Manufacturing Research

Additive Manufacturing, Robotic Manufacturing, and Composite Manufacturing

MAAL focuses on the modeling, control, and trajectory generation/optimization of machine tool feed drives, industrial robots, and additive manufacturing machines. By establishing dedicated dynamic/process/mechanical models, MAAL established a group of control and trajectory optimization methods to reduce the vibration, enhance the accuracy/speed, and improve the mechanical performance of the continuous fiber-reinforced parts.

Modeling and control of industrial robot considering its joint and link flexibility

This project establishes a dynamic model of industrial robots considering the link and joint flexibility. The geometrical nonlinearity of the robot is captured with low dimensions via the strain-based beam elements and modal amplitudes. The dynamic model captures the industrial robot’s position- and posture-dependent vibration. A nonlinear filtered B-spline approach is developed to alleviate the motion-induced vibration.

Additive manufacturing process modeling, monitoring, and control

This project aims to establish a unified model of additive manufacturing process combining the process model and the feed drive dynamic model. Thermal cameras and accelerometers are exploited to acquire vibration, temperature, position, and process data. Local and cloud controllers are deployed to enable model-based and data-driven control for enhanced manufacturing performance.

Continuous fiber-reinforced material modeling, optimization, and fabrication

This project addresses the modeling and control in continuous fiber additive manufacturing. It aims to establish a computationally efficient model of free-form continuous-fiber-reinforced parts. The model is further exploited in fiber path optimization in a unified consideration of part modulus, strength, cost, and weights.

BOOM LIFT-MOUNTED ROBOT

This project proposes the boom lift-mounted robot platform, combining the scale model of boom lift vehicle with the six-axis industrial robot. The aim is to replace human to do the dangerous tasks at high altitude. This platform is deployed with the real-time controller, which can stabilize against the external disturbance, such as strong wind.

Aerospace Research

ROM and control of flexible aircraft and VTOL aircraft

MAAL focuses on the reduced-order modeling (ROM) and control of flexible aircraft and vertical takeoff and landing (VTOL) aircraft.

Reduced-order modeling and control of (very) flexible aircraft

Flexible and very flexible aircraft are increasingly popular in the pursuit of lightweight structure and aerodynamics efficiency. This project aims to establish a reduced-order model of the (very) flexible aircraft such that the aeroelastic properties of the aircraft can be more effectively evaluated. Furthermore, the reduced-order model is further exploited to control the aircraft’s load, fuel efficiency, and flight trajectory. Wind tunnel experiments are exploited to verify the model and the control algorithms.

VTOL aircraft data-driven modeling and control allocation

This project aims to address the difficulties in the modeling and control of vertical takeoff and landing (VTOL) aircraft by exploiting the combination of physics-based models and flight test data. The critical aerodynamics terms regarding high angles of attack, rotor-wing-airframe interactions, and thruster vectoring are considered. The hybrid model is exploited in a control allocation framework to control different phases of the VTOL flights.

Archived Projects