Stability and Control of a Rider–Bicycle System: Analysis and Experiments

Abstract

We present stability and control analysis of a rider–bicycle system under human steering and body movements. The dynamic model of rider–bicycle interactions is first constructed to integrate the rider’s body movement with the moving bicycle platform. We then present human balance control strategies based on human riding experiments. The closed-loop system stability is analyzed and discussed. Quantitative influences of the bicycle physical parameters, the human control gains, and the time delays are also analyzed and discussed. Extensive experiments are conducted to validate the human control models and demonstrate human balance performance using the bikebot, an instrumented bicycle platform. The presented modeling and analysis results can be potentially used for further development of bicycle-assisted rehabilitation for postural balance patients. Note to Practitioners —Understanding human balance and control of bicycles is crucial for not only designing bicycle-based rehabilitation devices but also studying physical human–machine interactions for healthcare automation. This paper takes the rider and bicycle as an example of physical human–machine interactions to understand how human use their limbs and body movement to stabilize an unstable platform (i.e., bicycles). We develop an instrumented bicycle system, called bikebot, to conduct human riding experiments. Using experimental data, we build the dynamic models for human steering and leaning control actions. Using these actuation models, stability analyses are conducted for rider–bicycle interactions and then validated by experiments. We also obtain the stability results by perturbing human visual and sensorimotor feedback. These results reveal that the visual feedback and the time delay in sensorimotor feedback mechanism play critical roles in stabilizing the unstable bicycle platform.