LQG Vibration Control of Aircraft Panel Using Automated State Weighting Procedure

2005 ◽  
Author(s):  
T. C. Waite ◽  
Christopher E. Whitmer ◽  
Atul G. Kelkar
Keyword(s):  
Maximum Amplitude ◽  
Linear Quadratic Regulator ◽  
Initial Guess ◽  
Performance Comparison ◽  
System Response ◽  
Linear Quadratic ◽  
Cabin Noise ◽  
Automated Method ◽  
And Control ◽  
Error State

Optimal control theory has long been plagued by its inability to optimize the state and control weighting matrices specified in the LQR (Linear Quadratic Regulator) cost function. Although this control is optimal for a given set of user-defined state and control weighting matrices, the performance of the controller varies widely based on the selection of these weights. Engineers have been left with the task of choosing appropriate weighting sequences by iterating each weight until the controller performs to their satisfaction. This procedure gets increasingly more frustrating and time consuming as the size of the controller increases. The work in this paper outlines an effective strategy which reduces the engineer’s effort in finding these weights. It is shown that the introduction of an additional performance index along with the repeated perturbation of an initial guess quickly leads to a controller with excellent performance. Comparison of this automated method with a controller exhaustively designed using a standard selection method reveals a closed loop system response which has more energy reduction and more maximum amplitude reduction, all in a fraction of the time it takes to guess and check the weights. The controller will be applied to the model of an aircraft panel in an effort to reduce vibrations caused by wind. The goal is to achieve a reduction in cabin noise by controlling the vibration of such panels. The system identification procedure uses a modification of the SOCIT toolbox to achieve extremely accurate frequency domain system models. The model obtained using this method will then be used in the design and simulation of both the trial-and-error state weighted controller and the automated state weighted controller.

Analytical and Experimental Aeroelastic Wing Flutter Analysis and Suppression

2015 ◽  
Vol 15 (06) ◽  
pp. 1450084 ◽  
Author(s):  
Khalid A. Alsaif ◽  
Mosaad A. Foda ◽  
Hachimi Fellouah
Keyword(s):  
Nonlinear Models ◽  
Linear Quadratic Regulator ◽  
System Response ◽  
Linear Quadratic ◽  
Aeroelastic Response ◽  
Naca0012 Airfoil ◽  
Aerodynamic Model ◽  
Full State ◽  
Full State Feedback ◽  
And Control

Aeroelastic response and control of airfoil-flap wing exposed to unsteady aerodynamic loads is addressed. The aim is to suppress flutter and to maintain stability of the system. The analytical aerodynamic model is featuring plunging–pitching–flapping coupled motion. Both linear and nonlinear models are developed. Linear quadratic regulator theory is used to design a full state feedback controller in state-space. The control law is implemented through the flap torque to suppress flutter instability and enhance the aeroelastic response. The system response is investigated when it is flying beyond the flutter speed and the control is delayed by a few seconds. The effects of aircraft propeller excitation and the variation of the aspect ratio on the intitiation of flutter are investigated. Numerical simulations are complemented by experimental measurements in a wind tunnel for NACA0012 airfoil.

scholarly journals Mathematical Modelling and Control of a Two-Wheeled PUMA-LikeVehicle

2016 ◽  
Vol 6 (2) ◽  
pp. 11 ◽  
Author(s):  
Khaled M Goher
Keyword(s):  
Mathematical Modelling ◽  
Sliding Mode ◽  
Impact Load ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
The Body ◽  
Pole Placement ◽  
General Motors ◽  
Linear Quadratic ◽  
And Control

<p class="1Body">This paper presents mathematical modelling and control of a two-wheeled single-seat vehicle. The design of the vehicle is inspired by the Personal Urban Mobility and Accessibility (PUMA) vehicle developed by General Motors® in collaboration with Segway®. The body of the vehicle is designed to have two main parts. The vehicle is activated using three motors; a linear motor to activate the upper part in a sliding mode and two DC motors activating the vehicle while moving forward/backward and/or manoeuvring. Two stages proportional-integral-derivative (PID) control schemes are designed and implemented on the system models. The state space model of the vehicle is derived from the linearized equations. Controller based on the Linear Quadratic Regulator (LQR) and the pole placement techniques are developed and implemented. Further investigation of the robustness of the developed LQR and the pole placement techniques is emphasized through various experiments using an applied impact load on the vehicle.</p>

Modeling and Control of a Complex Interacting Process

2011 ◽  
Vol 403-408 ◽  
pp. 3758-3762
Author(s):  
Subhajit Patra ◽  
Prabirkumar Saha
Keyword(s):  
Storage System ◽  
Linear Quadratic Regulator ◽  
Model Parameters ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Dynamic Matrix ◽  
Liquid Storage ◽  
Efficient Control ◽  
And Control

In this paper, two efficient control algorithms are discussed viz., Linear Quadratic Regulator (LQR) and Dynamic Matrix Controller (DMC) and their applicability has been demonstrated through case study with a complex interacting process viz., a laboratory based four tank liquid storage system. The process has Two Input Two Output (TITO) structure and is available for experimental study. A mathematical model of the process has been developed using first principles. Model parameters have been estimated through the experimentation results. The performance of the controllers (LQR and DMC) has been compared to that of industrially more accepted PID controller.

Acoustic Control Modeling of Conical Bores With Actuating Boundary Conditions

2001 ◽  
Author(s):  
Kevin M. Farinholt ◽  
Donald J. Leo
Keyword(s):  
Boundary Conditions ◽  
Driving Forces ◽  
State Space Model ◽  
Linear Quadratic Regulator ◽  
Mode Shapes ◽  
Linear Quadratic ◽  
Acoustic Control ◽  
Average Control ◽  
The One ◽  
And Control

Abstract An investigation of the natural frequencies and mode shapes associated with sealed conical bores having actuating boundary conditions is presented. Beginning with the one dimensional wave equation for spherically expanding waves, modal characteristics are developed as functions of cone geometry and actuator parameters. This paper presents both analytical and experimental comparisons for the purpose of validating model and development techniques. An investigation of the orthogonality and adjointness of the solution is presented. A discussion of incorporating driving forces in the system model for the purpose of coupling control actuators with internal acoustics is also included. Including these driving forces, a state space model of the system is developed for the purpose of applying modern feedback control. This paper concludes with a study on applying Linear Quadratic Regulator techniques to this system, relating tradeoffs between spatially averaged pressure and control voltages. The results of our simulations indicate that pressure reductions of 30% are attainable with average control voltages of 14.4 volts, given an example geometry.

Compensator Design for a MEMS Gyroscope With Quadratic Optimal Control

2010 ◽  
Author(s):  
Wei Cui ◽  
Wei Xue ◽  
Xiaolin Chen
Keyword(s):  
Dynamic Range ◽  
Linear Quadratic Regulator ◽  
Control Algorithms ◽  
System Response ◽  
Linear Quadratic ◽  
Control Effort ◽  
Mems Gyroscope ◽  
Compensator Design ◽  
Wide Range ◽  
Parameter Perturbations

A number of control algorithms have been reported to adopt force balancing scheme into MEMS vibratory gyroscope systems. In practice, however, many algorithms are difficult to implement with electronic circuits. This paper designs and analyzes a lead compensator for a MEMS gyroscope via the Linear Quadratic Regulator (LQR) technique. LQR optimizes and balances the control effort and system response swiftness. Simulation shows the gyroscope achieves high linearity, wide dynamic range, and high robustness to fabrication uncertainties with this efficient compensator design. The closed-loop scale factor uniformity error is 0.7% under ±10% parameter perturbations. The compensator designed in this paper exhibits comparable outstanding performance compared to other reported control algorithms. The method reported in this paper is proved to be effective and can be used in a wide range of applications.

scholarly journals System design for inverted pendulum using LQR control via IoT

2020 ◽  
Vol 11 ◽  
pp. 12
Author(s):  
Dechrit Maneetham ◽  
Petrus Sutyasadi
Keyword(s):  
Inverted Pendulum ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Lqr Control ◽  
Lqr Controller ◽  
Model Tuning ◽  
And Performance ◽  
Performance Results ◽  
And Control

This research proposes control method to balance and stabilize an inverted pendulum. A robust control was analyzed and adjusted to the model output with real time feedback. The feedback was obtained using state space equation of the feedback controller. A linear quadratic regulator (LQR) model tuning and control was applied to the inverted pendulum using internet of things (IoT). The system's conditions and performance could be monitored and controlled via personal computer (PC) and mobile phone. Finally, the inverted pendulum was able to be controlled using the LQR controller and the IoT communication developed will monitor to check the all conditions and performance results as well as help the inverted pendulum improved various operations of IoT control is discussed.

Backstepping Controller Design for a 5 DOF Spherical Inverted Pendulum

2019 ◽  
Vol 41 ◽  
pp. 37-50 ◽  
Author(s):  
Soukaina Krafes ◽  
Zakaria Chalh ◽  
Abdelmjid Saka
Keyword(s):  
Degrees Of Freedom ◽  
Inverted Pendulum ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Performance Comparison ◽  
Virtual Reality Environment ◽  
Linear Quadratic ◽  
Control Scheme ◽  
Linearized System ◽  
Backstepping Controller

This paper presents a Backstepping controller for five degrees of freedom Spherical Inverted Pendulum. Since the system is nonlinear, unstable, underactuated and MIMO and has a nonsquare form, the classic control design cannot be applied to control it. In order to remedy this problem, we propose in this paper a new method based on hierarchical steps of the Backstepping controller taking into a count the nonlinearities that cannot be neglected. Furthermore, a Linear Quadratic Regulator controller and LQR + PID based on the linearized system model are also designed for performance comparison. Finally, a simulation study is carried out to prove the effectiveness of proposed control scheme and is validated using the virtual reality environment that proves the performance of the Backstepping controller over the linear ones where it brings the pendulum from any initial condition in the upper hemisphere while the base is brought to the origin of the coordinates.

Augmented-Stability Controller Design for a UAV’s Longitudinal Motion

2011 ◽  
Vol 63-64 ◽  
pp. 533-536
Author(s):  
Xiao Jun Xing ◽  
Jian Guo Yan
Keyword(s):  
Dynamic Characteristics ◽  
Controller Design ◽  
Damping Ratio ◽  
Linear Quadratic Regulator ◽  
Longitudinal Motion ◽  
Linear Quadratic ◽  
Short Period ◽  
Quality Specifications ◽  
Simulation Results ◽  
And Control

With the purpose of overcoming the defect that unmanned air vehicles (UAVs) are easily disturbed by air current and tend to be unstable, an augmented-stability controller was developed for a certain UAV’s longitudinal motion. According to requirements of short-period damping ratio and control anticipation parameter (CAP) in flight quality specifications of GJB185-86 and C*, linear quadratic regulator (LQR) theory was used in the augmented-stability controller’s design. The simulation results show that the augmented-stability controller not only improves the UAV’s stability and dynamic characteristics but also enhances the UAV’s robustness.

scholarly journals The Coupled Orbit-Attitude Dynamics and Control of Electric Sail in Displaced Solar Orbits

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Mingying Huo ◽  
He Liao ◽  
Yanfang Liu ◽  
Naiming Qi
Keyword(s):  
Linear Quadratic Regulator ◽  
Coupled System ◽  
Control Force ◽  
Attitude Dynamics ◽  
Voltage Distribution ◽  
Linear Quadratic ◽  
Displaced Orbit ◽  
Dynamics And Control ◽  
And Control ◽  
Small Torque

Displaced solar orbits for spacecraft propelled by electric sails are investigated. Since the propulsive thrust is induced by the sail attitude, the orbital and attitude dynamics of electric-sail-based spacecraft are coupled and required to be investigated together. However, the coupled dynamics and control of electric sails have not been discussed in most published literatures. In this paper, the equilibrium point of the coupled dynamical system in displaced orbit is obtained, and its stability is analyzed through a linearization. The results of stability analysis show that only some of the orbits are marginally stable. For unstable displaced orbits, linear quadratic regulator is employed to control the coupled attitude-orbit system. Numerical simulations show that the proposed strategy can control the coupled system and a small torque can stabilize both the attitude and orbit. In order to generate the control force and torque, the voltage distribution problem is studied in an optimal framework. The numerical results show that the control force and torque of electric sail can be realized by adjusting the voltage distribution of charged tethers.

Novel Method on Using Evolutionary Algorithms for PD Optimal Tuning

2011 ◽  
Vol 110-116 ◽  
pp. 4977-4984 ◽  
Author(s):  
R.A. Khoshrooz ◽  
M.A.D. Vahid ◽  
M. Mirshams ◽  
M.R. Homaeinezhad ◽  
A.H. Ahadi
Keyword(s):  
Attitude Control ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Initial Guess ◽  
Pd Controller ◽  
Linear Quadratic ◽  
Optimal Tuning ◽  
Heavy Burden ◽  
Novel Method

This paper presents a method to solve the Evolutionary Algorithm (EA) problems for optimal tuning of the Proportional-Deferential (PD) controller parameters. The major efficiency of the proposed method is the Genetic Algorithm (GA) stuck avoidance as well an appropriate estimation for GA lower and upper bounds. Also by this method for the Particle Swarm Optimization (PSO) methodology the initial choice of the controller parameters can be fulfilled to achieve the acceptable performance accuracies. For both GA and PSO methods, the Linear Quadratic Regulator (LQR) obtained trend is used as the reference for the determination of the aforementioned bounds and initial guess. The presented algorithm was applied to regulate a PD controller for the attitude control of a virtual satellite and also with Hardware-in-the-loop (HIL) reaction wheels. Heavy burden trying and error was eliminated from the PD controller design which can be mentioned as the important merit of the presented study.

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