Nonlinear Receding Horizon Control of an F-16 Aircraft

Bhattacharya, Raktim; Balas, Gary J.; Kaya, Mehmet; Packard, Andy

doi:10.2514/2.4965

Cited by 72 publications

(36 citation statements)

References 11 publications

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“…Predictive control in general is usually implemented on top of low-level controllers which take care of fast system dynamics and stabilization (if necessary) [2], [3]. In [8], NMPC is shown to provide better performance compared to a Linear Parameter Varying (LPV) control approach for the F-16 model used in the work presented here. The NMPC scheme in [8] was implemented on a prestabilized F-16 aircraft model, and it employs regulation of state perturbations to a set as its control objective.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable fault tolerant flight control based on Nonlinear Model Predictive Control

Kufoalor

Johansen

2013

2013 American Control Conference

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Abstract-Constrained Nonlinear Model Predictive Control (NMPC) is shown to have potentials for reconfigurable fault tolerant control of highly nonlinear, intrinsically unstable, high performance aircraft. Results on fault tolerance of NMPC autopilots were obtained for an F-16 fighter aircraft model, without the implementation of any prestabilizing controllers. It has been shown that NMPC has inherent fault detection capabilities due to its effective utilization of feedback and its internal model predictions. Actuator (control surface) faults, including extreme cases of total actuator failure are examined as test cases for the NMPC reconfigurable fault tolerant control scheme developed in this work. The NMPC autopilots implementation and simulations were done using the ACADO nonlinear optimization solver. I. INTRODUCTIONThe increasing complexity of modern and future flight control systems demands advanced and reliable control techniques that will ensure safety and survivability. When faults occur, it is very important that system stability is maintained and an acceptable system performance is attained.The reconfigurable fault-tolerant control systems review in [1] highlights important limitations on conventional approaches to solving reconfigurable control problems for constrained multivariable systems and systems with significant nonlinearities. In general, how to design fault-tolerant control systems which can work effectively in the entire range of nonlinear systems, and how to distinguish the changes induced by faults from that by operating condition variations is still a challenge.In the past few decades it became apparent that predictive control methods display qualities that could be utilized in complex, nonlinear flight control applications [2]. Model predictive control, in general, has been identified as a method that offers good possibilities for reconfiguration and fault-tolerant control [1], [3]-[6]. This claim is simply due to model predictive control's ability of handling most of the challenges of reconfigurable control in a generic and systematic manner. The choice of NMPC over standard nonlinear control methods is therefore justified by the fact that they are not developed in order to handle constraints in a systematic way. In addition, many nonlinear methods depend on complicated design procedures that do not scale well to large systems [7].Most fault tolerant control systems rely on or integrate fault detection and diagnosis (FDD) subsystems in order to

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Section: Introductionmentioning

confidence: 99%

Reconfigurable fault tolerant flight control based on Nonlinear Model Predictive Control

Kufoalor

Johansen

2013

2013 American Control Conference

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“…If the performance index l(x, u) and the terminal cost V (x(t + T )) are given as (3), (4), then the stability of the system which consists of (1) and receding horizon control is guaranteed.…”

Section: Theoremmentioning

confidence: 99%

Experiments on Stabilizing Receding Horizon Control of a Direct Drive Manipulator

et al. 2007

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In this paper, the application of receding horizon control to a two-link direct drive manipulator (Fig. 1) is demonstrated. Instead of the terminal constraints, a terminal cost on receding horizon control is used to guarantee the stability, because of the computational demand. The key idea of this paper is to apply the receding horizon control with the terminal cost which is derived from the energy function of the robot system. The energy function is given as the control Lyapunov function by considering the inverse optimality. In the experimental results, the stability and the performance are compared with respect to the horizon length by applying the receding horizon control and the inverse optimal control to the robot arm.

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“…Challenges in automatic flight control are predominant over those in many systems due to the uncertainties that are involved in the aircraft itself, as well as its surroundings [1][2][3][4][5]. Nonlinearities are found in the dynamics of the plane and the actuators that control it.…”

Section: Introductionmentioning

confidence: 99%

A Model Matching STR Controller for High Performance Aircraft

Ghandakly

Reed

2013

ISRN Aerospace Engineering

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This paper presents a development, as well as an investigation of a Model Matching Controller (MMC) design based on the SelfTuning Regulator (STR) framework for high performance aircraft with direct application to an F-16 aircraft flight control system. In combination with the Recursive Least Squares (RLS) identification, the MMC is developed and investigated for effectiveness on a detailed model of the aircraft. The popular robust Quantitative Feedback Theory (QFT) controller is also outlined and used to represent a baseline controller, for performance comparison during four simulated test flight maneuvers. In each of the four maneuvers, the proposed MMC provided consistently stable and satisfactory performance, including the challenging pull-up and pushover maneuvers. The baseline stationary controller has been found to become unstable in two of the four maneuvers tested. It also performs satisfactorily-to-arguably poorly in the remaining two as compared to the MMC. Simulation results presented in this investigation support a clear argument that the proposed MMC provides superior performance in the realm of automatic flight control.

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Nonlinear Receding Horizon Control of an F-16 Aircraft

Cited by 72 publications

References 11 publications

Reconfigurable fault tolerant flight control based on Nonlinear Model Predictive Control

Reconfigurable fault tolerant flight control based on Nonlinear Model Predictive Control

Experiments on Stabilizing Receding Horizon Control of a Direct Drive Manipulator

A Model Matching STR Controller for High Performance Aircraft

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