scholarly journals Adaptive Differential Thrust Methodology for Lateral/Directional Stability of an Aircraft with a Completely Damaged Vertical Stabilizer

2018 ◽  
Vol 2018 ◽  
pp. 1-18
Author(s):  
Long K. Lu ◽  
Kamran Turkoglu
Keyword(s):  
Adaptive Control ◽  
Commercial Aircraft ◽  
Control Approach ◽  
Directional Stability ◽  
Fatal Crash ◽  
And Performance ◽  
The Stability ◽  
And Control ◽  
Model Reference Adaptive ◽  
Differential Thrust

This paper investigates the utilization of differential thrust to help a commercial aircraft with a damaged vertical stabilizer in order to regain its lateral/directional stability. In the event of an aircraft losing its vertical stabilizer, the consequential loss of the lateral/directional stability and control is likely to cause a fatal crash. In this paper, an aircraft with a completely damaged vertical stabilizer is investigated, and a unique differential thrust-based adaptive control approach is proposed to achieve a stable flight envelope. The propulsion dynamics of the aircraft is modeled as a system of differential equations with engine time constant and time delay terms to study the engine response time with respect to a differential thrust input. The proposed differential thrust control module is then presented to map the rudder input to differential thrust input. Model reference adaptive control based on the Lyapunov stability approach is implemented to test the ability of the damaged aircraft to track the model aircraft’s (reference) response in an extreme scenario. Investigation results demonstrate successful application of such differential thrust approach to regain lateral/directional stability of a damaged aircraft with no vertical stabilizer. Finally, the conducted robustness and uncertainty analysis results conclude that the stability and performance of the damaged aircraft remain within desirable limits and demonstrate a safe flight mission through the proposed adaptive control methodology.

scholarly journals L 1 Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Boutheina Maalej ◽  
Rim Jallouli Khlif ◽  
Chokri Mhiri ◽  
Mohamed Habib Elleuch ◽  
Nabil Derbel
Keyword(s):  
Genetic Algorithms ◽  
Adaptive Control ◽  
Time Lag ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Control Approach ◽  
Low Pass ◽  
The Stability ◽  
Fractional Control ◽  
Model Reference Adaptive

Recently, an adaptive control approach has been proposed. This approach, named L 1 adaptive control, involves the insertion of a low-pass filter at the input of the Model Reference Adaptive Control (MRAC). This controller has been designed to overcome several limitations of classical adaptive controllers such as (i) the initialization of estimated parameters, (ii) the stability problems with high adaptation gains, and (iii) the appropriate parameter excitation. In this paper, a new design of the filter is presented, used for L 1 adaptive control, for which the desired performances are guaranteed (appropriate values of the control during start-up, a high filtering of noises, a reduced time lag, and a reduced energy consumption). Parameters of the new proposed filter have been optimised by genetic algorithms. The proposed L 1 adaptive fractional control is applied to a polyarticulated robotic system. Simulation results show the efficiency of the proposed control approach with respect to the classical L 1 adaptive control in the nominal case and in the presence of a multiplicative noise.

Stability and Control of Tooling System for High-Speed Machining

2014 ◽  
Vol 684 ◽  
pp. 375-380
Author(s):  
Deng Sheng Zheng ◽  
Jian Chen ◽  
D.F. Tao ◽  
L. Lv ◽  
Gui Cheng Wang
Keyword(s):  
Natural Frequency ◽  
High Speed ◽  
System Stability ◽  
Finite Model ◽  
High Speed Machining ◽  
Cnc Machine ◽  
And Performance ◽  
The Stability ◽  
Tooling System ◽  
And Control

Tooling system for high-speed machining is one of the key components of high-end CNC machine , its stability and reliability directly affects the quality and performance of the machine. Based on the finite element method, developing a 3D finite model of high-speed machining tool system, studying on the stability of the high Speed machining tool from the natural frequency by the method of modal analysis. Analysis the amount of the overhang and clamping of the tooling , different shank taper interference fit and under different speed conditions, which affects the natural frequency of high-speed machining tool system. Proposed to the approach of improving system stability, which also provides a theoretical basis for the development of new high-speed machining tool system.

Dynamic Analysis and Stability Improvement Concerning the Integration of Wind Farms Kurdistan Electric Network Case Study

2011 ◽  
pp. 198-219 ◽  
Author(s):  
Mohammad Saleh ◽  
Hassan Bevrani
Keyword(s):  
Wind Power ◽  
Dynamic Models ◽  
Wind Farms ◽  
Integrated System ◽  
Electric Network ◽  
Control Approach ◽  
Control Loops ◽  
And Performance ◽  
The Stability

This chapter presents an overview of key issues and technical challenges in a regional electric network, following the integration of a considerable amount of wind power. A brief survey on wind power system, the present status of wind energy worldwide, common dynamic models, and control loops for wind turbines are given. In this chapter, the Kurdistan electric network in the Northwest part of Iran is introduced as a case study system, and an analytical approach is conducted to evaluate the potential of wind power installation, overall capacity estimation, and economic issues, based on the practical data. Then, the impact of high penetration wind power on the system dynamic and performance for various wind turbine technologies is presented. The stability of integrated system is analyzed, and the need for revising of conventional controls and performance standards is emphasized. Finally, a STATCOM-based control approach is addressed to improve the system stability.

Stability Behavior of Model Reference Adaptive Control Methods in Presence of Aircraft Structural Damage

2007 ◽  
Author(s):  
Pascal Nespeca ◽  
Nesrin Sarigul-Klijn
Keyword(s):  
Adaptive Control ◽  
Numerical Study ◽  
Function Analysis ◽  
Model Reference Adaptive Control ◽  
Approximation Technique ◽  
Control Methods ◽  
Model Reference ◽  
Stability Behavior ◽  
The Stability ◽  
Model Reference Adaptive

Any classical control design starts by first satisfying stability and then looking towards satisfying transient requirements. Similarly, a Model Reference Adaptive Control (MRAC) Method should start with a stability analysis. Lyapunov function analysis is first used to justify the stability of the adaptive scheme. Next, a numerical study is conducted to predict the stability behavior of three different MRAC methods in the presence of large unanticipated changes in the dynamics of an aircraft. The Model reference adaptive control methods studied are: Method:1, an adaptive gain method; Method:2, a Neural Network (NN) approximation technique; and, Method:3, a linear approximation technique. For comparison purposes, the aircraft is assumed to have Linear Time Invariant, LTI dynamics. Each algorithm is given full state feedback, an inaccurate reference model and a poor Linear Quadratic Regulator, LQR design for the true plant. It is seen that when the LQR stabilizes the true plant, the three algorithms all achieve the same steady state error to a step command. Numerical results predict the different types of stability behavior that the algorithms provide. It is seen that the Methods: 2 and 3 can only provide a bounded stability, whereas Method: 1 can provide an asymptotic stability. A robust static controller can satisfy stability, but a robust static controller that accommodates variations in plant dynamics might not always be able to match transient requirements as expected. Although there may be no analytical guarantee from adaptive controllers of transient performance, one might look at anecdotal performances.

Adaptive Identification and Control for Small Modular Reactors

2011 ◽  
Author(s):  
Daniel G. Cole
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Adaptive System ◽  
Operating Conditions ◽  
System Stability ◽  
Peak Performance ◽  
Model Matching ◽  
Adaptive Identification ◽  
Control Approach ◽  
And Control

This paper discusses adaptive identification and control (AID&C) techniques to enable automated online identification and control of SMRs. Adaptive system ID allows engineers to rapidly measure system dynamics, calibrate sensors channels, determine loop processes, and quantify actuator authority for the various reactor control loops. Adaptive control can automatically tune these loops and adjust plant processes to optimize conditions for peak performance and power production. Another advantage of the adaptive ID and control approach is that these tools can be used during reactor operation to monitor active and passive components. Adaptive system ID techniques are used to measure loop-transfer characteristics. Presented is a practical approach that uses adaptive model-matching tools to identify the coprime factors of the local loops. This has the advantage over model based approaches since coprime factors can be identified on the real system using real data. Adaptive control enables auto-tuning of controller parameters to meet operational specifications. Using the coprime factors, all controllers that stabilize the plant can be parametrized by a free Q-parameter that can be changed to meet control system objectives and improve performance, and the tuning is performed using adaptive techniques. The controller architecture presented provides several desirable and necessary features: e.g., a default fail-safe mode of operation, stability in the presence of communications failures, guaranteed stability, and robustness. An advantage of the adaptive structure presented here is that control system stability can be guaranteed, even during adaptation by ensuring certain norm conditions on the Q-parameter and estimated plant uncertainty. More importantly, the Q-parameter can be monitored during operation, providing a real-time estimate of the changes in the plant resulting from changes in the reactor itself. This signal monitors the dynamics of each loop, providing information about the reactor from the perspective of the control process. Online monitoring using AID&C can be used to better track control system transients that result in reactor trip, thus avoiding undesirable reactor trips and diversion events. And, there is a potential that the system can better adapt to changing operating conditions during plant transients including load following procedures.

Sign in / Sign up

Export Citation Format

Share Document