A linear-quadratic-Gaussian approach for automatic flight control of fixed-wing unmanned air vehicles

2011 ◽  
Vol 115 (1163) ◽  
pp. 29-41 ◽  
Author(s):  
C.-S. Lee ◽  
W.-L. Chan ◽  
S.-S. Jan ◽  
F.-B. Hsiao
Keyword(s):  
Flight Control ◽  
Linear Quadratic Regulator ◽  
Flight Test ◽  
Computationally Efficient ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Control Approach ◽  
State Measurement ◽  
Onboard System ◽  
Lqg Controllers

AbstractThis paper presents the design and implementation of automatic flight controllers for a fixed-wing unmanned air vehicle (UAV) by using a linear-quadratic-Gaussian (LQG) control approach. The LQG design is able to retain the guaranteed closed-loop stability of the linear-quadratic regulator (LQR) while having incomplete state measurement. Instead of feeding back the actual states to form the control law, the estimated states provided by a separately designed optimal observer, i.e. the Kalman filter are used. The automatic flight controllers that include outer-loop controls are constructed based on two independent LQG regulators which govern the longitudinal and lateral dynamics of the UAV respectively. The resulting controllers are structurally simple and thus efficient enough to be easily realized with limited onboard computing resource. In this paper, the design of the LQG controllers is described while the navigation and guidance algorithm based on Global Positioning System (GPS) data is also outlined. In order to validate the performance of the automatic flight control system, a series of flight tests have been conducted. Significant results are presented and discussed in detail. Overall, the flight-test results show that it is highly feasible and effective to apply the computationally efficient LQG controllers on a fixed-wing UAV system with a relatively simple onboard system. On the other hand, a fully automatic 44km cross-sea flight demonstration was successfully conducted using the LQG-based flight controllers. Detailed description regarding the event and some significant flight data are given.

scholarly journals Performance Improvement of Air Path Dynamics in Diesel Engines using LQR/LQG Optimal & Switching Control Techniques

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2059-2064
Keyword(s):  
Performance Improvement ◽  
Diesel Engines ◽  
Linear Quadratic Regulator ◽  
Variable Geometry ◽  
Optimal Switching ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Control Techniques ◽  
Variable Geometry Turbine ◽  
Lqg Controllers

The modern-day chalenge for the manipulate framework network is to enhance the exhibition of the kingdom elements associated enormous all spherical manner of diesel cars. The automobile enterprise is utilising Exhaust fuel Recirculation (EGR), Variable Geometry Turbine (VGT) and Fuelling has manipulate contributions of air elements. subsequently, on this paper analyses are executed whilst the framework is uncovered to deterministic and arbitrary commotions through structuring the controller utilizing Linear Quadratic Gaussian (LQG). The proposed controller is contrasted and Linear Quadratic Regulator (LQR) and Later, converting among LQG controllers is likewise proposed to approve the effects without changing.

scholarly journals Control of longitudinal flight dynamics of a fixedwing UAV using LQR, LQG and nonlinear control

2019 ◽  
Vol 104 ◽  
pp. 02001
Author(s):  
Aline Ingabire ◽  
Andrey A. Sklyarov
Keyword(s):  
Flight Control ◽  
Stability Margin ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
External Disturbances ◽  
Control Laws ◽  
Pitch Control ◽  
Nonlinear Controllers ◽  
Aerial Vehicle

This paper aim is to present a comparative study between Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG) and nonlinear controllers for pitch control of a fixed-wing Unmanned Aerial Vehicle (UAV). Due to a good stability margin and strong robustness LQR has been selected. LQG was chosen because is able to overcome external disturbances. Kalman Filter controller was also introduced to the fixed-wing UAV flight control. Further, we designed an autopilot that controls the pitch angle of the fixed-wing UAV. In the end, the control laws are simulated in Matlab/Simulink. The results obtained are compared to see which method is faster, more reliable and more robust.

scholarly journals Modified LQG/LTR Control Methodology in Active Structural Control

2003 ◽  
Vol 22 (2) ◽  
pp. 97-108 ◽  
Author(s):  
Yan Sheng ◽  
Chao Wang ◽  
Ying Pan ◽  
Xinhua Zhang
Keyword(s):  
Structural Control ◽  
Signal To Noise Ratio ◽  
Open Loop ◽  
Control Force ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Control Approach ◽  
Active Structural Control ◽  
Loop Transfer Recovery ◽  
Control Methodology

This paper presents a new active structural control design methodology comparing the conventional linear-quadratic-Gaussian synthesis with a loop-transfer-recovery (LQG/LTR) control approach for structures subjected to ground excitations. It results in an open-loop stable controller. Also the closed-loop stability can be guaranteed. More importantly, the value of the controller's gain required for a given degree of LTR is orders of magnitude less than what is required in the conventional LQG/LTR approach. Additionally, for the same value of gain, the proposed controller achieves a much better degree of recovery than the LQG/LTR-based controller. Once this controller is obtained, the problems of control force saturation are either eliminated or at least dampened, and the controller band-width is reduced and consequently the control signal to noise ratio at the input point of the dynamic system is increased. Finally, numerical examples illustrate the above advantages.

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.

Flight Control System Design for Propulsion-Controlled Aircraft

2005 ◽  
Vol 219 (4) ◽  
pp. 329-340 ◽  
Author(s):  
Y Ochi
Keyword(s):  
Flight Control ◽  
Linear Models ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
State Feedback Control ◽  
Longitudinal Motion ◽  
Linear Quadratic ◽  
Engine Thrust ◽  
Model Following Control ◽  
Flight Controls

The loss of an aircraft's primary flight controls can lead to a fatal accident. However, if the engine thrust is available, controllability and safety can be retained. This article describes flight control using engine thrust only when an aircraft has lost all primary flight controls. This is a kind of flight control reconfiguration. For safe return, the aircraft must first descend to a landing area, decelerate to a landing speed, and then be capable of precise flight control for approach and landing. For these purposes, two kinds of controllers are required: a controller for descent and deceleration and a controller for approach and landing. The former controller is designed for longitudinal motion using a model-following control method, based on a linear quadratic regulator. The latter is designed by an H∞ state-feedback control method for both longitudinal and lateral-directional motions. Computer simulation is conducted using linear models of the Boeing 747. The results indicate that flight path control, including approach and landing, is possible using thrust only; however, speed control proves more difficult. However, if the horizontal stabilizer is available, the airspeed can be reduced to a safe landing speed.

LQG Control Design for Vehicle Active Anti-Roll Bar System

2014 ◽  
Vol 663 ◽  
pp. 146-151 ◽  
Author(s):  
Noraishikin Zulkarnain ◽  
Hairi Zamzuri ◽  
Saiful Amri Mazlan
Keyword(s):  
Ride Comfort ◽  
Simulation Analysis ◽  
Control Strategies ◽  
Dynamic Modelling ◽  
Linear Quadratic Regulator ◽  
Vehicle Body ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Roll Rate ◽  
External Forces

The objective of this paper is to design a linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers for an active anti-roll bar system. The use of an active anti-roll bar will be analysed from two different perspectives in vehicle ride comfort and handling performances. This paper proposed the basic vehicle dynamic modelling with four degree of freedom (DOF) on half car model and are described that show, why and how it is possible to control the handling and ride comfort of the car, with the external forces also control strategies on the front anti-roll bar. By simulation analysis, the design model is validity and the performance under control of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controller are achieved. Both two controllers are modeled in MATLAB/SIMULINK environment. It has to be determined which control strategy delivers better performance with respect to roll angle and the roll rate of half vehicle body. The result shows, however, that LQG produced better response compared to a LQR strategy.

scholarly journals Elevation, pitch and travel axis stabilization of 3DOF helicopter with hybrid control system by GA-LQR based PID controller

2020 ◽  
Vol 10 (2) ◽  
pp. 1868 ◽  
Author(s):  
Ibrahim K. Mohammed ◽  
Abdulla I. Abdulla
Keyword(s):  
Pid Controller ◽  
Hybrid Control ◽  
Research Work ◽  
Linear Quadratic Regulator ◽  
Optimization Method ◽  
Feedback Gain ◽  
Algorithm Optimization ◽  
Linear Quadratic ◽  
Control Approach ◽  
Lqr Controller

This research work presents an efficient hybrid control methodology through combining the traditional proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) optimal controlher. The proposed hybrid control approach is adopted to design three degree of freedom (3DOF) stabilizing system for helicopter. The gain parameters of the classic PID controller are determined using the elements of the LQR feedback gain matrix. The dynamic behaviour of the LQR based PID controller, is modeled and the formulated in state space form to enable utlizing state feedback controller technique. The performance of the proposed LQR based LQR controller is improved by using Genetic Algorithm optimization method which are adopted to obtain optimum values for LQR controller gain parameters. The LQR-PID hybrid controller is simulated using Matlab environment and its performance is evaluated based on rise time, settling time, overshoot and steady state error parameters to validate the proposed 3DOF helicopter balancing system. Based on GA tuning approach, the simulation results suggest that the hybrid LQR-PID controller can be effectively adopted to stabilize the 3DOF helicopter system.

Robust Control and Synchronization of Chaotic Systems with Actuator Constraints

2015 ◽  
pp. 1-43 ◽  
Author(s):  
Kouamana Bousson ◽  
Carlos Velosa
Keyword(s):  
Robust Control ◽  
Chaotic System ◽  
Chaotic Systems ◽  
Linear Part ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Aeroelastic System ◽  
Control Approach ◽  
Nonlinear Part ◽  
Actuator Constraints

This chapter proposes a robust control approach for the class of chaotic systems subject to magnitude and rate actuator constraints. The approach consists of decomposing the chaotic system into a linear part plus a nonlinear part to form an augmented system comprising the system itself and the integral of the output error. The resulting system is posteriorly seen as a linear system plus a bounded disturbance, and two robust controllers are applied: first, a controller based on a generalization of the Lyapunov function, then a Linear-Quadratic Regulator (LQR) with a prescribed degree of stability. Numerical simulations are performed to validate the approach applying it to the Lorenz chaotic system and to a chaotic aeroelastic system, and parameter uncertainties are also considered to prove its robustness. The results confirm the effectiveness of the approach, and the constraints are guaranteed as opposed to other control techniques which do not consider any kind of constraints.

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