This chapter considers norm optimal iterative learning control design with constraints. Two classes of constraints are discussed, namely, hard constrains and soft constraints. For the former, a successive projection framework is used to develop two constrained iterative learning control algorithms; for the latter, the problem is formulated as an auxiliary optimization problem for which two switching algorithms are provided. The convergence properties of the algorithms are analysed in detail and illustrated via examples.