Design of Automatic Landing Systems Using the H-inf Control and the Dynamic Inversion

2015 ◽  
Vol 138 (2) ◽  
Author(s):  
Romulus Lungu ◽  
Mihai Lungu
Keyword(s):  
Federal Aviation Administration ◽  
Dynamic Inversion ◽  
Control Law ◽  
Reference Models ◽  
Low Intensity ◽  
Automatic Landing ◽  
Sensor Measurement ◽  
Wind Shears ◽  
Sensor Errors ◽  
Theoretical Results

This paper focuses on the automatic control of aircraft in the longitudinal plane, during landing, by using the linearized dynamics of aircraft, taking into consideration the wind shears and the errors of the sensors. A new robust automatic landing system (ALS) is obtained by means of the H-inf control, the dynamic inversion, an optimal observer, and two reference models providing the aircraft desired velocity and altitude. The theoretical results are validated by numerical simulations for a Boeing 747 landing; the simulation results are very good (Federal Aviation Administration (FAA) accuracy requirements for Category III are met) and show the robustness of the system even in the presence of wind shears and sensor errors. Moreover, the designed control law has the ability to reject the sensor measurement noises and wind shears with low intensity.

scholarly journals Adaptive Optimal Robust Control for Uncertain Nonlinear Systems Using Neural Network Approximation in Policy Iteration

2021 ◽  
Vol 11 (5) ◽  
pp. 2312
Author(s):  
Dengguo Xu ◽  
Qinglin Wang ◽  
Yuan Li
Keyword(s):  
Neural Network ◽  
Optimal Control ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Policy Iteration ◽  
Control Law ◽  
Globally Asymptotically Stable ◽  
Control Approach ◽  
Input Uncertainties ◽  
Theoretical Results

In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust control is converted into solving an optimal control containing a nominal or auxiliary system with a predefined performance index. It is demonstrated that the optimal control law enables the considered system globally asymptotically stable for all admissible uncertainties. Second, based on the Bellman optimality principle, the online PI algorithms are proposed to calculate robust controllers for the matched and the mismatched uncertain systems. The approximate structure of the robust control law is obtained by approximating the optimal cost function with neural network in PI algorithms. Finally, in order to illustrate the availability of the proposed algorithm and theoretical results, some numerical examples are provided.

scholarly journals Hybrid Passivity Based and Fuzzy Type-2 Controller for Chaotic and Hyper-Chaotic Systems

2017 ◽  
Vol 11 (2) ◽  
pp. 96-103 ◽  
Author(s):  
Fernando Serrano ◽  
Josep M. Rossell
Keyword(s):  
Lyapunov Exponents ◽  
Chaotic System ◽  
Control Strategy ◽  
Chaotic Systems ◽  
Control Law ◽  
Four Dimensions ◽  
Design Requirements ◽  
The Stability ◽  
Theoretical Results

AbstractIn this paper a hybrid passivity based and fuzzy type-2 controller for chaotic and hyper-chaotic systems is presented. The proposed control strategy is an appropriate choice to be implemented for the stabilization of chaotic and hyper-chaotic systems due to the energy considerations of the passivity based controller and the flexibility and capability of the fuzzy type-2 controller to deal with uncertainties. As it is known, chaotic systems are those kinds of systems in which one of their Lyapunov exponents is real positive, and hyper-chaotic systems are those kinds of systems in which more than one Lyapunov exponents are real positive. In this article one chaotic Lorentz attractor and one four dimensions hyper-chaotic system are considered to be stabilized with the proposed control strategy. It is proved that both systems are stabilized by the passivity based and fuzzy type-2 controller, in which a control law is designed according to the energy considerations selecting an appropriate storage function to meet the passivity conditions. The fuzzy type-2 controller part is designed in order to behave as a state feedback controller, exploiting the flexibility and the capability to deal with uncertainties. This work begins with the stability analysis of the chaotic Lorentz attractor and a four dimensions hyper-chaotic system. The rest of the paper deals with the design of the proposed control strategy for both systems in order to design an appropriate controller that meets the design requirements. Finally, numerical simulations are done to corroborate the obtained theoretical results.

Robust flight control law design for an automatic landing flight experiment

1999 ◽  
Vol 7 (9) ◽  
pp. 1143-1151 ◽  
Author(s):  
Masahiro Ohno ◽  
Yasuhiro Yamaguchi ◽  
Takashi Hata ◽  
Morio Takahama ◽  
Yoshikazu Miyazawa ◽  
...  
Keyword(s):  
Flight Control ◽  
Control Law ◽  
Flight Experiment ◽  
Automatic Landing ◽  
Robust Flight Control

scholarly journals Adaptive Neural Network-Based Satellite Attitude Control by Using the Dynamic Inversion Technique and a VSCMG Pyramidal Cluster

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Mihai Lungu ◽  
Romulus Lungu
Keyword(s):  
Neural Network ◽  
Attitude Control ◽  
Approximation Error ◽  
Inversion Method ◽  
Dynamic Inversion ◽  
Control Law ◽  
Feed Forward Neural Network ◽  
Small Satellites ◽  
Control Moment ◽  
Satellite Attitude Control

The paper presents an adaptive system for the control of small satellites’ attitude by using a pyramidal cluster of four variable-speed control moment gyros as actuators. Starting from the dynamic model of the pyramidal cluster, an adaptive control law is designed by means of the dynamic inversion method and a feed-forward neural network-based nonlinear subsystem; the control law has a proportional-integrator component (for the control of the reduced-order linear subsystem) and an adaptive component (for the compensation of the approximation error associated with the function describing the dynamics of the nonlinear system). The software implementation and validation of the new control architecture are achieved by using the Matlab/Simulink environment.

scholarly journals Formation Control of Multi-Agent Systems with Region Constraint

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Zhengquan Yang ◽  
Qing Zhang ◽  
Zengqiang Chen
Keyword(s):  
Formation Control ◽  
Convex Set ◽  
Local Information ◽  
Control Law ◽  
Multi Agent Systems ◽  
Numerical Examples ◽  
Agent Systems ◽  
Multi Agent ◽  
Theoretical Results ◽  
Multi Agents

In this paper, the formation problem for multi-agent systems with region constraint is studied while few researchers consider this problem. The goal is to control all multi-agents to enter the constraint area while reaching formation. Each agent is constrained by a common convex set. A formation control law is presented based on local information of the neighborhood. It is proved that the positions of all the agents would converge to the set constraint while reaching formation. Finally, two numerical examples are presented to illustrate the validity of the theoretical results.

Synchronization control of complex dynamical networks with piecewise constant arguments

2018 ◽  
Vol 41 (2) ◽  
pp. 540-551 ◽  
Author(s):  
Tianhu Yu ◽  
Menglong Su
Keyword(s):  
Impulsive Control ◽  
Lyapunov Stability Theory ◽  
Pinning Control ◽  
Complex Dynamical Networks ◽  
Control Law ◽  
Dynamical Networks ◽  
Piecewise Constant Arguments ◽  
Piecewise Constant ◽  
Synchronization Problem ◽  
Theoretical Results

The pinning synchronization problem is investigated for complex dynamical networks with hybrid coupling via impulsive control. Based on the Lyapunov stability theory, some novel synchronization criteria are derived and an impulsive pinning control law is proposed. By introducing a differential inequality for systems with piecewise constant arguments, it is not necessary to establish any relationship between the norms of the error states with or without piecewise constant arguments. Typical numerical examples are utilized to illustrate the validity and improvements as regards conservativeness of the theoretical results.

Robust launch vehicle’s generalized dynamic inversion attitude control

2017 ◽  
Vol 89 (6) ◽  
pp. 902-910 ◽  
Author(s):  
Uzair Ansari ◽  
Abdulrahman H. Bajodah
Keyword(s):  
Attitude Control ◽  
Closed Loop ◽  
Sliding Mode ◽  
Dynamic Scaling ◽  
Dynamic Inversion ◽  
Control Law ◽  
Successful Implementation ◽  
Robust Tracking Control ◽  
Content Type ◽  
Dynamic Constraints

Purpose To design a robust attitude control system for the ascent flight phase of satellite launch vehicles (SLVs). Design/methodology/approach The autopilot is based on generalized dynamic inversion (GDI). Dynamic constraints are prescribed in the form of differential equations that encapsulate the control objectives, and are generalized inverted using the Moore-Penrose Generalized Inverse (MPGI) based Greville formula to obtain the control law. The MPGI is modified via a dynamic scaling factor for assuring generalized inversion singularity-robust tracking control. An additional sliding mode control (SMC) loop is augmented to robustify the GDI closed-loop system against model uncertainties and external disturbances. Findings The robust GDI control law allows for two cooperating controllers that act on two orthogonally complement control spaces: one is the particular controller that realizes the dynamic constraints, and the other is the auxiliary controller that is affined in the null control vector, and is used to enforce global closed-loop stability. Practical implications Orthogonality of the particular and the auxiliary control subspaces ensures noninterference of the two control actions, and thus, it ensures that both actions work toward a unified goal. The robust control loop increases practicality of the GDI control design. Originality/value The first successful implementation of GDI to the SLV control problem.

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