Controller Design based on Polynomial Evolution Using Multi-Objective Genetic Programming
نویسندگان
چکیده
Genetic programming (GP) is extensively used for structure and parameter tuning of control systems. This paper describes an application of genetic programming for Pareto biobjective design of polynomial based controllers for some common time-delay systems. In this way, a multi-objective uniform-diversity genetic programming proposed and used for polynomial controller evolution. The ε-elimination diversity is used to improve the population diversity among the obtained Pareto front. The objective functions considered are namely, integral time absolute error (ITAE) and control effort. Additionally, the obtained Pareto fronts and some performance measures of the designed controllers compared with that of obtained by other known methods.
منابع مشابه
Power System Stability Improvement via TCSC Controller Employing a Multi-objective Strength Pareto Evolutionary Algorithm Approach
This paper focuses on multi-objective designing of multi-machine Thyristor Controlled Series Compensator (TCSC) using Strength Pareto Evolutionary Algorithm (SPEA). The TCSC parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a SPEA ...
متن کاملLoad Frequency Control in Power Systems Using Multi Objective Genetic Algorithm & Fuzzy Sliding Mode Control
This study proposes a combination of a fuzzy sliding mode controller (FSMC) with integral-proportion-Derivative switching surface based superconducting magnetic energy storage (SMES) and PID tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. The goal of design is to improve the dynamic response of power systems after load demand changes. In t...
متن کاملRobust optimal multi-objective controller design for vehicle rollover prevention
Robust control design of vehicles addresses the effect of uncertainties on the vehicle’s performance. In present study, the robust optimal multi-objective controller design on a non-linear full vehicle dynamic model with 8-degrees of freedom having parameter with probabilistic uncertainty considering two simultaneous conflicting objective functions has been made to prevent the rollover. The obj...
متن کاملOptimum sliding mode controller design based on skyhook model for nonlinear vehicle vibration model
In this paper a new type of multi-objective differential evolution employing dynamically tunable mutation factor is used to optimally design non-linear vehicle model. In this way, non-dominated sorting algorithm with crowding distance criterion are combined to fuziified mutation differential evolution to construct multi-objective algorithm to solve the problem. In order to achieve fuzzified mut...
متن کاملModeling and Multi-Objective Optimization of Stall Control on NACA0015 Airfoil with a Synthetic Jet using GMDH Type Neural Networks and Genetic Algorithms
This study concerns numerical simulation, modeling and optimization of aerodynamic stall control using a synthetic jet actuator. Thenumerical simulation was carried out by a large-eddy simulation that employs a RNG-based model as the subgrid-scale model. The flow around a NACA0015 airfoil, including a synthetic jet located at 10 % of the chord, is studied under Reynolds number Re = 12.7 × 106 a...
متن کامل