Optimization of Interval Type-2 Fuzzy Logic Controller Using Real-Coded Quantum Clonal Selection Algorithm

In recent years, quantum computing has gained immense popularity with the production of real computers. Researchers have developed quantum-inspired evolutionary algorithms (QIEAs) to solve combinatorial optimization problems and obtained successful results. As a special case QIEAs, real-coded algorithm (RCQEA) is used in high-dimensional complex problems. this study, novel mechanism rotation gate (QRG) that determine angle qubit RCQEA introduced implemented accelerate process increase possibility finding optimal solution. Moreover, skeleton modified by using clonal selection mechanism, (RCQCSA) developed. Our proposed QRG accelerates convergence speed algorithm. The main purpose study present more effective inspires principles for optimizing interval type-2 fuzzy logic controller (IT2FLC) membership functions (MFs). four different comparisons are made these two original version our QRG. Optimized IT2FLC provides stabilization inverted pendulum system. results show RCQCSA having outperforms stabilizing system parameters.