Anti-Windup Compensator Design For Improved Tracking Performance Of Differential Drive Mobile Robot

Wheeled mobile robots (WMRs) have been widely used for navigation purposes as well as industrial applications such as path tracking and obstacle detections. Differential drive robot (DDR) is one type of WMRs with a specific wheel configuration where two fixed wheels are controlled by the motors and a castor wheel is added to mechanically support its translational and rotational movements. For tracking purposes, the controller plays a very important role to ensure it does not deviate far from the targeted locations or path. In this project, a DDR is built with two DC motors. As most motors exhibit nonlinear behavior, they are modeled as a multivariable Hammerstein-Wiener structure which contains static nonlinearities and a linear system in series with each other. The identification of the linear model is performed via time response analysis with different types of inputs, whereas the nonlinearities are estimated via several tests in MATLAB Simulink. This work also focuses on both dynamic and kinematic models of the DDR where a proportional-integral (PI) controller is designed to achieve the desired specifications in the linear region. In order to account for the nonlinear effects from the DC motor model which is mainly influenced by its bounded velocity capability, a static anti-windup compensator (AWC) is implemented which is activated when the controller output exceeds the bound. Via this strategy, a significant improvement on the tracking performance of the DDR can be observed via simulations especially when the desired path involves sharp corners or turns.

Real-Time Trajectory Generation and Control of a Semi-Omnidirectional Mobile Robot

When controlling a wheeled mobile robot with four independently steerable driving wheels, the control of the wheel coordination must be handled. Both the direction and velocity of the wheels must be coordinated to allow for proper operation of the robot. The focus of this work is on the coordination of the wheel directions. Such coordination is mostly done by solving constraint equations of the system kinematics, but when the demands on the coordination are high, it is sometimes necessary to include the steering dynamics in the coordination control. With dynamics included the complexity of the wheel coordination increases, since constraints dependent on required angle changes and current velocities must be fulfilled. By calculating the dynamic limitations in each control cycle, the steering limit for the whole wheel base within the current control cycle can be found. With use of such wheel base limit, followable and coordinated wheel trajectories can be generated online. This thesis includes the construction of a dynamic model for inclusion of the steering dynamic limitations affecting the performance the most, the construction of the online trajectory generation idea, as well as implementation and validation on the real target wheeled mobile robot platform

Modeling, Analysis, and Control of a Mobile Robot for \u3ci\u3eIn Vivo\u3c/i\u3e Fluoroscopy of Human Joints during Natural Movements

In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while dynamically tracking the desired skeletal joint of interest. In addition to the joint tracking, this also requires the robotic platform to move along with the subject, allowing the manipulators to operate within their ranges of motion. A comprehensive dynamic model of the robotic fluoroscope prototype was created, incorporating the dynamic coupling of the system. Empirical data collected from an RGB-D camera were used to create a human kinematic model that can be used to simulate the joint of interest target dynamics. This model was incorporated into a computer simulation that was validated by comparing the simulation results with actual prototype experiments using the same human kinematic model inputs. The computer simulation was used in a comprehensive dynamic analysis of the prototype and in the development and evaluation of sensing, control, and signal processing approaches that optimize the subject and joint tracking performance characteristics. The modeling and simulation results were used to develop real-time control strategies, including decoupling techniques that reduce tracking error on the prototype. For a normal walking activity, the joint tracking error was less than 20 mm, and the subject tracking error was less than 140 mm