The stochastic parallel gradient descent (SPGD) algorithm had been proved to be an effective system control method of image clarity in experiments and applications, which is independent of wavefront sensor and can optimize the system performance directly. The convergence speed and stability are determined by the value of the control parameters. The ranges of the control parameters are narrow, and out of range will lead to the vibration of the convergence or reduce the convergence speed. Based on SPGD, an image clarity test bed is built with a 52-element deformable mirror and a position sensitive detector. A method of automatic adjustment of parameters is proposed. The principle of SPGD control algorithm was demonstrated through examining the effects of gain and perturbation amplitude on correction capability and convergence rate, and the new method is proved to be effective. Experimental results show that by using the method of automatic adjustment of parameters, the ranges of parameters are extended. The practicality and convergence speed of the algorithm are improved with better convergence stability.