The optimization problem for multi-variable industrial high-efficiency control systems is to find the optimal parameters that could minimize the errors. In order to get such a stable control system, various control tuning methods were proposed by many researchers, but still, it is a challenge to get an effective controlled system. In this work, a method is proposed in order to attain a stable control system, called Error Recursion -Reduction Computational (ERRC) technique. Two processes, level, and flow are considered; their respective process models are identified and validated. The performance of the proposed technique has verified by implementing real-time transducers' interfaced experimental process. Results are compared with the conventional PID tuning technique and by optimization algorithms. The proposed experimental results show that better closed-loop performance can be achieved than other tuning techniques.

In this paper, Complex Fuzzy Graph (CFG) analyzed and introduced new concepts in CFG such as Spanning CFG, Complete CFG, path, arc, length, connected, strongest path and weakest path of CFG. We derived some properties of self complementary CFG and defined the operations on direct product, Semi strong product and strong product of CFG. Derived Isomorphic CFG with example is given in this paper. Moreover we introduced density of the graph and balanced complex fuzzy graph.