Synchronizing of Stabilizing Platform Mounted on a Two-Wheeled Robot

This paper represents the designing, building, and testing of a self-stabilizing platform mounted on a self-balancing robot. For the self-stabilizing platform, a servo motor is used and for the self-balancing robot, two dc motors are used with an encoder, inertial measurement unit, motor driver, an Arduino UNO microcontroller board. A PID controller is used to control the balancing of the system. The PID controller gains (Kp, Ki, and Kd) were evaluated experimentally. The value of the tilted angle from IMU was fed to the PID controller to control the actuated motors for balancing the system. For the self-stabilizing control part, whenever the robot tilted, it maintained the horizontal position by rotating that much in the opposite direction

Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system: A comparative assessment

This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. The particle swarm optimization and spiral dynamic algorithm are used for enhanced performance of the IT2FLC by finding optimised values for input and output controller gains and parameter values of IT2FLC membership function as comparison purpose in order to identify better solution for the system. A new model of triple-link inverted pendulum on two-wheels system, developed within SimWise 4D software environment and integrated with Matlab/Simulink for control purpose. Several tests comprising system stabilization, disturbance rejection and convergence accuracy of the algorithms are carried out to demonstrate the robustness of the control approach. It is shown that the particle swarm optimization-based control mechanism performs better than the spiral dynamic algorithm-based control in terms of system stability, disturbance rejection and reduce noise. Moreover, the particle swarm optimization-based IT2FLC shows better performance in comparison to previous research. It is envisaged that this system and control algorithm can be very useful for the development of a mobile robot with extended functionality

Stabilizing control of two-wheeled wheelchair with movable payload using optimized interval type-2 fuzzy logic

The control schemes of a wheelchair having two wheels with movable payload utilizing the concept of a double-link inverted pendulum have been investigated in this article. The proposed wheelchair has been simulated using SimWise 4D software considering the most efficient parameters. These parameters are extracted using the spiral dynamic algorithm while being controlled with interval type-2 fuzzy logic controller (IT2FLC). The robustness and stability of the implemented controller are assessed under different situations including standing upright, forward motion and application of varying directions and magnitudes of outer disturbances to movable (up and down) system payload. It is shown that the two-wheeled wheelchair adopted by the newly introduced controller has achieved a 94% drop in torque for both Link1 and Link2 and more than 98% fall in distance travelled in comparison with fuzzy logic control type-1 (FLCT1) controller employed in an earlier design. The present study has further considered the increased nonlinearity and complexity of the additional moving payload. From the outcome of this study, it is obvious that the proposed IT2FLC-spiral dynamic algorithm demonstrates better performance than FLCT1 to manage the uncertainties and nonlinearities in case of a movable payload two-wheel wheelchair system

Comparative Study of Takagi-Sugeno-Kang and Madani Algorithms in Type-1 and Interval Type-2 Fuzzy Control for Self-Balancing Wheelchairs

This study examines the effectiveness of four different fuzzy logic controllers in self-balancing wheelchairs. The controllers under consideration are Type-1 Takagi-Sugeno-Kang (TSK) FLC, Interval Type-2 TSK FLC, Type-1 Mamdani FLC, and Interval Type-2 Mamdani FLC. A MATLAB-based simulation environment serves for the evaluation, focusing on key performance indicators like percentage overshoot, rise time, settling time, and displacement. Two testing methodologies were designed to simulate both ideal conditions and real-world hardware limitations. The simulations reveal distinct advantages for each controller type. For example, Type-1 TSK excels in minimizing overshoot but requires higher force. Interval Type-2 TSK shows the quickest settling times but needs the most force. Type-1 Mamdani has the fastest rise time with the lowest force requirement but experiences a higher percentage of overshoot. Interval Type-2 Mamdani offers balanced performance across all metrics. When a 2.7 N control input cap is imposed, Type-2 controllers prove notably more efficient in minimizing overshoot. These results offer valuable insights for future design and real-world application of self-balancing wheelchairs. Further studies are recommended for the empirical testing and refinement of these controllers, especially since the initial findings were limited to four-wheeled self-balancing robotic wheelchairs

Interval type-2 fuzzy logic control optimize by spiral dynamic algorithm for two-wheeled wheelchair

The reconfiguration of the two-wheeled wheelchair system with movable payload has been investigated within the current study towards permitting multi-task operations; through enhanced maneuverability on a flat surface under the circumstances of disturbance rejections during forward and backward motions, as well as motions on the inclined surface for uphill and downhill motions; while having height extensions of the wheelchair’s seat. The research study embarks on three objectives includes developing Interval Type-2 Fuzzy Logic Control (IT2FLC) as the control system, design a Spiral Dynamic Algorithm (SDA) for IT2FLC in stabilizing the designed double-link twowheeled wheelchair system, and optimize the input-output gains and control parameters. The two-wheeled system gives lots of benefits to the user such as less space needed to turn the wheelchair, able to move in the narrow spaces, having eye-to-eye contact with normal people, and can reach stuff on the higher shelve. However, the stability of the twowheeled system will produce high fluctuations due to the uncertainties while stabilizing the system in the upright position. Indirectly, it also caused the long travelled distance and high magnitude of tilt angle and torque. Thus, IT2FLC has been proposed as the compatible control strategy for disturbance rejections to overcome uncertainties for enhanced system stability in the upright position. Basically, IT2FLC uses a Type-2 Fuzzy Set (T2FS) and its membership function (MFs) composed of the lower MFs, upper MFs, and footprint of uncertainty (FOU). This is the reason that IT2FLC possessing the ability to handle cases of nonlinearities and uncertainties that occur in the system. Therefore, any disturbances that give at the back of the seat can be eliminated using the proposed controller, IT2FLC. Additionally, SDA implemented within the control strategy to acquire optimal values of the IT2FLC input-output control gains and parameters of its MFs further accommodated extensive fluctuations of the two-wheeled system; thus, ensuring a safe and comfortable experience among users via shorter traveled distance and lower magnitude of torques following disruptions. The two-wheeled wheelchair is designed using SimWise 4D software to subduing shortcomings of a linearized mathematical model where lengthy equation with various assumptions is required to represent the proposed system; without forgoing its nonlinearity and complexity. Moreover, a 70kg payload was also included to embody an average user, in simulating vertical extensions of the system from 0.11m to 0.25m. The completed model is then integrated with Matlab/Simulink for control design and performance evaluation through visualized simulations. The research has been compared to the previous controllers, Fuzzy Logic Control Type-1 (FLCT1), in gauging improvements and performance superiority. The significance of SDA-IT2FLC as the stability controller within the investigated system has been confirmed through current findings, which outperformed that of its predecessors (IT2FLC and FLCT1). Such results are supported through a significant reduction in traveled distance, tilt, and control torques, following a recorded 5.6% and 33.3% improvements on the stability of the system, to the performance of heuristically-tuned IT2FLC; as well as a 60% and 94% improvements in angular positions on the system, as compared to the FLCT1. Moreover, a 95.4% reduction in torques has been recorded for SDA-IT2FLC, as compared to that of FLCT1. Ultimately, SDAIT2FLC has demonstrated promising outcomes over its predecessors on maintaining the system’s stability in an upright position in terms of faster convergence and a significant reduction in traveled distance, tilt and control torques, proving itself as the robust controller for a double-link two-wheeled wheelchair with movable payload system

Two-wheel balancing robot; review on control methods and experiments

Two-wheel mobile robot has been active field of study and research as it provides simple mechanical design and high maneuverability. Various developments continue to take place in the process of achieving stability, navigation from one place to another. This article intended to address the control methods of balancing two-wheeled mobile robot from linear controller, non-linear controller and adapting and self-learning algorithm. The focus of the review will be the evaluation and experiment done on two-wheel mobile robot. With the objective of mobile robot advances further from self-balancing, navigating or obstacle avoiding, towards completing sophisticated external task such as transporting and monitoring the surrounding. It is believed that this review will help researchers in developing substantial two-wheeled mobile robot

Lifting and stabilizing of two-wheeled wheelchair system using interval type-2 fuzzy logic control based spiral dynamic algorithm

The current study emphasizes on improving an interval type-2 fuzzy logic control (IT2FLC) system through the use of spiral dynamics algorithm (SDA) optimization in stabilizing a transformational two-wheeled wheelchair. The main contribution of this research is to reduce vibrations while performing the lifting and stabilization of a wheelchair from its standard four-wheeled to two-wheeled transformation. IT2FLC based SDA was used to enhance the system’s stability performance by obtaining the optimized value for input and output controller gains and IT2FLC parameters for IT2FLC. System modeling was done through development within the SimWise 4D software environment, which was then integrated with MATLAB/SIMULINK for control purposes. The proposed algorithm has demonstrated improved tilt angle performance with reduced noise and lower torque when various disturbances were applied, as compared to a system solely controlled by IT2FLC without any optimization. Moreover, the proposed algorithm has also comprehensively outperformed previous controllers in terms of system’s stability, further demonstrated its superiority as a system controller within transformational wheelchairs

Using a Combination of PID Control and Kalman Filter to Design of IoT-based Telepresence Self-balancing Robots during COVID-19 Pandemic

COVID-19 is a very dangerous respiratory disease that can spread quickly through the air. Doctors, nurses, and medical personnel need protective clothing and are very careful in treating COVID-19 patients to avoid getting infected with the COVID-19 virus. Hence, a medical telepresence robot, which resembles a humanoid robot, is necessary to treat COVID-19 patients. The proposed self-balancing COVID-19 medical telepresence robot is a medical robot that handles COVID-19 patients, which resembles a stand-alone humanoid soccer robot with two wheels that can maneuver freely in hospital hallways. The proposed robot design has some control problems; it requires steady body positioning and is subjected to disturbance. A control method that functions to find the stability value such that the system response can reach the set-point is required to control the robot's stability and repel disturbances; this is known as disturbance rejection control. This study aimed to control the robot using a combination of Proportional-Integral-Derivative (PID) control and a Kalman filter. Mathematical equations were required to obtain a model of the robot's characteristics. The state-space model was derived from the self-balancing robot's mathematical equation. Since a PID control technique was used to keep the robot balanced, this state-space model was converted into a transfer function model. The second Ziegler-Nichols's rule oscillation method was used to tune the PID parameters. The values of the amplifier constants obtained were Kp=31.002, Ki=5.167, and Kd=125.992128. The robot was designed to be able to maintain its balance for more than one hour by using constant tuning, even when an external disturbance is applied to it. Doi: 10.28991/esj-2021-SP1-016 Full Text: PD

Hybrid spiral-dynamic bacteria-chemotaxis algorithm with application to control two-wheeled machines

This paper presents the implementation of the hybrid spiral-dynamic bacteria-chemotaxis (HSDBC) approach to control two different configurations of a two-wheeled vehicle. The HSDBC is a combination of bacterial chemotaxis used in bacterial forging algorithm (BFA) and the spiral-dynamic algorithm (SDA). BFA provides a good exploration strategy due to the chemotaxis approach. However, it endures an oscillation problem near the end of the search process when using a large step size. Conversely; for a small step size, it affords better exploitation and accuracy with slower convergence. SDA provides better stability when approaching an optimum point and has faster convergence speed. This may cause the search agents to get trapped into local optima which results in low accurate solution. HSDBC exploits the chemotactic strategy of BFA and fitness accuracy and convergence speed of SDA so as to overcome the problems associated with both the SDA and BFA algorithms alone. The HSDBC thus developed is evaluated in optimizing the performance and energy consumption of two highly nonlinear platforms, namely single and double inverted pendulum-like vehicles with an extended rod. Comparative results with BFA and SDA show that the proposed algorithm is able to result in better performance of the highly nonlinear systems

Design Nonlinear Model Reference with Fuzzy Controller for Nonlinear SISO Second Order Systems

Model reference controller is considering as one of the most useful controller to specific performance of systems where the desired output is produced for a given input. This system used the difference between the outputs of the plant and the desired model by comparing them to produce the signals of the control. This paper focus on design a model reference controller (MRC) combined with (type-1 and interval type-2) fuzzy control scheme for single input-single output (SISO) systems under uncertainty and external disturbance. The model reference controller is designed firstly without fuzzy scheme based on an optimal desired model and Lyapunov stability theory. Then a (type-1 and Interval type-2) fuzzy controller Takagi-Sugeno type is combine with the suggested MRC in order to enhance the performer of it, the common parts between the two fuzzy systems such as: fuzzifier, inference engine, fuzzy rule-base and defuzzifier are illustrated. In this paper the proposed controller is applied to controla (SISO) inverted pendulum sustem and the Matlab R2015 software is used to carry out two simulation cases for the overall controlled scheme. The obtained results for the two cases show that the proposed MRC with both fuzzy control schemes have acceptable performance, but it have better performance with the interval type-2 fuzzy scheme