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Control allocation—A survey

Multivariable adaptive control

This paper is concerned with the fault detection (FD) problem in finite frequency domain for continuous-time Takagi-Sugeno fuzzy systems with sensor faults. Some finite-frequency performance indices are initially introduced to measure the fault/reference input sensitivity and disturbance robustness. Based on these performance indices, an effective FD scheme is then presented such that the generated residual is designed to be sensitive to both fault and reference input for faulty cases, while robust against the reference input for fault-free case. As the additional reference input sensitivity for faulty cases is considered, it is shown that the proposed method improves the existing FD techniques and achieves a better FD performance. The theory is supported by simulation results related to the detection of sensor faults in a tunnel-diode circuit.

Fault detection in finite frequency domain for Takagi-Sugeno fuzzy systems with sensor faults.

This paper presents a recent study to investigate flight dynamics and adaptive control methods for stability and control recovery of a damaged generic transport aircraft. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of the damaged aircraft. Flight dynamics for a general aircraft are developed to account for changes in aerodynamics, mass properties, and the center of gravity that can compromise the stability of the damaged aircraft An iterative trim analysis is developed to compute incremental trim states. A neural network hybrid direct-indirect adaptive flight control is developed for the stability augmentation control of the damaged aircraft. The proposed method performs an online estimation of damaged plant dynamics to improve the command tracking performance in conjunction with a direct adaptive controller. The plant estimation is based on two approaches: 1) an indirect adaptive law derived from the Lyapunov stability theory to ensure that the tracking error is bounded, and 2) a recursive least-squares method that minimizes the modeling error. Simulations show that the hybrid adaptive controller can provide a significant improvement in the tracking performance over a direct adaptive controller working alone.

Flight Dynamics and Hybrid Adaptive Control of Damaged Aircraft

An adaptive disturbance rejection algorithm is developed for the standard control problem The multiple input-multiple output (MIMO) system and controller are represented as ARMARKOV/Toeplitz models, and the parameter matrix of the compensator is updated online by means of a gradient algorithm The algorithm requires minimal knowledge of the plant, specifically, the numerator of the ARMARKOV model of the transfer function from the control inputs to the performance variables is required No knowledge about the spectrum of the disturbance is needed Experimental results demonstrating tonal and broadband disturbance rejection in an acoustic duct are presented

Adaptive disturbance rejection using ARMARKOV/Toeplitz models

This paper proposes a control allocation framework where a feedback adaptive signal is designed for a group of redundant actuators and then it is adaptively allocated among all group members. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and adaptively allocated to the member actuators. Two adaptive control allocation algorithms, guaranteeing closed-loop stability and asymptotic state tracking when partial and total loss of control effectiveness occur, are developed. Proper grouping of the actuators reduces the controller complexity without reducing their efficacy. The implementation and effectiveness of the strategies proposed is demonstrated in detail using several examples.

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Adaptive control allocation in the presence of actuator failures

An Adaptive Disturbance Rejection Algorithm for MIMO Systems with An Aircraft Flight Control Application

In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

/pdf/adaptive-control-allocation-in-the-presence-of-actuator-1h8vr58jdf.pdf

Adaptive Control Allocation in the Presence of Actuator Failures

An aircraft model that incorporates independently adjustable engine throttles and ailerons is employed to develop an adaptive control scheme in the presence of actuator failures. This model captures the key features of aircraft flight dynamics when in the engine differential mode. Based on this model an adaptive feedback control scheme for asymptotic state tracking is developed and applied to a transport aircraft model in the presence of two types of failures during operation, rudder failure and aileron failure. Simulation results are presented to demonstrate the adaptive failure compensation scheme.

/pdf/adaptive-failure-compensation-for-aircraft-tracking-control-4z6y73q54i.pdf

Adaptive failure compensation for aircraft tracking control using engine differential based model

Adaptive control schemes are developed for uncertain multivariable systems with unmatched input disturbances and are applied to an aircraft flight turbulence compensation problem. Key relative degree conditions from system input and disturbance are derived in terms of system interactor matrices for the design of a nominal state or output feedback control law that ensures desired asymptotic output tracking and disturbance rejection. To deal with an uncertain system high-frequency gain matrix, a gain matrix decomposition technique is employed to parametrize an error system model in terms of the parameter and tracking errors, for the design of an adaptive parameter update law with reduced system knowledge. Both adaptive state and output feedback control schemes are presented in detail for systems with general interactor matrices, based on an LDS gain decomposition parametrization, and LDU and SDU decomposition-based designs are also discussed, to develop unified adaptive disturbance rejection techniques for multivariable systems. All closed-loop system signals are bounded, and the system output tracks a reference output asymptotically despite the system and disturbance parameter uncertainties. Simulation results of an aircraft flight control system with adaptive turbulence compensation are presented to show the desired system disturbance rejection performance. Copyright © 2015 John Wiley & Sons, Ltd.

Yu Liu

Papers

Adaptive control allocation in the presence of actuator failures

An Adaptive Disturbance Rejection Algorithm for MIMO Systems with An Aircraft Flight Control Application

Adaptive Control Allocation in the Presence of Actuator Failures

Adaptive failure compensation for aircraft tracking control using engine differential based model

Multivariable adaptive output rejection of unmatched input disturbances