Combined Active and Passive Loads Alleviation through Aeroelastic Tailoring and Control Surface/Control System Optimization

Digital Clay is an NSF funded project for human machine communication through a tangible haptic surface actuated by fluid power. Digital Clay's hardware can be divided into three subsystems: massive actuator-sensor array, fluidic driving system, and control system. The main focus of this paper is on the control issues of the massive actuator array of Digital Clay. Categorized by the function of control algorithms, the control system can be further divided into three levels: cell control, surface control, and user application interface. Analysis and testing results of above introduced topics are provided based on a 5×5 actuator array prototype. Most of the topics discussed in this paper are widely applicable not just for this specific device.

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Robust NSV Fault-Tolerant Control System Design Against Actuator Faults and Control Surface Damage Under Actuator Dynamics

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2015.2450714 ◽

2015 ◽

Vol 62 (9) ◽

pp. 5919-5928 ◽

Cited By ~ 59

Author(s):

Dezhi Xu ◽

Bin Jiang ◽

Peng Shi

Keyword(s):

Control System ◽

System Design ◽

Fault Tolerant ◽

Fault Tolerant Control ◽

Surface Damage ◽

Control Surface ◽

Control System Design ◽

Actuator Faults ◽

Actuator Dynamics ◽

And Control

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A Framework for Fused Experimental/Numerical Plant and Control System Optimization Using Iterative G-Optimal Design of Experiments

Volume 2A: 42nd Design Automation Conference ◽

10.1115/detc2016-60488 ◽

2016 ◽

Cited By ~ 4

Author(s):

Nihar Deodhar ◽

Christopher Vermillion

Keyword(s):

Control System ◽

Optimal Design ◽

Design Of Experiments ◽

Center Of Mass ◽

System Optimization ◽

Energy System ◽

Experimental Results ◽

Optimal Design Of Experiments ◽

Wind Energy System ◽

And Control

This paper presents a methodology for optimally fusing experiments and numerical simulations in the design of a combined plant and control system. The proposed methodology uses G-optimal Design of Experiments to balance the need for experimental data with the expense of collecting a multitude of experimental results. Specifically, G-optimal design is used to first select a batch of candidate experimental configurations, then determine which of those points to test experimentally and which to numerically simulate. The optimization process is carried out iteratively, where the set of candidate design configurations is shrunken at each iteration using a Z-test, and the numerical model is corrected according to the most recent experimental results. The methodology is presented on a model of an airborne wind energy system, wherein both the center of mass location (plant parameter) and trim pitch angle (controller parameter) are critical to system performance.

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Design and Simulation of Air to Air Missile Homing System

INSIST ◽

10.23960/ins.v2i2.84 ◽

2019 ◽

Vol 2 (2) ◽

pp. 75

Author(s):

Rahmat Alfi Duhri ◽

Rianto Adhy Sasongko ◽

Yayom Dwi Laksmana

Keyword(s):

Control System ◽

General Purpose ◽

Guidance System ◽

Control Surface ◽

System Control ◽

Missile Guidance ◽

Proportional Navigation ◽

Simulink Model ◽

Non Linear Equation ◽

And Control

This paper will talk about AIM 120 AMRAAM missile guidance for pursuing a moving target. The missile guidance system itself consists of missile dynamics, control system, seeker, and guidance methods. For general purpose, the missile dynamics approach will use non-linear equation of motions. The control surface that will be discussed follow the rule BTT (Bank-to-Turn) and control system that will be used is PID control system that widely used for control design. Lastly, the guidance method that will be studied here is proportional navigation and constant bearing course approach. The simulation will be conducted using MATLAB Simulink. The Simulink model consist of target dynamics, and guidance system. From the result of simulation, it will be shown that the missile can pursue its target quite well. Hence, the simulation system can be used well for preliminary design purpose.Keywords—Homing System, Control System, Proportional Navigation, Missile Dynamics, Seeker, Bank-to-Turn, Constant Bearing Course.

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Reconfiguration of Unmanned Aircraft Control System

Transactions on Aerospace Research ◽

10.2478/tar-2017-0017 ◽

2017 ◽

Vol 2017 (2) ◽

pp. 80-96

Author(s):

Marcin Żugaj

Keyword(s):

Control System ◽

Unmanned Aircraft ◽

Control Surface ◽

Control Input ◽

Aircraft Control ◽

System Failures ◽

System Reconfiguration ◽

And Control ◽

Control Surfaces ◽

Aircraft Control System

Abstract Reliability of unmanned aircraft is a decisive factor for conducting air tasks in controlled airspace. One of the means used to improve unmanned aircraft reliability is reconfiguration of the control system, which will allow to maintain control over the aircraft despite occurring failures. The control system is reconfigured by using operational control surfaces, to compensate for failure consequences and to control the damaged aircraft. Development of effective reconfiguration algorithms involves utilization of a non-linear model of unmanned aircraft dynamics, in which deflection of each control surface can be controlled independently. The paper presents a method for an unmanned aircraft control system reconfiguration utilizing a linear and nonlinear model of aerodynamic loads due to control. It presents reconfiguration algorithms, which differ with used models and with optimization criteria for deflections of failure-free control surfaces. Additionally it presents results of a benchmark of the developed algorithms, for various types of control system failures and control input.

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Development of a Jacobian Module for Advanced Pulp and Paper Simulation and Control

TAPPI Journal ◽

10.32964/tj8.1.4 ◽

2009 ◽

Vol 8 (1) ◽

pp. 4-11

Author(s):

MOHAMED CHBEL ◽

LUC LAPERRIÈRE

Keyword(s):

Control System ◽

Nonlinear Behavior ◽

Simulation Software ◽

Pulp And Paper ◽

Pid Controllers ◽

Tuning Parameters ◽

Pid Tuning ◽

Fixed Set ◽

And Control ◽

Operating Points

Pulp and paper processes frequently present nonlinear behavior, which means that process dynam-ics change with the operating points. These nonlinearities can challenge process control. PID controllers are the most popular controllers because they are simple and robust. However, a fixed set of PID tuning parameters is gen-erally not sufficient to optimize control of the process. Problems related to nonlinearities such as sluggish or oscilla-tory response can arise in different operating regions. Gain scheduling is a potential solution. In processes with mul-tiple control objectives, the control strategy must further evaluate loop interactions to decide on the pairing of manipulated and controlled variables that minimize the effect of such interactions and hence, optimize controller’s performance and stability. Using the CADSIM Plus™ commercial simulation software, we developed a Jacobian sim-ulation module that enables automatic bumps on the manipulated variables to calculate process gains at different operating points. These gains can be used in controller tuning. The module also enables the control system designer to evaluate loop interactions in a multivariable control system by calculating the Relative Gain Array (RGA) matrix, of which the Jacobian is an essential part.

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