To solve the tensor completion problem, a cyclic algorithm for low rank tensor completion is proposed. Based on the alternating direction multiplier method, the sub-problem is circularly updated, which effectively reduces the cost of tensor expansion, matrix folding and singular value decomposition in the iterative process. At the same time, the convergence analysis of the algorithm is given under reasonable assumptions. Finally, the numerical experiments show that the proposed algorithm is more efficient than other algorithm.