A Fractional-Order On-Line Self Optimizing Control Framework and a Benchmark Control System Accelerated Using Fractional-Order Stochasticity

This paper presents a design and evaluation of fractional-order self optimizing control (FOSOC) architecture for process control. It is based on real-time derivative-free optimization layer that adjusts the parameters discrete-time proportional integral (FOPI) controller according to an economic cost function. A simulation benchmark designed assess performance FOSOC first order plus dead time system. Similarly, acceleration mechanism proposed framework employing Gaussian noise with long-range dependence given by Hurst exponent. The obtained results show can improve system closed-loop response under different operating conditions reduce convergence algorithm using stochasticity.