Stable self-levelling control of a Stewart platform

Abstract

As the need for stability in motion continues to grow across various industries, there has been a keen interest in self-levelling platforms. These are mechatronic systems designed to automatically maintain a stable and level orientation, even when the surface they rest on is tilted or disturbed. The project focuses on a specific type of parallel manipulator called a Stewart platform, which is constructed using six linear actuators connected between a fixed base plate and a movable top plate. The movement of the top plate is controlled by adjusting the lengths of these actuators. The main objective of this dissertation is to design and implement a controller that is able to self-level the top plate of the Stewart platform without causing the system to become unstable, even in the presence of unpredictable forces or disturbances. This must be achieved while also managing the complex and highly non-linear behaviour that characterises the platform’s dynamics. This project presents the complete design and implementation of a self-levelling Stewart platform. It includes the development of a mathematical model of the platform’s dynamics using the Lagrangian formulation, followed by its application to a physically constructed system. A two-stage control strategy is implemented to achieve regulatory control and trajectory tracking, together with the self-levelling functionality based on a novel controller concept. The design and implementation of both the simulation models and the physical setup are detailed, encompassing the actuator control system, the inertial measurement system, hardware interfacing, and other essential aspects of the overall system. Extensive testing is carried out on both the simulation models and the physically implemented system, with results demonstrating stable performance and a high degree of self-levelling effectiveness for both user-defined poses and trajectories.