A model and tracking control method for a double-steering wheeled climbing robot (DSWCR) are presented in this article. The dynamic model of the DSWCR system is established using the Lagrange equation, considering the effects of slipping, variations in gravity and the friction coefficient, and wall/wheel interaction forces. During wall motion, the DSWCR is subject to uncertainties introduced from both the state and model. To address the tracking problem of the DSWCR under state and model uncertainties, an adaptive dynamic programming (ADP) controller based on zero-sum theory is proposed. The stability of the DSWCR tracking system and the convergence of the weights in a neural network are demonstrated. Finally, simulations and a prototype experiment are conducted to verify the optimality and robustness of the proposed control method.
Du et al. (Fri,) studied this question.