Year: 2024
Type: conference-paper
Abstract: Identifying and controlling an unstable, under-actuated robot to enable reference tracking is a challenging control problem. In this paper, a ballbot (robot balancing on a ball) is used as an experimental setup to demonstrate and test proposed strategies to tackle this control problem. A double-loop control system, including a state-feedback gain in the outer-loop and a Proportional-Integral-Derivative (PID) controller in the inner-loop, is presented to balance the system in its unstable equilibrium. Once stability is reached, the plant’s response to an excitation signal is measured and interpreted to identify the system’s dynamics. Hereby, the parameters of a linearized model of the ballbot are identified with prior knowledge about the structure of the nonlinear dynamics of the system. Based on an identified linear time-invariant (LTI) state-space model, a double-loop control strategy is considered to balance the real system and to allow for reference tracking. A linear quadratic regulator (LQR) is designed offline and implemented in the inner-loop to ensure balance. In the outer-loop, the estimated dynamics forecast the system’s behavior online using a model-predictive-controller (MPC) to find the optimal control input for reference tracking. The experimental results demonstrate the applicability of the proposed strategies.
Authors: Tobias Fischer, Dimitrios S. Karachalios, Ievgen Zhavzharov, Hossam S. Abbas
Institution: University of Lübeck
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: Deutsche Forschungsgemeinschaft
OpenAlex ID: W4402436975