scholarly journals Piecewise Model and Parameter Obtainment of Governor Actuator in Turbine

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jie Zhao ◽  
Li Wang ◽  
Dichen Liu ◽  
Jun Wang
Keyword(s):  
Pid Controller ◽  
Particle Swarm Optimization Algorithm ◽  
Piecewise Linear ◽  
Heat Engine ◽  
Experimental Tests ◽  
Proportional Integral Derivative ◽  
Closing Time ◽  
Time Constants ◽  
Piecewise Model ◽  
Opening And Closing

The governor actuators in some heat-engine plants have nonlinear valves. This nonlinearity of valves may lead to the inaccuracy of the opening and closing time constants calculated based on the whole segment fully open and fully close experimental test curves of the valve. An improved mathematical model of the turbine governor actuator is proposed to reflect the nonlinearity of the valve, in which the main and auxiliary piecewise opening and closing time constants instead of the fixed oil motive opening and closing time constants are adopted to describe the characteristics of the actuator. The main opening and closing time constants are obtained from the linear segments of the whole fully open and close curves. The parameters of proportional integral derivative (PID) controller are identified based on the small disturbance experimental tests of the valve. Then the auxiliary opening and closing time constants and the piecewise opening and closing valve points are determined by the fully open/close experimental tests. Several testing functions are selected to compare genetic algorithm and particle swarm optimization algorithm (GA-PSO) with other basic intelligence algorithms. The effectiveness of the piecewise linear model and its parameters are validated by practical power plant case studies.

Crane Lift-Off Control of Inclined Payloads

2017 ◽  
Author(s):  
Michael J. Toth ◽  
Colby F. Lewallen ◽  
Joseph C. Hanson ◽  
Shenghai Wang ◽  
William Singhose
Keyword(s):  
Pid Controller ◽  
Experimental Tests ◽  
Peak Amplitude ◽  
Level Surface ◽  
Proportional Integral Derivative ◽  
Construction Sites ◽  
Residual Vibration ◽  
Proportional Integral ◽  
Lift Off ◽  
Inclined Surface

It is difficult for crane operators to lift and maneuver payloads without causing significant, uncontrolled motion. Consequently, research in the area of crane operation has focused on designing controllers to minimize payload swing. However, lifting long and slender payloads (e.g., steel I-beams) from a non-level surface (e.g., like many outdoor construction sites) has not been addressed in much detail. This paper evaluates the amplitude of residual swing and robustness of two different control methodologies while hoisting a slender payload up into the air from an inclined surface. A semi-automatic approach, where the crane operator controls the lift direction and a proportional-integral-derivative (PID) controller adjusts the overhead trolley position, was developed. Experimental tests demonstrate that this method reduces the peak amplitude of residual vibration by about 80% for most non-zero incline angles.

Establishment and comparison of a spatial dynamics model for virtual track train with different steering modes

2021 ◽  
pp. 146441932110240
Author(s):  
Zhonghui Yin ◽  
Jiye Zhang ◽  
Haiying Lu
Keyword(s):  
Pid Controller ◽  
Dynamic Performance ◽  
Spatial Dynamics ◽  
Steering System ◽  
Front Wheel ◽  
Proportional Integral Derivative ◽  
Dynamics Model ◽  
Proposed Model ◽  
Suspension Control ◽  
Curved Section

To solve the urbanization and the economic challenges, a virtual track train (VTT) transportation system has been proposed in China. To evaluate the dynamic behavior of the VTT, a spatial dynamics model has been developed that considers the suspension system and the steering system. Additionally, the model takes into account road irregularity to make simulations more realistic. Based on the newly proposed dynamic model and a designed proportional–integral–derivative (PID) controller, simulation frames of the vehicle and of the VTT are established with the path-tracking performance. The results show that the vehicle and the VTT can run along a desired lane with allowable errors, verifying the proposed model. The vehicle and VTT with the four-wheel steering system show a better dynamic performance than the models with the front-wheel steering system in the curved section. Moreover, the simulation frame can be further applied to dynamics-related assessments, parameter optimization and active suspension control strategy.

scholarly journals The Adaptive Power of Ammophila arenaria: Biomimetic Study, Systematic Observation, Parametric Design, and Experimental Tests with Bimetal

Polymers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2554
Author(s):  
Tarciana Araújo Brito de Andrade ◽  
José Nuno Dinis Cabral Beirão ◽  
Amilton José Vieira de Arruda ◽  
Cristina Cruz
Keyword(s):  
Parametric Design ◽  
Experimental Tests ◽  
Ammophila Arenaria ◽  
Systematic Observation ◽  
Natural Movement ◽  
Biomimetic Approach ◽  
Three Stages ◽  
Adaptive Power ◽  
Response To Temperature ◽  
Opening And Closing

The aim of our study was to apply a biomimetic approach, inspired by the Ammophila arenaria. This organism possesses a reversible leaf opening and closing mechanism that responds to water and salt stress (hydronastic movement). We adopted a problem-based biomimetic methodology in three stages: (i) two observation studies; (ii) how to abstract and develop a parametric model to simulate the leaf movement; and (iii) experiments with bimetal, a smart material that curls up when heated. We added creases to the bimetal active layer in analogy to the position of bulliform cells. These cells determine the leaf-closing pattern. The experiments demonstrated that creases influence and can change the direction of the bimetal natural movement. Thus, it is possible to replicate the Ammophila arenaria leaf-rolling mechanism in response to temperature variation and solar radiation in the bimetal. In future works, we will be able to propose responsive facade solutions based on these results.

An H∞ Design Approach for a PID Automatic Flight Control System of a Launch Vehicle

2016 ◽  
Vol 859 ◽  
pp. 116-123
Author(s):  
Adrian Mihail Stoica ◽  
Mihaela Raluca Stefanescu
Keyword(s):  
Flight Control ◽  
Pid Controller ◽  
Design Methodology ◽  
Launch Vehicle ◽  
Proportional Integral Derivative ◽  
Flight Control System ◽  
Numerical Examples ◽  
Stability Robustness ◽  
Norm Minimization ◽  
Atmospheric Disturbances

The paper presents a design methodology for the automatic flight control of a launch vehicle. In the proposed approach the controller has a PID (Proportional-Integral-Derivative) structure but its gains are determined solving an H∞ norm minimization problem of the mapping from the atmospheric disturbances to the control amplitude and to the angle of attack of the launcher. The design methodology is illustrated by numerical examples in which both time responses and stability robustness properties of the optimal PID controller are analyzed.

PSO-Based Tunning of PID Controller for Speed Control of DC Motor

2014 ◽  
Vol 7 (3) ◽  
pp. 65-79
Author(s):  
Ibrahem S. Fatah
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Dc Motor ◽  
Proportional Integral Derivative ◽  
Stable Convergence ◽  
Swarm Optimization ◽  
Tuning Parameters ◽  
Pid Controller Tuning ◽  
Rising Time

In this paper, a Proportional-Integral-Derivative (PID) controller of DC motor is designed by using particle swarm optimization (PSO) strategy for formative optimal PID controller tuning parameters. The proposed approach has superior feature, including easy implementation, stable convergence characteristics and very good computational performances efficiency. The DC Motor Scheduling PID-PSO controller is modeled in MATLAB environment. Comparing with conventional PID controller using Genetic Algorithm, the planned method is more proficient in improving the speed loop response stability, the steady state error is reduced, the rising time is perfected and the change of the required input do not affect the performances of driving motor with no overtaking.

DEVELOPMENT OF ANN-BASED PID CONTROLLER FOR ACTIVE FLUID-FILM BEARING CONTROL

2020 ◽  
Vol 6 ◽  
pp. 94-100
Author(s):  
N.N. MAKHOVA ◽  
A.Yu. BABIN
Keyword(s):  
Neural Network ◽  
Pid Controller ◽  
Particle Swarm Optimization Algorithm ◽  
Fluid Film ◽  
Training Dataset ◽  
Swarm Optimization ◽  
Controlled System ◽  
Active Fluid ◽  
Control Scheme ◽  
Controlled Object

The article proposes a method for controlling an active fluid-film bearing, based on the use of a classical PID controller in conjunction with an artificial neural network. The regulator coefficients are not constant numbers, but are chosen by the network depending on the state of the controlled system. To implement such a control scheme, the coefficients are selected using a particle swarm optimization algorithm, which constitutes the training dataset, and an ANN is trained using the dataset. The controlled object is represented with a model operating in the Simulink environment.

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