Industrial cameras cannot clearly observe targets in real time in overexposed lighting conditions with sudden changes in brightness. An adaptive exposure control method is proposed to address this problem. First， the weighted average gray value of an image of a preset reference area is calculated， and then， the exposure value is calculated for the image. Next， a parameter control optimization method based on an improved "S" curve is designed to optimize and adjust the internal parameters. Finally， the optimal level of clarity is obtained with reference to the preset position. Experimental results show that the proposed method takes approximately 0.08 s to complete the entire camera adjustment process. Compared with those of the automatic exposure algorithm implemented on the camera hardware and an adaptive exposure algorithm based on image histogram features under the same conditions， the average standard deviation of the Laplacian of the images produced by the proposed algorithm is 54.3% and 20.6% greater， respectively. Therefore， the proposed algorithm can effectively enhance the adaptability of the optimized cameras under conditions of sudden changes in brightness and can be implemented in various practical applications.