This paper considers the use of constrained minimum crest factor multisine signals as inputs for plant-friendly identification testing of chemical process systems. The approach developed in this paper greatly increases their effectiveness in a process control setting by enabling the user to simultaneously specify important frequency and time-domain characteristics of these signals. Two problem formulations meaningful to both linear and nonlinear identification problems are presented. State-of-the-art computational methods are needed to solve the challenging optimization problems associated with crest factor minimization.