A Bio-Inspired Adaptive Control Compensation System for an Aircraft Outside Bounds of Nominal Design

2015 ◽  
Vol 137 (9) ◽  
Author(s):  
Andres E. Perez ◽  
Hever Moncayo ◽  
Mario Perhinschi ◽  
Dia Al Azzawi ◽  
Adil Togayev
Keyword(s):  
Adaptive Control ◽  
Immune System ◽  
Degrees Of Freedom ◽  
Humoral Response ◽  
Control Technique ◽  
Tracking Errors ◽  
Control Approach ◽  
Handling Qualities ◽  
Genetic Algorithm Approach ◽  
Living Organisms

This paper presents a novel bio-inspired adaptive control technique that has been designed to maintain the performance of an aircraft under upset conditions. The proposed control approach is inspired by biological principles that govern the humoral response of the immune system of living organisms and is intended to reduce pilot effort while maintaining adequate aircraft operation outside bounds of nominal design. The immunity-based control parameters are optimized offline for multiple sets of failures using a genetic algorithm approach. The performance of the immunity-based augmentation is compared with a neural network (NN)-based augmentation. Different piloted tests were performed on a six degrees-of-freedom (6DOF) motion-based simulator for different types of maneuvers under several flight conditions. The results show that the artificial immune system (AIS) proposed scheme improves the aircraft handling qualities by reducing the tracking errors (TEs) and improving the pilot response required to maintain control of the aircraft under upset conditions.

Adaptive Control of Mechanical Gas Face Seals With Rotor Runout and Static Stator Misalignment

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Haojiong Zhang ◽  
Robert G. Landers ◽  
Brad A. Miller
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Equations Of Motion ◽  
Control Technique ◽  
Estimation Errors ◽  
Adaptive Controllers ◽  
Gas Leakage ◽  
Robust Model ◽  
Robust Adaptive ◽  
Model Reference Adaptive

This paper presents a control methodology that utilizes a robust model reference adaptive control technique to regulate the dynamic behavior of a coned mechanical gas face seal system in a flexibly mounted stator configuration. Individual adaptive controllers are designed for the three stator rigid body degrees of freedom based on the linear portions of their respective equations of motion. The force and moments generated within the gas film are estimated using Kalman filter-based estimators and directly cancelled in the control algorithm using offset control signals. The estimation errors are considered as bounded disturbances to the seal system and are taken into account by the robust adaptive controllers. Simulation results show that the controllers effectively stabilize the stator motion and control the stator tilts to synchronously track the rotor runout with near-zero relative misalignment magnitude and phase shift, thus, minimizing gas leakage.

Adaptive Control Scheme for Grid Tied SPV System with DSTATCOM Capabilities: Review

2021 ◽  
Vol 23 (07) ◽  
pp. 678-689
Author(s):  
Bilal Ahmad Ganie ◽  
◽  
Dr. (Mrs.) Lini Mathew ◽  
Keyword(s):  
Adaptive Control ◽  
Stage Structure ◽  
Voltage Regulation ◽  
Control Technique ◽  
Voltage Source ◽  
Voltage Source Converter ◽  
Current Harmonics ◽  
Control Approach ◽  
Photovoltaic Array ◽  
Static Compensator

This study provides an adaptive control approach of VSC (voltage source converter) coupled with SPV (solar photovoltaic array), in a 3P3W (three-phase three-wire) system with three single-phase non-linear loads having Distributed Static Compensator (DSTATCOM) abilities using P and O (perturb & observe) methodology. The adaptive control technique converges quickly and has a low mean square error. For the correction of power factor and zero voltage regulation modes, the system is studied and simulated. The system’s great efficacy at high voltages is due to its one-stage structure. Grid current harmonics are significantly below the IEEE-519 norm. The suggested system is modeled and simulated with the available sim power system toolbox in MATLAB/Simulink, and the system’s behavior under different loads and environmental circumstances is confirmed.

scholarly journals Handling Model and Implementation Uncertainties via an Adaptive Discrete Sliding Mode Controller Design

2016 ◽  
Author(s):  
Mohammad Reza Amini ◽  
Mahdi Shahbakhti ◽  
Selina Pan ◽  
J. Karl Hedrick
Keyword(s):  
Adaptive Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Electronic Control Unit ◽  
Control Technique ◽  
Propagation Mechanism ◽  
Sliding Mode Controller ◽  
Model Uncertainties ◽  
Control Approach ◽  
The Impact

Analog-to-digital conversion (ADC) and uncertainties in modeling the plant dynamics are the main sources of imprecisions in the design cycle of model-based controllers. These implementation and model uncertainties should be addressed in the early stages of the controller design, otherwise they could lead to failure in the controller performance and consequently increase the time and cost required for completing the controller verification and validation (V&V) with more iterative loops. In this paper, a new control approach is developed based on a nonlinear discrete sliding mode controller (DSMC) formulation to mitigate the ADC imprecisions and model uncertainties. To this end, a DSMC design is developed against implementation imprecisions by incorporating the knowledge of ADC uncertainties on control inputs via an online uncertainty prediction and propagation mechanism. Next, a generic online adaptive law will be derived to compensate for the impact of an unknown parameter in the controller equations that is assumed to represent the model uncertainty. The final proposed controller is an integrated adaptive DSMC with robustness to implementation and model uncertainties that includes (i) an online ADC uncertainty mechanism, and (ii) an online adaptation law. The proposed adaptive control approach is evaluated on a nonlinear automotive engine control problem in real-time using a processor-in-the-loop (PIL) setup with an actual electronic control unit (ECU). The results reveal that the proposed adaptive control technique removes the uncertainty in the model fast, and significantly improves the robustness of the controllers to ADC imprecisions. This provides up to 60% improvement in the performance of the controller under implementation and model uncertainties compared to a baseline DSMC, in which there are no incorporated ADC imprecisions.

Adaptive Synchronization Control of Multiple Spacecraft Formation Flying

2006 ◽  
Vol 129 (3) ◽  
pp. 337-342 ◽  
Author(s):  
Hong-Tao Liu ◽  
Jinjun Shan ◽  
Dong Sun
Keyword(s):  
Formation Flying ◽  
Control Technique ◽  
Adaptive Synchronization ◽  
Synchronization Control ◽  
Tracking Errors ◽  
Control Approach ◽  
Synchronization Errors ◽  
Spacecraft Formation ◽  
Spacecraft Formation Flying ◽  
Multiple Spacecraft

An adaptive nonlinear synchronization control approach is developed for multiple spacecraft formation flying with elliptical reference orbits. It can guarantee that both the tracking errors and the synchronization errors of the relative positions converge to zero globally, even in the presence of uncertain parameters. The generalized synchronization concept allows us to design various synchronization errors so that different synchronization performance can be obtained. Simulation results of a leader-follower spacecraft pair and the maneuvering of multiple spacecraft in formation flying are presented to verify the effectiveness of the proposed control technique.

Adaptive attitude controller design for tail-sitter unmanned aerial vehicles

2020 ◽  
pp. 107754632092535
Author(s):  
Deyuan Liu ◽  
Hao Liu ◽  
Jiansong Zhang ◽  
Frank L Lewis
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicles ◽  
Control Method ◽  
Controller Design ◽  
Dynamic Pressure ◽  
Tracking Errors ◽  
Control Approach ◽  
Aerial Vehicles ◽  
Attitude Tracking ◽  
Mode Transitions

Tail-sitter unmanned aerial vehicles have two flight modes: they can fly long distances at high cruising speeds as fixed-wing aircrafts; or hover, take off, and land vertically as rotary-wing aircrafts. The tail-sitter dynamics involves serious nonlinearities and high uncertainties, especially in the two flight mode transitions. In this article, an adaptive control approach is proposed for a class of tail-sitter unmanned aerial vehicles to achieve the robustness properties. The control torque allocation problem is addressed based on the dynamic pressure in the transition flight. The proposed control method does not need to switch the coordinate system, the controller structure, or the controller parameters in different flight modes. It is proven that the attitude tracking errors can converge into a given neighborhood of the origin in finite time. Simulation results are presented to show the advantages of the proposed adaptive control method.

Modified Model-Free Adaptive Control Method Applied to Vibration Control of an Elastic Crane

2019 ◽  
Author(s):  
Hoang Anh Pham ◽  
Dirk Söffker
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Structural Information ◽  
Control Strategies ◽  
Control Input ◽  
Tracking Errors ◽  
Adaptive Controllers ◽  
Control Approach ◽  
Model Free ◽  
Controlled Systems

Abstract Model-free adaptive control (MFAC) is a data-driven control approach receiving increased attention in the last years. Different model-free-based control strategies are proposed to design adaptive controllers when mathematical models of the controlled systems should not be used or are not available. Using only measurements (I/O data) from the system, a feedback controller is generated without the need of any structural information about the controlled plant. In this contribution an improved MFAC is discussed for control of unknown multivariable flexible systems. The main improvement in control input calculation is based on the consideration of output tracking errors and its variations. A new updated control input algorithm is developed. The novel idea is firstly applied for controlling vibrations of a MIMO ship-mounted crane. The control efficiency is verified via numerical simulations. The simulation results demonstrate that vibrations of the elastic boom and the payload of the crane can be reduced significantly and better control performance is obtained when using the proposed controller compared to standard model-free adaptive and PI controllers.

Temperature Control Of A Water Bath Process: A Comparative Study Between Neuro-Control, A Self-Tuning Adaptive Control, A Generalised Predictive Control, And A Conventional Feedback Control Approach

1991 ◽  
pp. 14-33
Author(s):  
Marzuki Khalid ◽  
Rubiyah Yusof ◽  
Sigeru Omatu
Keyword(s):  
Neural Networks ◽  
Adaptive Control ◽  
Feedback Control ◽  
Predictive Control ◽  
Temperature Control ◽  
Water Bath ◽  
The Other ◽  
Control Technique ◽  
Control Approach ◽  
Self Tuning

Currently, neural networks are being used to solve problem related to control. One way to determine the reliability of the neuro-control technique is to test it on a variety of realistic problems, and to compare directly with existing traditional control technique, to see whether it works well and where it needs further refinement. In this article, we compare the neuro-control approach to a self-tuning adaptive control approach, a generalised predictive control approach, and a conventional feedback control approach on a real-time process control system. The neuro-control scheme consists of a backpropagation through time utility where two neural networks are trained one as an emulator, and the other as a controller. The four systems are compared conceptually and through experimental studies on the same single-input single-output water bath temperature control process. Comparisons, where applicable, are made with respect to methodology, system tracking performance, speed of adaptation, disturbance rejection, effect of long time-delay, and noise rejection. The results show that the neural network controller performs very well and offers encouraging advantages in many aspects over the other three controllers.

Development of Immunity Based Adaptive Control Laws for Aircraft Fault Tolerance

2014 ◽  
Author(s):  
Andres E. Perez ◽  
Hever Moncayo ◽  
Israel Moguel ◽  
Mario G. Perhinschi ◽  
Dia Al Azzawi ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Immune System ◽  
Degrees Of Freedom ◽  
Performance Metrics ◽  
Fault Tolerant ◽  
System Response ◽  
Control Laws ◽  
Structural Failures ◽  
And Performance ◽  
Control Surfaces

This paper presents the development and testing of a novel fault tolerant adaptive control system based on a bio-inspired immunity-based mechanism applied to an aircraft fighter model. The proposed baseline control laws use a non-linear dynamic inversion and model reference adaptive control on the inner loops of the aircraft dynamics. In this new approach, the baseline controllers are augmented with an artificial immune system mechanism that relies on a direct compensation inspired primarily by the biological immune system response. The effectiveness of the approach is demonstrated through a full 6 degrees-of-freedom aircraft model interfaced with a Flight gear environment. The performance of the proposed control laws are investigated under a novel set of performance metrics, which quantify the level of input activity from the pilot and from the control surfaces in order to ensure the stability and performance of the aircraft under different actuator and structural failures. Optimization of the parameters of the artificial immunity system is performed using a genetic algorithm. The results show that the optimized fault tolerant adaptive control laws improve significantly the failure rejection using minimum pilot input and control surfaces activity under upset flight conditions.

Model-Reference Based Adaptive Control for Enhancing Lateral Stability of Car-Trailer Systems

2016 ◽  
Author(s):  
Smitha Vempaty ◽  
Eungkil Lee ◽  
Yuping He
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Reference Model ◽  
Model Reference Adaptive Control ◽  
Operating Conditions ◽  
Model Parameters ◽  
Lateral Stability ◽  
Model Reference ◽  
Control Approach ◽  
Model Reference Adaptive

This paper presents a model reference adaptive control (MRAC) approach to enhance the lateral stability of car-trailer systems. To this end, a 3 degrees of freedom (DOF) linear yaw-plane car-trailer model was developed as a “reference model”. The yaw rate of leading and trailing units of the reference model were used as the target states to control and stabilize a virtual vehicle plant represented by a 5 DOF linear yaw-roll car-trailer model. A Lyapunov-based controller was designed to handle the lateral stability of the car-trailer dynamical system. The model parameters and operating conditions of the system were predefined while designing the controller. The effectiveness of the adaptive controller for improving the lateral stability of car-trailer systems was demonstrated under a simulated multiple cycle sine-wave steering input maneuver. It was observed that the lateral stability of car-trailer system was improved by controlling respective yaw rates of the car and the trailer, using model reference adaptive control approach in conjunction with Lyapunov stability criterion.

ADAPTIVE CONTROL OF AN ACTIVE SUSPENSION FOR NONLINEAR TIME VARYING VEHICLE PLANT

2000 ◽  
Vol 24 (3-4) ◽  
pp. 525-546
Author(s):  
Rao V. Dukkipati ◽  
Satya S. Vallurupalli
Keyword(s):  
Adaptive Control ◽  
Degrees Of Freedom ◽  
Reference Model ◽  
Model Simulation ◽  
A Priori ◽  
Optimal Performance ◽  
Time Varying ◽  
Control Approach ◽  
Dynamic Variations ◽  
Suspension Model

This paper presents a new adaptive control approach to general multi-degrees-of-freedom suspension models. The control concept diverts from the widely applied optimal control to adaptive control. The basic idea involves obtaining optimal performance of any nonlinear time varying suspension model by adaptively following a predefined reference model. Optimal performance is achieved by an adaptive control law, which involves feed forward, feedback and auxiliary controller parameters. Model reference adaptive control is used to derive adaptation laws for the controller. The proposed control scheme is computationally fast and does not require a priori knowledge of complex nonlinear dynamic variations and time varying parameters of the model. Simulation results for a two-degree of freedom nonlinear suspension model subjected to random asphalt road input are presented. The time and frequency domain results indicate good performance of adaptive controller even for large dynamic variations of model.

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