The brushless excitation system of aircraft AC generator is a strong coupled and nonlinearity dynamic system which is often being subjected to disturbances. Therefore, the conventional PID controller is unable to meet the brushless excitation system control requirements of More Electric Aircraft (MEA) or All Electric Aircraft (AEA). A new brushless excitation compound control controller (RBFPID...

An optimization methodology for the combination of several green technologies is introduced in this paper. These are smart meters, smart appliances, solar power systems and time-of-use (TOU) pricing. These technologies are collectively and widely utilized in the recent smart grid, which is rolling out all over the world to facilitate greener power generation and distribution. Adaptive particle ...

Abstract Most of the current mine hoists use PID controllers for speed adjustment, and there are problems such as long adjustment time, excessive reliance on experience, easy overshoot oscillation. In order to solve above-mentioned problems, it is planned adaptive particle swarm optimization based simulated annealing (SA-APSO) algorithm optimize parameters controller, conduct simulation experim...

This paper assumes each user has more than one queue, derives a new packet-dependant proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new cross-layer packet-dependant OFDM scheduling schemes based on proportional fairness for heterogeneous classes of traffic. Scenario 1, scenario 2 and scenario 3 lead r...

An imaging approach to clear detection of two-dimensional geometries is proposed in this paper. The imaging reconstruction of multiple dielectric objects is retrieved by finite difference time domain (FDTD) method and the asynchronous particle swarm optimization (APSO) to determine the shape, location and permittivity of each dielectric object. The forward problem is solved based on the subgrid...

In solving the portfolio optimization problem, mean-semivariance (MSV) model is more complicated and time-consuming, their relations are unbalanced because they conflict with each other due to return risk. Therefore, in order solve these existing problems, multi-strategy adaptive particle swarm optimization, namely APSO/DU, has been developed problem. present study, a constraint factor introduc...

in this paper, a new enhanced version of the particle swarm optimization (pso) is presented. an important modification is made by adding probabilistic functions into pso, and it is named probabilistic particle swarm optimization (ppso). since the variation of the velocity of particles in pso constitutes its search engine, it should provide two phases of optimization process which are: explorati...

Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. These networks can be trained with gradient descent back propagation. The algorithm is not definite in finding the global minimum of the error function since gradient descent may get stuck ...