Actuator Dynamics-Aware Model Predictive Control of a Wheeled Inverted Pendulum with a Fan
Dohyeon Kim, Yeongtae Jung
AI summary
Problem
Wheeled inverted pendulum systems are inherently unstable and underactuated, and adding a bidirectional fan thrust introduces severe control challenges due to the fan's low bandwidth and nonlinear dynamics that standard controllers ignore.
Approach
The authors design a Frequency-Shaped Model Predictive Control (FSMPC) framework that uses the fan's experimentally identified frequency response to create a frequency-dependent cost function, penalizing out-of-bandwidth inputs while enabling real-time nonlinear optimization.
Key results
- Systematic method to derive FSMPC weighting parameters directly from actuator frequency response
- Nonlinear solver achieves control updates exceeding 1 kHz for real-time implementation
- FSMPC demonstrates superior stability and robustness over LQR, standard MPC, and FSLQR in simulations and hardware experiments
- Successfully integrates asymmetric thrust constraints and hybrid actuation bandwidths into the optimization
Why it matters
Enables reliable, high-speed control of hybrid-actuated robots with mismatched bandwidths, advancing agile and terrain-adaptive mobility.
Abstract
Wheeled Inverted Pendulum (WIP) systems offer ag- ile mobility but are challenging to control due to their unstable and underactuated dynamics. To address these limitations, we develop a Wheeled Inverted Pendulum with a Fan (WIPF), which incor- porates a fan-generated bidirectional thrust force as an additional control input. This makes the system fully actuated and enhances stability; however, the limited bandwidth of the fan thrust intro- duces control challenges. In this letter, we propose a Frequency- Shaped Model Predictive Control (FSMPC) design framework that accounts for actuator dynamics in the optimization process, and is expandable to other systems with different actuator dynamics. The proposed FSMPC can provide improved stability by penalizing high-frequency input using the frequency response of the fan. The nonlinear solver enables control input updates at rates exceeding 1 kHz, meeting real-time control requirements. The performance of FSMPC with the proposed design framework is compared through simulations and experiments against a Linear Quadratic Regula- tor (LQR), a standard Model Predictive Controller (MPC), and a Frequency-Shaped LQR (FSLQR) that does not consider fan dynamics or the input constraint. The results demonstrate that FSMPC achieves improved stability and robustness compared to other controllers.