In this research work proposed MPSO methods for nonlinear complex processes. These processes are implemented in various process control industries, Design and development of new controller to increase the better stability and improve the performance index. This paper goal the minimize parameters for process controller by Taguchi method combined mutation particle swarm optimization algorithm for industrial laboratory highly complex nonlinear QTS. Analysis of means techniques analyses the meaning of means which are effectively different from the output responses combined means to detect nearer values of PID controller parameters while ANOVA method determines the two most effective parameters with the response of Quadruple tanks system. The result shows that TMPSO technique is provided the good result when compared with other approaches. The TMPSO techniques use for setting controller offers enhanced process specification such as better time domain specifications, smooth error reference tracking, remove the coupling effect and minimization of error in the nonlinear system.