This article aims to handle the optimal attitude tracking control tasks for rigid bodies via a reinforcement-learning-based scheme, in which constrained parameter estimator is designed compensate system uncertainties accurately. guarantees exponential convergence of estimation errors and can strictly keep all instant estimates always within predetermined bounds. Based on it, critic-only adaptiv...
