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An integrated direct/indirect adaptive robust controller (DIARC) is proposed to further improve the achievable posture trajectory tracking control performance of a parallel manipulator driven by pneumatic muscles. Due to the model errors of the static forces and friction forces of pneumatic muscles, the simplified average flow rate characteristics of valves, and the unknown disturbances of entire system, there exist large extent of parametric uncertainties and rather severe uncertain nonlinearities in the modeling of the parallel manipulator. To address these problems, in this paper, an indirect type parameter estimation is used to obtain reliable estimates of effective model parameters for reducing the parametric uncertainties while an integrated direct/indirect ARC with dynamic compensation type fast adaptation is utilized to further attenuate the influences of uncertain nonlinearities for better tracking performance. Considering that the conventional parameter estimation algorithm based on single error minimizing criterion normally fails to provide reliable parameter estimation for the parallel manipulator with symmetric structure due to the difficulty in satisfying the persistent exciting conditions all the time-the theoretical requirement for the convergence of online parameter estimation, additional practical constraints are imposed to further condition the parameter estimation process and a new parameter estimation algorithm based on composite error minimizing criterion in task-space is developed. Experimental results demonstrate that the parallel manipulator under the control of the proposed integrated DIARC has strong self-adaptability and robustness with the steady-state posture tracking error being less than 0.01deg, average tracking error less than 0.1deg, and maximum tracking error less than 0.3deg, which are significantly better than those of the direct ARC.