Analysis of internal dynamics in trajectory tracking problems

Bastos, Guaraci

doi:10.1007/s40435-023-01161-1

Cited by 1 publication

(1 citation statement)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many underactuated systems are non-minimum phases for certain outputs of interest [6,9]. Motion planning for these kinds of systems is even more challenging; indeed, the system internal dynamics is unstable [10]. Hence, the model inversion yields a set of ODEs that diverge during their numerical integrations [6,11].…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning through Model Inversion of an Underactuated Spatial Gantry Crane Moving in Structured Cluttered Environments

Bettega,

Richiedei,

Tamellin

2024

Actuators

View full text Add to dashboard Cite

Handling suspended loads in cluttered environments is critical due to the oscillations arising while the load is traveling. Exploiting active control algorithms is often unviable in industrial applications, due to the necessity of installing sensors on the load side, which is expensive and often impractical due to technological limitations. In this light, this paper proposes a trajectory planning method for underactuated, non-flat, non-minimum phase spatial gantry crane moving in structured cluttered environments. The method relies on model inversion. First, the system dynamics is partitioned into actuated and unactuated coordinates and then the load displacements are described as a non-linear separable function of these. The unactuated dynamic is unstable; hence, the displacement, velocity, and acceleration references are modified through the output redefinition technique. Finally, platform trajectory is computed, and the desired displacements of the load are obtained. The effectiveness of the proposed method is assessed through numerical and experimental tests performed on a laboratory testbed composed by an Adept Quattro robot moving a pendulum. The load is moved in a cluttered environment, and collisions are avoided while simultaneously tracking the prescribed trajectory effectively.

show abstract