Multivariable Adaptive Piecewise Linear Control Design for NASA Generic Transport Model

Sang, Qian; Tao, Gang

doi:10.2514/1.55185

Cited by 14 publications

(17 citation statements)

References 6 publications

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“…48 The nonlinear system is linearized at steady-state, straight, wings-level flight condition at 75 and 85 kt, both at 800 ft, and the resulting dynamics at each operating point are given, respectively, as follows: x ∈ [−1, 1], i ∈ [1,4], j ∈ [1, 2], p = 1, 2 (the notation K (i, j) represents the (i, j)th entry of matrix K). 48 The nonlinear system is linearized at steady-state, straight, wings-level flight condition at 75 and 85 kt, both at 800 ft, and the resulting dynamics at each operating point are given, respectively, as follows: x ∈ [−1, 1], i ∈ [1,4], j ∈ [1, 2], p = 1, 2 (the notation K (i, j) represents the (i, j)th entry of matrix K).…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In this section, we study the effectiveness of the proposed adaptive hybrid control policy using the NASA GTM. 48 The nonlinear system is linearized at steady-state, straight, wings-level flight condition at 75 and 85 kt, both at 800 ft, and the resulting dynamics at each operating point are given, respectively, as follows: [1,2], p = 1, 2 (the notation K (i, j) represents the (i, j)th entry of matrix K). This leads to have R = 26.71.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In line with the design in the work ofSang and Tao,48 the desired dynamics are selected as with B m1 = B 1 and B m2 = B 2 for the reference model. It is important to underline that the matrices A 1 , B 1 , A 2 , and B 2 are given for simulation purposes, while the controller design does not use the knowledge of these matrices (only the knowledge of the reference model is used).…”

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confidence: 99%

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An adaptive design for quantized feedback control of uncertain switched linear systems

Moustakis

Yuan

Baldi

2018

Adaptive Control & Signal

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This paper addresses the problem of asymptotic tracking for switched linear systems with parametric uncertainties and dwell-time switching, when input measurements are quantized due to the presence of a communication network closing the control loop. The problem is solved via a dynamic quantizer with dynamic offset that, embedded in a model reference adaptive control framework, allows the design of the adaptive adjustments for the control parameters and for the dynamic range and dynamic offset of the quantizer. The overall design is carried out via a Lyapunov-based zooming procedure, whose main feature is overcoming the need for zooming out at every switching instant, in order to compensate for the possible increment of the Lyapunov function at the switching instants. It is proven analytically that the resulting adjustments guarantee asymptotic state tracking. The proposed quantized adaptive control is applied to the piecewise linear model of the NASA Generic Transport Model aircraft linearized at multiple operating points.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

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confidence: 99%

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An adaptive design for quantized feedback control of uncertain switched linear systems

Moustakis

Yuan

Baldi

2018

Adaptive Control & Signal

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“…Since the flight dynamics have nonlinear nature, the linear approximation of the system leads to controllers with stability and performance limitations. To overcome such limitations there exist in the literature a variety of control methodologies which provide important advances in GSC and hybrid and nonlinear approaches [5][6][7][8]; see also GSC surveys [1,[9][10][11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Stability of Gain Scheduling Control for Aircraft with Highly Nonlinear Behavior

Mendez-Vergara

Cervantes

Mendoza-Torres

2014

Mathematical Problems in Engineering

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The main goal of this work is to study the stability properties of an aircraft with nonlinear behavior, controlled using a gain scheduled approach. An output feedback is proposed which is able to guarantee asymptotical stability of the task-coordinates origin and safety of the operation in the entire flight envelope. The results are derived using theory of hybrid and singular perturbed systems. It is demonstrated that both body velocity and orientation asymptotic tracking can be obtained in spite of nonlinearities and uncertainty. The results are illustrated using numerical simulations in F16 jet.

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“…The scheduling variable in our reference model design process is an endogenous parameter, which in the gas turbine engine case is a function of the gas turbine engine spool speeds. Some of the works dedicated to the adaptive control of systems with multiple equilibrium points and with time varying reference systems are [7,8,9,10]. Adaptive control of piecewise linear systems has been developed in [7,8].…”

Section: Introductionmentioning

confidence: 99%

Adaptive control of uncertain systems with gain scheduled reference models

Pakmehr

Yucelen

2014

2014 American Control Conference

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Firstly, a new state feedback model reference adaptive control approach is developed for uncertain systems with gain scheduled reference models in a multi-input multi-output (MIMO) setting. Specifically, adaptive state feedback for output tracking control problem of MIMO nonlinear systems is studied and gain scheduled reference model system is used for generating desired state trajectories. Using convex optimization tools, a common Lyapunov matrix is computed for multiple linearizations near equilibrium and non-equilibrium points of the nonlinear closed loop gain scheduled reference system. This approach guarantees stability of the closed-loop gain scheduled system. Adaptive state feedback control scheme is then developed, and its stability is proven. The resulting closed-loop system is shown to have bounded solutions with bounded tracking error, with the proposed stable gain scheduled reference model. Secondly, the developed control approach is improved for systems with constraints on the control inputs. The resulting closed-loop system is shown to have bounded solutions with bounded tracking error. Sufficient conditions for ultimate boundedness of the closed-loop system are derived. A semi-global stability result is proved with respect to the level of saturation for open-loop unstable plants while the stability result is shown to be global for open-loop stable plants. Thirdly, a decentralized adaptive state feedback control architecture is developed and its stability is proved. Specifically, the resulting closed-loop system is shown to have bounded solutions with bounded tracking error for all the subsystems with the proposed stable gain scheduled reference model. Simulation results are presented for each control architecture.

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Multivariable Adaptive Piecewise Linear Control Design for NASA Generic Transport Model

Cited by 14 publications

References 6 publications

An adaptive design for quantized feedback control of uncertain switched linear systems

An adaptive design for quantized feedback control of uncertain switched linear systems

Stability of Gain Scheduling Control for Aircraft with Highly Nonlinear Behavior

Adaptive control of uncertain systems with gain scheduled reference models

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