Thesis Energy Efficient Optimization of Lifting Operations

Background and Motivation

Lifting operations in automated systems are often energy-intensive and contribute significantly to overall power consumption and cycle time. In many existing implementations, the lifting motor is driven at or near full speed with limited motion shaping.

This can result in high mechanical shock loads when engaging or lifting a payload, leading to increased mechanical stress on the motor, transmission components, and structural elements.

With increasing demands for sustainability, performance, and system durability, optimizing lifting behavior at the software and control level has become increasingly important. Improved motion planning can not only reduce energy consumption and cycle time, but also decrease peak forces, mechanical impact, and wear, thereby potentially extending hardware lifetime and reducing maintenance requirements.

Problem Statement

Existing lifting str...