Multiplexed Predictive Control of a Large Commercial Turbofan Engine

Richter, Hanz; Singaraju, Anil; Litt, Jonathan S.

doi:10.2514/1.30591

Cited by 58 publications

(30 citation statements)

References 33 publications

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“…(8 ) Because there exists the unknown term -dex(t) in Eq. (7), one can see §ex^ex = fexm(Xexm) -Keex fex(X ex) -dcx (?)…”

Section: = Keexmentioning

confidence: 99%

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Aeroengine Multivariable Nonlinear Tracking Control Based on Uncertainty and Disturbance Estimator

Xiao

2014

Journal of Engineering for Gas Turbines and Power

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L in g fe i X iao C olleg e o f E nergy and P ow er E n g in e erin g, J ia n g s u P ro v in c e Key L ab o ra to ry o f A e rospace P ow er System s, N a n jin g U n iv e rs ity o f A e ron a u tics and A s tro n a u tic s , N a n jin g 2 1 0 0 1 6 , C h in a e -m a il: lfxiao @ n ua a .e d u.cn A e ro e n g in e M u ltiv a ria b le N o n lin e a r T ra c k in g C ontrol B ased on U n c e rta in ty and D is tu rb a n c e E s tim a to rThe multivariable robust tracking control problem for aeroengine is considered in this paper. On the basis of the aeroengine nonlinear affine uncertain dynamic model, and according to uncertainty and disturbance estimator (UDE) control approach, a novel aeroengine multivariable robust nonlinear tracking control method is presented in order to provide favorable tracking and disturbance rejection performance. After getting a generalization form of UDE-based aeroengine multivariable controller, a simplification form o f control law is obtained when a specified form of low-pass filter is applied. Reference model of the aeroengine system should have satisfying dynamic, thus an optional reference model is provided. Simulation on a twin-shaft aeroengine with two inputs, verifies the effectiveness o f the proposed method.

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“…(8 ) Because there exists the unknown term -dex(t) in Eq. (7), one can see §ex^ex = fexm(Xexm) -Keex fex(X ex) -dcx (?)…”

Section: = Keexmentioning

confidence: 99%

“…Nonlinear control methods Contributed have been developed to overcome the shortcomings of linear design approaches [7,8]. Nonlinear control methods Contributed have been developed to overcome the shortcomings of linear design approaches [7,8].…”

Section: Introductionmentioning

confidence: 99%

Aeroengine Multivariable Nonlinear Tracking Control Based on Uncertainty and Disturbance Estimator

Xiao

2014

Journal of Engineering for Gas Turbines and Power

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“…Robust MMPC was first described in [28]. In [29] our MMPC idea was applied (by others) to the control of an aircraft engine. In [15] an experimental evaluation of MMPC is reported.…”

Section: Related Workmentioning

confidence: 99%

Multiplexed model predictive control

et al. 2012

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This paper proposes a form of MPC in which the control variables are moved asynchronously. This contrasts with most MIMO control schemes, which assume that all variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires online optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The multiplexed MPC scheme described in this paper solves the MPC problem for each subsystem sequentially, and updates subsystem controls as soon as the solution is available, thus distributing the control moves over a complete update cycle. The resulting computational speed-up allows faster response to disturbances, which may result in improved performance, despite finding sub-optimal solutions to the original problem.

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“…The other control method is based on the optimization algorithm, including model predictive controls and reference governors. For the former, because of its advantages in dealing with constraints, it is obviously suitable for dealing with limit management control problems of aero-engines, and a number of research results have emerged recently [17][18][19]. For the latter, its advantage is that it can keep the original control structure of the engine in service, optimize the control reference online by configuring an add-on scheme, and improve the limit management ability of the control system [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

An Output-Based Limit Protection Strategy for Turbofan Engine Propulsion Control with Output Constraints

Qin

Pan

et al. 2019

Energies

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To accomplish the limit protection task, the Min-Max selection structure is generally adopted in current aircraft engine control strategies. However, since no relationship between controller switching and limit violation is established, this structure is inherently conservative and may produce slower transient responses than the behavior by engine nature. This paper proposes an output-based limit management strategy, which consists of the safety margin module and the parameter prediction module to monitor system responses, plus the switching logic to govern switches between the main controller and limiters, and, in this way, a faster transient performance is achieved, and the limit protections in transient states become more effective. To realize smooth switching control, the linear-quadratic bumpless transfer method is developed. The design principle of the multi-loop switching control and bumpless compensator is detailed, and the effect-on limit protection control performance-of the design parameters in the safety margin and parameter prediction modules are also analyzed. The proposed approach is tested using simulations covering the whole flight envelope on the nonlinear component-level model of a turbofan engine, and the superiority over the Min-Max architecture is also validated.

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Multiplexed Predictive Control of a Large Commercial Turbofan Engine

Cited by 58 publications

References 33 publications

Aeroengine Multivariable Nonlinear Tracking Control Based on Uncertainty and Disturbance Estimator

Aeroengine Multivariable Nonlinear Tracking Control Based on Uncertainty and Disturbance Estimator

Multiplexed model predictive control

An Output-Based Limit Protection Strategy for Turbofan Engine Propulsion Control with Output Constraints

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