot that has two wheels on the right and left sides which will not balance if it is not controlled. This study aims to design a control system that can balance the self-balancing robot. The system used as input is from the MPU6050 sensor, and the output from the sensor in the form of a tilt angle will be processed using a microcontroller. The angle obtained will be compared with the setpoint value which is 0 degrees. The difference between the setpoint and the system output angle is controlled using PID control. For the output from the PID to be more stable, it will be filtered using a Kalman filter. Analysis of calculations using MATLAB software to make it easier to analyze the response of the self-balancing robot that has been given the values of Kp, Ki, and Kd. From the test results, it is obtained that the PID controller parameters that will be used from tunning the Kcr value with the Ziegler-Nichols method are Kp = 5.67, Ki = 85.5 and Kd = 0...

Two-wheeled self-balancing robot, moving on a horizontal plane, may be presented by a set of highly coupled nonlinear differential equations. In the recent literatures and in the commonly used twowheeled self-balancing robots, the control algorithms are designed based on the mathematical models with simplified structure. In these models, a nonlinear coupling term is usually neglected, whereas it has significant effects on the dynamic behavior of the system. In this paper, the mathematical representation of twowheeled self-balancing robots, including this new term, is derived using both Kane's and Lagrangian methods. The significant effect of the new term on the response of the system is shown by presenting the behavior of the system under different conditions and by comparing it with the system models when this term is neglected. Then sliding-mode control techniques are used to derive the controllers. The controller objective is to drive the two-wheeled self-balancing robot to the desired path as well as to make the robot stable. By some simulations, the behavior of the robot with the proposed controller is discussed. It is shown that if the nonlinear coupling term is ignored in designing the controller, the controller cannot compensate its effect.

This paper is aimed to discuss and compare three of the most famous Control Theories on a Two wheeled Self Balancing Robot Simulation using Robot Operating System (ROS) and Gazebo. Two Wheeled Self Balancing Robots are one of the most fascinating applications of Inverted Pendulum System. In this paper, PID, LQR and Fuzzy logic controllers are discussed. Also,0 the modeling and algorithms of the robot simulation is discussed. The primary objectives of this paper is to discuss about the building of a robot model in ROS and Gazebo , experimenting different control theories on them, documenting the whole process with the analysis of the robot and comparison of different control theories on the system.

2009 IEEE International Conference on Control Applications, 2009

In this brief note a new strict Lyapunov function for mechanical systems controlled by the well-known Passivitybased Control technique of Interconnection and Damping Assignment is proposed. The general, total energy-shaping, formulation of the control technique is considered, which yields a port-Hamiltonian closed-loop system with non-fixed symplectic structure. To construct the proposed Lyapunov function a new systematic mathematical machinery is introduced. The resulting Lyapunov function contains, as particular cases, previous functions obtained for robot manipulators controlled by potential energy-shaping (plus damping injection) schemes. Moreover, the class of robot manipulators considered so far in the literature is restricted, and almost universally accepted, to have only revolute joints, and the class considered here includes both revolute and prismatic joints. As an illustration example, practical bounds for a two-link direct drive robot manipulator are computed.

International journal of engineering research and technology, 2021

Self-balancing robot is an effective approach to the development and advancement in the field of robotics. In this particular model, the concept of inverted pendulum is used. Selfbalancing is a process by which a system achieves stability by internal forces. The basic idea of this project is to overcome the challenge of balancing initially unstable system, by providing control mechanism to the robot so that it can balance on its own. The robot uses sensor values provided by accelerometer and gyroscope to find exact position of itself in three-dimensional geometry and send the values to microcontroller. The microcontroller on the other hand uses programs in it to give proper instruction about rotation of wheels to the motor driver module which in turn helps to balance the robot. This robot is advantageous over traditional four wheeled robots as it helps in taking sharp turns and navigating through tighter areas thus, serving as an essential machine for various industrial applications.