Improved Cascade Chaotic Invasive Weed Optimization Algorithm (ICCIWO), application to controller tuning and optimization

An Improved Cascade Chaotic Invasive Weed Optimization Algorithm (ICCIWO) is proposed, employing cascade chaotic maps in the structure of a metaheuristic optimisation algorithm. The main aim of this modification is to provide a new algorithm for tuning the parameters of controllers. Conventionally, invasive weed optimisation algorithms (IWO) have been utilised in the literature to solve optimisation problems. The IWO has merits, namely fast convergence and high extraction capability. However, the IWO suffers from a lack of population diversity and poor exploration. Two novel improvements are proposed here to eliminate these disadvantages, based on utilising chaotic behaviours in the population generation and in the standard deviation update rule. The final proposed mechanism is applied to tune the parameters of a PID controller and solve several benchmark optimisation problems. Simulation analysis compares the performance of the proposed method with a recent similar approach. The simulation results validate the high performance of the proposed novel cascade chaotic scheme.