Currently, there exist many traditional PID (Proportional-Integral-Derivative) controller tuning methods for the unconstrained single-objective optimization problems. However, when dealing with multi-objective optimization problems, the traditional methods face many theoretical challenges. Furthermore, the situations may be even worse in the presence of multi-constraint requirements. In the view of above situations, by applying the heavy tailed -distribution (HTD) sequences into the basic cuckoo search (CS) algorithm, we firstly propose a novel HTD-CS-based PID controller tuning method for the multi-objective and multi-constraint optimization problems. In this proposed swarm intelligent optimization algorithm, the introduction of HTD sequences represents a novel heavy-tailed search strategy in order to improve the search performance. Thus, in terms of achieving global optimization, the modified HTD-CS algorithm can provide more accurate PID parameter estimates. The simulation experiments verify that the proposed algorithm is quite efficient. (C) 2016 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.