In this paper, the Jacobian-linearization-and feedback-linearization-based techniques of obtaining linearized model approaches are combined with a family of robust LQR control laws to identify the pairing which results in superior control performance of the bicycle robot, despite uncertainty and constraints, what is the main contribution of the paper. The control performance is analyzed using various indices, related, e.g. to energy consumption of the considered laws, with the experiments conducted on a real bicycle robot. As a result, the easily-implementable controller is obtained, which requires only to perform a set of off-line computations with a single additional parameter in comparison with a standard linear-quadratic controller, to obtain a state-feedback vector, which, when implemented to the control system, ensures proper regulation of the output signal of the plant, despite uncertainty or possible actuator failures, obtaining energy-efficient control law.

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