Papers by Keyword: Mutative Scale

Abstract: In view of the disadvantage existing in stochastic programming and fuzzy programming that in the process of modeling of wind power both of them need a huge amount of historical data information to establish precise model, and the advantage of interval planning that it only need to know the upper and lower bounds of the variable in the uncertainty modeling and interval variables contains more information than real variables, this paper puts forward the interval model of the wind power, and use the interval possible degree to deal with the interval constraint conditions. At the same time, this paper adopted the chaotic particle swarm optimization algorithm based on logic from the map to solve the model. Finally, the paper proved the accuracy and effectiveness of the model and algorithm by an example.

Abstract: A novel method based on the mutative scale chaos optimization algorithm is proposed to solve the robust reliability index of non-probabilistic reliability model. Compared with the basic chaos optimization method, this novel method can minimize searching area of optimization variable and change the adjustable parameters of next search stage for improving the optimization performance. The proposed optimization algorithm is more efficient and has smaller computational complexity in solving robust reliability index. The feasibility and efficiency of the proposed method are demonstrated by two examples.

Abstract: The permanent magnetic spherical stepper motor model is introduced in this paper, random encoder is painted on the rotor surface, and outputs of 96 optoelectronic sensors are used to identify rotor orientation. Based on the special structure and rotational character, the paper uses an improved mutative scale chaos search algorithm to mapping the dynamics equation of chaos variable to the orientation space. When the number of either local minima or cycles is equal to the initial value, the search space is dynamically reduced. Simulation shows that the search method is simple and has ability of fast convergence to the goal orientation, thus the search efficiency is improved.

Abstract: Ergodicity is the outstanding character of chaos system, and chaotic variables can be used to approach global optimal point. Aiming at the control requirements for position and speed of mobile robot, a compact PID controller parameters optimization strategy based on mutative scale chaos optimization algorithm is proposed. The Kinematics model of the soccer robot system is introduced, and the strategy of chaos optimization PID controller parameters is discussed. This optimal solution needs no prior knowledge, searches the whole parameter’s space efficiently and finds the optimal parameter, according to the given performance criteria. Simulation results show that this strategy is feasible and effective.

Abstract: In order to avoid blind searching before reducing the searching space of optimized variable and enhance searching efficiency in chaos optimization algorithm, a new mutative scale chaos optimization algorithm, Probability Chaos Optimization Algorithm (PCOA) was proposed. The current searching space is searched according to large probability and the origin space is searched according to small probability. Though the searching space is shrunk prematurely, the global optimal point can be found because the origin space is still searched according to small probability, which can overcome the shortcoming of losing the global optimal points owing to prematurely shrinking the searching space of the optimized variables in conventional mutative scale chaos optimization algorithm. The simulation results prove the validity of the algorithm.