相关论文: Fast Hybrid PSO and Tabu Search Approach for Optim…

The aim of this research is to design a PID Controller using particle swarm optimization (PSO) algorithm for multiple-input multiple output (MIMO) Takagi-Sugeno fuzzy model. The conventional gain tuning of PID controller (such as…

The Particle Swarm Optimized (PSO) fuzzy controller has been proposed for indirect vector control of induction motor. In this proposed scheme a Neutral Point Clamped (NPC) multilevel inverter is used and hysteresis current control technique…

This paper investigates the controller optimization for a helicopter system with three degrees of freedom (3-DOF). To control the system, we combined fuzzy logic with adaptive control theory. The system is extensively nonlinear and highly…

This paper presents a new optimal fuzzy approach based on particle swarm optimization evolutionary algorithm for controlling the servo actuating system. It is clear that attaining the maximum stability margin is the prominent goal in…

Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO) are nature-inspired, swarm-based optimization algorithms respectively. Though they have been widely used for single-objective optimization since their inception,…

L1 adaptive controller has been recognized for having a structure that allows decoupling between robustness and adaption owing to the introduction of a low pass filter with adjustable gain in the feedback loop. The trade-off between…

Hardware security vulnerabilities in computing systems compromise the security defenses of not only the hardware but also the software running on it. Recent research has shown that hardware fuzzing is a promising technique to efficiently…

This paper investigates the operation of a hybrid power system through a novel fuzzy control scheme. The hybrid power system employs various autonomous generation systems like wind turbine, solar photovoltaic, diesel engine, fuel-cell, aqua…

Depth control of underwater vehicles in engineering applications must simultaneously satisfy requirements for rapid tracking, low overshoot, and actuator constraints. Traditional fuzzy PID tuning often relies on empirical methods, making it…

Combinatorial interaction testing is an important software testing technique that has seen lots of recent interest. It can reduce the number of test cases needed by considering interactions between combinations of input parameters.…

This dissertation addresses the growing challenge of air traffic flow management by proposing a simulation-based optimization (SbO) approach for multi-objective runway operations scheduling. The goal is to optimize airport capacity…

Particle Swarm Optimisation (PSO) is a powerful optimisation algorithm that can be used to locate global maxima in a search space. Recent interest in swarms of Micro Aerial Vehicles (MAVs) begs the question as to whether PSO can be used as…

During the last decades, a myriad of fuzzy time series models have been proposed in scientific literature. Among the most accurate models found in fuzzy time series, the high-order ones are the most accurate. The research described in this…

In this paper, the stability and stabilization problem of positive nonlinear systems, described by the Takagi-Sugeno discrete-time fuzzy model, is studied. The proposed approach is based on the linear co-positive Lyapunov function and…

In this paper, we propose a new approach to automatically retrieve the first-order design of double-sided telecentric zoom systems with high efficiency based on Particle Swarm Optimization (PSO) algorithms. We transform the design problem…

The prediction of uncertain and predictive nonlinear systems is an important and challenging problem. Fuzzy logic models are often a good choice to describe such systems however in many cases these become complex soon. commonlly, too less…

Feature selection is the process of identifying statistically most relevant features to improve the predictive capabilities of the classifiers. To find the best features subsets, the population based approaches like Particle Swarm…

The particle swarm optimization (PSO) algorithm has been recently introduced in the non--linear programming, becoming widely studied and used in a variety of applications. Starting from its original formulation, many variants for…

Particle Swarm Optimization technique offers optimal or suboptimal solution to multidimensional rough objective functions. In this paper, this optimization technique is used for designing fractional order PID controllers that give better…

Particle Swarm Optimization (PSO) has demonstrated efficacy in addressing static path planning problems. Nevertheless, such application on dynamic scenarios has been severely precluded by PSO's low computational efficiency and premature…