Harmony search-based robust optimal controller with prior defined structure - Rafieishahemabadi, Ali (2013)
Complexity, high order, and unknown structure of robust controller design methods making their implementation unsuitable in industry. To bridge the gap between the theoretical and industrial robust controller designs, a strategy is proposed which involves the design of a robust optimal controller based on harmony search (HS) optimization algorithm with predefined structure, which fulfils the robust stability and performance requirements for SISO linear time-invariant feedback control systems. In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. The second level compnses of two HS optimization algorithms developed and coded for robust stability examinations. Constraints are formulated based on controller variables. Initially, the proposed design method is exploited to design control laws for two different arbitrary structures for a flexible link manipulator used as a benchmark problem for the Hs, and recent robust H; PID based on particle swarm optimization (PSO) controllers. The results confirm the obtained two controller structure by the proposed method improve performance evaluating criteria in comparison to Hs, PID based on PSO controller. In terms of robustness, both design methods show the same performance. However, the harmony search-based robust optimal controller (HSRO) controller is superior to Hi; PID based on PSO controller when a different controller structure is needed. Furthermore, the obtained controllers are superior to the conventional H; design technique due to its simpler and flexible structure as well as zero steady state error resulted in better tracking and performance behaviour. For further assessment, the proposed design strategy is then employed to design a control law for an electrical DC drive velocity controller used as a benchmark problem for the recent PSO-based and genetic algorithm optimization (GAO)-based robust controllers. The results verified that the effect of the uncertainty acting on the plant is less when using proposed control design strategy. It is found that HSRO controller is superior to PSO-based and GAO-based controllers in both performance and robustness. Eventually, the proposed approach was adopted for a MIMO nonlinear twin rotor motor system (TRMS) for further implementation and evaluation in practical application. The method was successfully exploited to decouple the linearized plant to two SISO plants. Using the proposed strategy, the arbitrary predefined controllers were tuned to achieve the desired robustness and tracking capability. The results reveal that the decoupled HSRO controller is superior to MIMO LQR and PID based on LQR controllers in both, performance, and robustness. As a whole, the study shows that the proposed HSRO controller with the capability of selecting prior defined and flexible structure is very promising to be employed in many control problems.