Computational intelligence PC tools
Computational intelligence PC tools
Modern Control Engineering
Developing Professional Java Applets
Developing Professional Java Applets
Java Developers Guide; With Cdrom
Java Developers Guide; With Cdrom
Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
An Introduction to Computer Simulation Methods: Applications to Physical Systems (3rd Edition)
An Introduction to Computer Simulation Methods: Applications to Physical Systems (3rd Edition)
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
Multiobjective optimization using dynamic neighborhood particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Adaptive particle swarm optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multi-objective pole placement with evolutionary algorithms
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
An improved multi-objective particle swarm optimizer for multi-objective problems
Expert Systems with Applications: An International Journal
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Information Sciences: an International Journal
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In this paper, Java programming with applets for internet-based control education of two mechanical systems are presented. First, a new multi-objective optimization method is applied to obtain the Pareto frontiers of some non-commensurable objective functions in the design of linear state feedback controllers for an inverted pendulum and a ball-beam system. Second, the simulations of the problems were developed with Java applets and its results are given. The obtained results and analyses demonstrate that this multi-objective method presented in this paper operates very well in terms of convergence speed, global optimality, solution accuracy, and algorithm reliability.