Tsung-Wun (David) Wang

Tsung-Wun (David) Wang

Engineer at Vecow

Control Projects

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SemesterProjectKeywordsAttachment
Spring 2022Vibration Suppression of An Optical TableInput-Output Disturbance Response Decoupling (IODRD)report
Spring 2022MIMO System Identification of A QuadcopterARX Model, H $\infty$ Synthesisslide, video
Spring 2021$\mu$-Synthesis Design of A Half-Car Active Suspension System$\mu$-Synthesis, Robust Performanceslide, report
Spring 2020Adaptive Control Design and Stability Analysis of RR Robotic ManipulatorsLyapunov Stability, Model Reference Adaptive Control (MRAC)report
Fall 2018Wheeled Inverted PendulumSystem Identification, PID Controlslide, video

Vibration Suppression of An Optical Table

This project introduces a decoupling method called Disturbance Response Decoupling (DRD) to reduce the vibration of an optical table. The DRD is extended to Output DRD and Input-Output DRD to enhance the optical table’s performance under varied simulation conditions. We first test a quarter table and then extend our analysis to a larger scale, namely the full table. MATLAB simulations demonstrate the decoupling effects of various control strategies when different disturbances and outputs are considered. All types of DRD significantly reduce the vibration of the optical tables.

MIMO System Identification of A Quadcopter

The Multi-Input Multi-Output (MIMO) system of a quadcopter is more complex than a simple Single-Input Single-Output (SISO) system, necessitating a scientific analysis. After tuning a stable PID controller, we found that the ARX model best fits the experimental data. Our system identification approach enables the design of a stabilizing controller that improves the quadcopter’s performance.

μ-Synthesis Design of A Half-Car Active Suspension System

This project develops control strategies for vibration reduction in the suspension system to enhance passenger comfort. The challenge arises from disturbances originating from various sources. To achieve robust performance, we design a stabilizing controller to manage the actuators, improving both ride comfort and suspension deflections. This work focuses on an active suspension system and μ-synthesis, resulting in robust performance through our controller design.

Adaptive Control Design and Stability Analysis of RR Robotic Manipulators

This paper presents the adaptive control design and stability analysis of robotic manipulators based on two approaches: Lyapunov stability theory and hyperstability theory. We introduce two types of control for a 2-degree-of-freedom (2-DOF) robotic manipulator: computed-torque control and adaptive control. Additionally, we apply adaptive control to end-effector motion and force control, emphasizing motion control (e.g., position control, trajectory tracking). The control system developed by integrating Proportional-Integral-Derivative (PID) control and Model Reference Adaptive Control (MRAC) demonstrates convergence through the hyperstability approach. We compare the characteristics of the systems developed using PID control, MRAC control, and hybrid (PID + MRAC) control.

Wheeled Inverted Pendulum

In this project, we apply several control schemes, including PID control, to the inverted pendulum. We analyze the system’s characteristics to enhance its performance, aiming to shorten the settling time and minimize the steady-state error.