Hovering stability of a model helicopter

2016 ◽  
Vol 88 (6) ◽  
pp. 810-817 ◽  
Author(s):  
Ilker Murat Koc ◽  
Semuel Franko ◽  
Can Ozsoy
Keyword(s):  
Initial Conditions ◽  
Linear Quadratic Regulator ◽  
Open Loop ◽  
Small Scale ◽  
Linear Quadratic ◽  
Parameter Uncertainties ◽  
Control Effort ◽  
Content Type ◽  
Modeling Uncertainties ◽  
Angular Displacements

Purpose The purpose of this paper is to investigate the stability of a small scale six-degree-of-freedom nonlinear helicopter model at translator velocities and angular displacements while it is transiting to hover with different initial conditions. Design/methodology/approach In this study, model predictive controller and linear quadratic regulator are designed and compared within each other for the stabilization of the open loop unstable nonlinear helicopter model. Findings This study shows that the helicopter is able to reach to the desired target with good robustness, low control effort and small steady-state error under disturbances such as parameter uncertainties, mistuned controller. Originality/value The purpose of using model predictive control for three axes of the autopilot is to decrease the control effort and to make the close-loop system insensitive against modeling uncertainties.

Robust Compensator Control of a Non-Resonant MEMS Gyroscope With Linear Quadratic Regulator

2010 ◽  
Author(s):  
Wei Cui ◽  
Xiaolin Chen ◽  
Wei Xue
Keyword(s):  
Closed Loop ◽  
Linear Quadratic Regulator ◽  
Open Loop ◽  
High Order ◽  
Behavior Modeling ◽  
Linear Quadratic ◽  
Parameter Uncertainties ◽  
Control Effort ◽  
Wide Range ◽  
Sinusoidal Input

This paper presents a controller design for a four degrees-of-freedom (4-DOF) non-resonant gyroscope via the linear quadratic regulator (LQR) technique. Compared to conventional MEMS gyroscopes, non-resonant gyroscopes are less vulnerable to fabrication perturbations. However, closed-loop performance of non-resonant gyroscopes has not been investigated previously. The control of non-resonant gyroscopes involves consideration of high order systems. LQR, which achieves balances between a fast response and a low control effort, has proven to be effective for high order systems. Our simulation results show that the closed-loop 4-DOF non-resonant gyroscope presented in this paper is able to achieve faster response and higher robustness to parameter uncertainties than the open-loop device. Under the sinusoidal input, compared to an error of 11.06% for the open-loop system, the closed-loop scale factor uniformity error is reduced to 0.014% under ±10% parameter perturbations. The device performance is analyzed by the behavior modeling approach in CoventorWare. The results show that the closed-loop non-resonant gyroscope achieves better performance through the LQR. The method reported here is proven to be effective and can be used in a wide range of applications.

Plasma actuation effect on a NACA 4412 airfoil

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Burak Karadag ◽  
Cem Kolbakir ◽  
Ahmet Selim Durna
Keyword(s):  
Reynolds Number ◽  
Flow Separation ◽  
Open Loop ◽  
Electrode Configuration ◽  
Small Scale ◽  
Low Velocity ◽  
Dbd Plasma ◽  
Content Type ◽  
Plasma Actuation ◽  
Electric Wind

Purpose This paper aims to investigate the effects of a dielectric barrier discharge (DBD) plasma actuator (PA) qualitatively on aerodynamic characteristics of a 3 D-printed NACA 4412 airfoil model. Design/methodology/approach Airflow visualization study was performed at a Reynolds number of 35,000 in a small-scale open-loop wind tunnel. The effect of plasma actuation on flow separation was compared for the DBD PA with four different electrode configurations at 10°, 20° and 30° angles of attack. Findings Plasma activation may delay the onset of flow separation up to 6° and decreases the boundary layer thickness. The effects of plasma diminish as the angle of attack increases. Streamwise electrode configuration, in which electric wind is produced in a direction perpendicular to the freestream, is more effective in the reattachment of the airflow compared to the spanwise electrode configuration, in which the electric wind and the free stream are in the same direction. Practical implications The Reynolds number is much smaller than that in cruise aircraft conditions; however, the results are promising for low-velocity subsonic airflows such as improving control capabilities of unmanned aerial vehicles. Originality/value Superior efficacy of spanwise-generated electric wind over streamwise-generated one is demonstrated at a very low Reynolds number. The results in the plasma aerodynamics literature can be reproduced using ultra-low-cost off-the-shelf components. This is important because high voltage power amplifiers that are frequently encountered in the literature may be prohibitively expensive especially for resource-limited university aerodynamics laboratories.

Autopilot design for an aircraft by using Luenberger observer design

2018 ◽  
Vol 90 (5) ◽  
pp. 858-868 ◽  
Author(s):  
Muhammad Taimoor ◽  
Li Aijun ◽  
Rooh ul Amin ◽  
Hongshi Lu
Keyword(s):  
Design Methodology ◽  
Research Work ◽  
Linear Quadratic Regulator ◽  
Observer Design ◽  
Linear Quadratic ◽  
Content Type ◽  
Luenberger Observer ◽  
Level Flight ◽  
Aerial Vehicle ◽  
The Cost

Purpose The purpose of this paper is to design linear quadratic regulator (LQR) based Luenberger observer for the estimation of unknown states of aircraft. Design/methodology/approach In this paper, the LQR-based Luenberger observer is deliberated for autonomous level flight of unmanned aerial vehicle (UAV) which has been attained productively. Various modes like phugoid and roll modes are exploited for controlling the rates of UAV. The Luenberger observer is exploited for estimation of the mysterious states of the system. The rates of roll, yaw and pitch are used as an input to the observer, while the remaining states such as velocities and angles have been anticipated. The main advantage of using Luenberger observer was to reduce the cost of the system which has been achieved lucratively. The Luenberger observer proposes sturdiness at the rate of completion to conquest over the turmoil and insecurities to overcome the privileged recital. The FlightGear simulator is exploited for the endorsement of the recital of the Luenberger observer-based autopilot. The level flight has been subjugated lucratively and has been legitimated by exploiting the FlightGear simulator. The authenticated and the validated results are offered in this paper. Microsoft Visual Studio has been engaged as a medium between the MATLAB and FlightGear Simulator. Findings The suggested observer based on LQR ensures the lucrative approximation of the unknown states of the system as well as the successful level flight of the system. The Luenberger observer is used for approximation of states while LQR is used as controller. Originality/value In this research work, not only the estimation of unknown states of both longitudinal and lateral model is made but also the level flight is achieved by using those estimated states and the autopilot is validated by using the FlightGear, while in most of the research work only the estimation is made of only longitudinal or lateral model.

scholarly journals Terrain-Perception-Free Quadrupedal Spinning Locomotion on Versatile Terrains: Modeling, Analysis, and Experimental Validation

2021 ◽  
Vol 8 ◽  
Author(s):  
Hongwu Zhu ◽  
Dong Wang ◽  
Nathan Boyd ◽  
Ziyi Zhou ◽  
Lecheng Ruan ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Center Of Mass ◽  
Kinematic Model ◽  
Linear Quadratic Regulator ◽  
Small Scale ◽  
Small Range ◽  
Linear Quadratic ◽  
Stability Margins ◽  
Uneven Terrain ◽  
Quadruped Robots

Dynamic quadrupedal locomotion over rough terrains reveals remarkable progress over the last few decades. Small-scale quadruped robots are adequately flexible and adaptable to traverse uneven terrains along the sagittal direction, such as slopes and stairs. To accomplish autonomous locomotion navigation in complex environments, spinning is a fundamental yet indispensable functionality for legged robots. However, spinning behaviors of quadruped robots on uneven terrain often exhibit position drifts. Motivated by this problem, this study presents an algorithmic method to enable accurate spinning motions over uneven terrain and constrain the spinning radius of the center of mass (CoM) to be bounded within a small range to minimize the drift risks. A modified spherical foot kinematics representation is proposed to improve the foot kinematic model and rolling dynamics of the quadruped during locomotion. A CoM planner is proposed to generate a stable spinning motion based on projected stability margins. Accurate motion tracking is accomplished with linear quadratic regulator (LQR) to bind the position drift during the spinning movement. Experiments are conducted on a small-scale quadruped robot and the effectiveness of the proposed method is verified on versatile terrains including flat ground, stairs, and slopes.

An automatic system for a helicopter autopilot performance evaluation

2019 ◽  
Vol 91 (6) ◽  
pp. 880-885 ◽  
Author(s):  
Antoni Kopyt ◽  
Sebastian Topczewski ◽  
Marcin Zugaj ◽  
Przemyslaw Bibik
Keyword(s):  
Performance Evaluation ◽  
Flight Control ◽  
Automatic System ◽  
Control Algorithm ◽  
Linear Quadratic Regulator ◽  
Algorithm Analysis ◽  
Evaluation Methodology ◽  
Reference Trajectory ◽  
Linear Quadratic ◽  
Content Type

Purpose The purpose of this paper is to elaborate and develop an automatic system for automatic flight control system (AFCS) performance evaluation. Consequently, the developed AFCS algorithm is implemented and tested in a virtual environment on one of the mission task elements (MTEs) described in Aeronautical Design Standard 33 (ADS-33) performance specification. Design/methodology/approach Control algorithm is based on the Linear Quadratic Regulator (LQR) which is adopted to work as a controller in this case. Developed controller allows for automatic flight of the helicopter via desired three-dimensional trajectory by calculating iteratively deviations between desired and actual helicopter position and multiplying it by gains obtained from the LQR methodology. For the AFCS algorithm validation, the objective data analysis is done based on specified task accomplishment requirements, reference trajectory and actual flight parameters. Findings In the paper, a description of an automatic flight control algorithm for small helicopter and its evaluation methodology is presented. Necessary information about helicopter dynamic model is included. The test and algorithm analysis are performed on a slalom maneuver, on which the handling qualities are calculated. Practical implications Developed automatic flight control algorithm can be adapted and used in autopilot for a small helicopter. Methodology of evaluation of an AFCS performance can be used in different applications and cases. Originality/value In the paper, an automatic flight control algorithm for small helicopter and solution for the validation of developed AFCS algorithms are presented.

Robust Optimization in Possibility Theory

2019 ◽  
Vol 5 (4) ◽  
Author(s):  
Dominik Hose ◽  
Markus Mäck ◽  
Michael Hanss
Keyword(s):  
Decision Making ◽  
Robust Optimization ◽  
Objective Function ◽  
Optimization Problems ◽  
Initial Conditions ◽  
Multicriteria Decision Making ◽  
Possibility Theory ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Multicriteria Decision

Abstract In this contribution, the optimization of systems under uncertainty is considered. The possibilistic evaluation of the fuzzy-valued constraints and the adoption of a multicriteria decision making technique for the fuzzy-valued objective function enable a meaningful solution to general fuzzy-valued optimization problems. The presented approach is universally applicable, which is demonstrated by reformulating and solving the linear quadratic regulator problem for fuzzy-valued system matrices and initial conditions.

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.

Control of a thermoelastic beam using heat actuation

2016 ◽  
Vol 23 (20) ◽  
pp. 3309-3326 ◽  
Author(s):  
Ilhan Tuzcu ◽  
Joshua K Moua ◽  
Joe G Olivares
Keyword(s):  
Partial Differential Equations ◽  
Differential Equations ◽  
Rectangular Cross Section ◽  
Linear Quadratic Regulator ◽  
Elastic Displacement ◽  
Thermoelastic Damping ◽  
Linear Quadratic ◽  
Partial Differential ◽  
Control Effort ◽  
Thermoelastic Beam

This paper explores the idea of using heat as an actuator to simultaneously control vibration and temperature of a thermoelastic beam. We first model the beam as a slender, uniform cantilever beam of rectangular cross-section subject to heat through heat patches on the lower and upper surfaces at some discrete spanwise locations. The governing equations of the model are two coupled partial differential equations: one governing the elastic bending displacement and one governing the two-dimensional heat conduction of the beam. Through a discretization, the partial differential equations are replaced by a set of ordinary differential equations in a compact state-space form. We show that the coupling is actually between elastic displacement and those components of temperature contributing to the thickness-wise gradient at the midplane. The linear quadratic regulator in conjunction with the Kalman–Bucy filter is used for the control design to simultaneously damp out the displacement and the gradient. In a numerical example, we show the presence of thermoelastic damping due to the coupling. We also show that the displacement and gradient can simultaneously be controlled by using displacement measurements only, and that for less control effort it is also necessary to include some temperature measurements in the feedback.

Optimal attitude trajectory planning method for CMG actuated spacecraft

2017 ◽  
Vol 232 (1) ◽  
pp. 131-142 ◽  
Author(s):  
Lijun Zhang ◽  
Chunmei Yu ◽  
Shifeng Zhang ◽  
Hong Cai
Keyword(s):  
Trajectory Planning ◽  
Closed Loop ◽  
Pseudospectral Method ◽  
Linear Quadratic Regulator ◽  
Fixed Time ◽  
Open Loop ◽  
Planning Method ◽  
Global Perspective ◽  
Linear Quadratic ◽  
Loop Control

This paper presents an optimal attitude trajectory planning method for the spacecraft equipped with control moment gyros as the actuators. Both the fixed-time energy-optimal and synthesis performance optimal cases are taken into account. The corresponding nonsingular attitude maneuvering trajectories (i.e. open-loop control trajectories) with the consideration of a series of constraints are generated via Radau pseudospectral method. Compared with the traditional steering laws, the optimal steering law designed by this method can explicitly avoid the singularity from the global perspective. A linear quadratic regulator closed-loop controller is designed to guarantee the trajectory tracking performance in the presence of initial errors, inertia uncertainties and external disturbances. Simulation results verify the validity and feasibility of the proposed open-loop and closed-loop control methods.

scholarly journals iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data

2021 ◽  
Author(s):  
Marine Schimel ◽  
Ta-Chu Kao ◽  
Kristopher T. Jensen ◽  
Guillaume Hennequin
Keyword(s):  
Nonlinear Dynamical Systems ◽  
Initial Conditions ◽  
Linear Quadratic Regulator ◽  
External Input ◽  
Learning Approaches ◽  
Linear Quadratic ◽  
Nonlinear Dynamical ◽  
Neural Data ◽  
Recognition Model ◽  
Variational Autoencoder

Understanding how neural dynamics give rise to behaviour is one of the most fundamental questions in systems neuroscience. To achieve this, a common approach is to record neural populations in behaving animals, and model these data as emanating from a latent dynamical system whose state trajectories can then be related back to behavioural observations via some form of decoding. As recordings are typically performed in localized circuits that form only a part of the wider implicated network, it is important to simultaneously learn the local dynamics and infer any unobserved external input that might drive them. Here, we introduce iLQR-VAE, a novel control-based approach to variational inference in nonlinear dynamical systems, capable of learning both latent dynamics, initial conditions, and ongoing external inputs. As in recent deep learning approaches, our method is based on an input-driven sequential variational autoencoder (VAE). The main novelty lies in the use of the powerful iterative linear quadratic regulator algorithm (iLQR) in the recognition model. Optimization of the standard evidence lower-bound requires differentiating through iLQR solutions, which is made possible by recent advances in differentiable control. Importantly, having the recognition model implicitly defined by the generative model greatly reduces the number of free parameters and allows for flexible, high-quality inference. This makes it possible for instance to evaluate the model on a single long trial after training on smaller chunks. We demonstrate the effectiveness of iLQR-VAE on a range of synthetic systems, with autonomous as well as input-driven dynamics. We further show state-of-the-art performance on neural and behavioural recordings in non-human primates during two different reaching tasks.

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