Maple Optimizes Controller Design to Guide the Motion of a Maglev Train - Maplesoft

User Case Study:
Maple Optimizes Controller Design to Guide the Motion of a Maglev Train

Magnetically Levitated (Maglev) trains differ from conventional trains in that they are levitated, guided and propelled along a guideway by a changing magnetic field rather than by steam, diesel or electric engine. The absence of direct contact between the train and the rail allows the Maglev to reach record ground transportation speeds, which are on par to that of commercial airplanes.

An Electromagnetic Suspension (EMS) Maglev train uses the attractive forces of magnets, positioned below a ferrous metal guideway, to levitate a train and guide its motion. To prevent collision with the guideway, a constant air gap must be maintained at all times between the train and the guideway, regardless of a change in direction or angle of the track, inconsistencies in the guideway, or environmental forces such as wind.

In this example, Maple, Maplesoft’s powerful computation tool, is used to design a robust feedback controller and optimize the control parameters to guide the motion of a Maglev train along the guideway.

Maple is used to create, from first principles, a linear model of the new system and develop the control system, including both acceleration feedback and a PID controller. The acceleration feedback allows the air gap to be increased or decreased according to disturbances, so that there is no unwanted response. This results in a smoother and more comfortable ride.

By using Maple, the design time takes only a few days, instead of the weeks required by traditional methods. Additionally, capturing the design knowledge in a single Maple document makes replicating or expanding the analysis straightforward in the future.

Contact Maplesoft to learn how Maple can be used in your projects.