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

Adaptive Sliding Mode Tracking Control of Mobile Robot in Dynamic Environment Using Artificial Potential Fields

Solution to the safe and collision-free trajectory of the wheeled mobile robot in cluttered environments containing the static and/or dynamic obstacle has become a very popular and challenging research topic in the last decade. Notwithstanding of the amount of publications dealing with the different aspects of this field, the ongoing efforts to address the more effective and creative methods is continued. In this article, the effectiveness of the real-time harmonic potential field theory based on the panel method to generate the reference path and the orientation of the trajectory tracking control of the three-wheel nonholonomic robot in the presence of variable-size dynamic obstacle is investigated. The hybrid control strategy based on a backstepping kinematic and regressor-based adaptive integral sliding mode dynamic control in the presence of disturbance in the torque level and parameter uncertainties is employed. In order to illustrate the performance of the proposed adaptive algorithm, a hybrid conventional integral sliding mode dynamic control has been established. The employed control methods ensure the stability of the controlled system according to Lyapunov’s stability law. The results of simulation program show the remarkable performance of the both methods as the robust dynamic control of the mobile robot in tracking the reference path in unstructured environment containing variable-size dynamic obstacle with outstanding disturbance suppression characteristic

Optimizing the performance of a wheeled mobile robots for use in agriculture using a linear-quadratic regulator

Use of wheeled mobile robot systems could be crucial in addressing some of the future issues facing agriculture. However, robot systems on wheels are currently unstable and require a control mechanism to increase stability, resulting in much research requirement to develop an appropriate controller algorithm for wheeled mobile robot systems. Proportional, integral, derivative (PID) controllers are currently widely used for this purpose, but the PID approach is frequently inappropriate due to disruptions or fluctuations in parameters. Other control approaches, such as linear-quadratic regulator (LQR) control, can be used to address some of the issues associated with PID controllers. In this study, a kinematic model of a four-wheel skid-steering mobile robot was developed to test the functionality of LQR control. Three scenarios (control cheap, non -zero state expensive; control expensive, non -zero state cheap; only non -zero state expensive) were examined using the characteristics of the wheeled mobile robot. Peak time, settling time, and rising time for cheap control based on these scenarios was found to be 0.1 s, 7.82 s, and 4.39 s, respectively

Antifragile Control Systems: The case of mobile robot trajectory tracking in the presence of uncertainty

Mobile robots are ubiquitous. Such vehicles benefit from well-designed and calibrated control algorithms ensuring their task execution under precise uncertainty bounds. Yet, in tasks involving humans in the loop, such as elderly or mobility impaired, the problem takes a new dimension. In such cases, the system needs not only to compensate for uncertainty and volatility in its operation but at the same time to anticipate and offer responses that go beyond robust. Such robots operate in cluttered, complex environments, akin to human residences, and need to face during their operation sensor and, even, actuator faults, and still operate. This is where our thesis comes into the foreground. We propose a new control design framework based on the principles of antifragility. Such a design is meant to offer a high uncertainty anticipation given previous exposure to failures and faults, and exploit this anticipation capacity to provide performance beyond robust. In the current instantiation of antifragile control applied to mobile robot trajectory tracking, we provide controller design steps, the analysis of performance under parametrizable uncertainty and faults, as well as an extended comparative evaluation against state-of-the-art controllers. We believe in the potential antifragile control has in achieving closed-loop performance in the face of uncertainty and volatility by using its exposures to uncertainty to increase its capacity to anticipate and compensate for such events

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Model Predictive Control of Nonholonomic Mobile Robots

In this work, we investigate the possibility of using model predictive control (MPC) for the motion coordination of nonholonomic mobile robots. The contributions of this dissertation can be summarized as follows.A robust formation controller is developed for the leader-following formation of unmanned aerial vehicles (UAVs). With the assumption that an autopilot operating in holding mode at the low-layer, we present a two-layered hierarchical control scheme which allows a team of UAVs to perform complex navigation tasks under limited inter-vehicle communication. Specifically, the robust control law eliminates the requirement of leader's velocity and acceleration information, which reduces the communication overhead.A dual-mode MPC algorithm that allows a team of mobile robots to navigate in formations is developed. The stability of the formation is guaranteed by constraining the terminal state to a terminal region and switching to a stabilizing terminal controller at the boundary of the terminal region. With this dual-mode MPC implementation, stability is achieved while feasibility is relaxed.A first-state contractive model predictive control (FSC-MPC) algorithm is developed for the trajectory tracking and point stabilization problems of nonholonomic mobile robots. The stability of the proposed MPC scheme is guaranteed by adding a first-state contractive constraint and the controller is exponentially stable. The convergence is faster and no terminal region calculation is required. Tracking a trajectory moving backward is no longer a problem under this MPC controller. Moreover, the proposed MPC controller has simultaneous tracking and point stabilization capability.Simulation results are presented to verify the validity of the proposed control algorithms and demonstrate the performance of the proposed controllers.School of Electrical & Computer Engineerin

Integral Sliding Mode Control for Trajectory Tracking of Wheeled Mobile Robot in Presence of Uncertainties

Wheeled mobile robots present a typical case of complex systems with nonholonomic constraints. In the past few years, the dominance of these systems has been a very active research field. In this paper, a new method based on an integral sliding mode control for the trajectory tracking of wheeled mobile robots is proposed. The controller is designed to solve the reaching phase problem with the elimination of matched disturbances and minimize the unmatched one. We distinguish two parts in the suggested controller: a high-level controller to stabilize the nominal system and a discontinuous controller to assess the trajectory tracking in the presence of disturbances. This controller is robust during the entire motion. The effectiveness of the proposed controller is demonstrated through simulation studies for the unicycle with matched and unmatched disturbances