Learning Automata based Set-point weighted parameter for unstable systems

A simple method using Learning Automata is given for selection of the set point weighting parameter (b) in PI controllers for unstable first-order plus time delay systems.The parameter (b) is selected, based on the state transition probabilities to reduce the over shoot for a servo problem. The performance evaluation of the control action is carried out by using the reinforcement scheme based on reward-penalty and accordingly state transition probabilities are updated. The learning automata consider the updated state transition probabilities as input and tuning parameter (b) as output. The responses of PI controllers without and with the set point weighting are compared.