Robust control and limit protection in aircraft gas turbine engines

Kolmanovsky, Ilya; Jaw, Link C.; Merrill, Walter C.; Van, Hoang Tran

doi:10.1109/cca.2012.6402640

Cited by 18 publications

(12 citation statements)

References 11 publications

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“…where r(0) is the actual set-point at t = 0, while R = R T > 0 and Q = Q T > 0 are weight matrices, with Q satisfying (11). The solution of this problem has the form,…”

Section: B Ecg With Disturbancesmentioning

confidence: 99%

“…The components of the disturbance vector w in (1) reflect the fan health parameters of CMAPSS-40k model, 17,18 specifically, the fan efficiency modifier, the fan flow modifier and the fan pressure ratio modifier. Other health parameters of CMAPSS-40k model or the aggregate axial and circumferential inlet distortions parameters 11 can be treated similarly. The direct feed-through matrices D c and D cw in (1) are non-zero as the linearized model (1) is obtained after model order reduction and retaining only slower mechanical states.…”

Section: Extended Command Governormentioning

confidence: 99%

“…11 Recent studies based on simulation models have been conducted demonstrating that constraints in gas turbine engines can be enforced using reduced order, prioritized and decentralized RG designs. 7,8,24 The research into the decentralized reference governor theory 7 has in fact been motivated by its potential use as an enabling technology for distributed control of aircraft engines.…”

Section: Introductionmentioning

confidence: 99%

“…The matrix Q satisfying(11) was computed, based onĀ T QĀ − Q = −0.01I, where I is the identity matrix,…”

mentioning

confidence: 99%

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Limit Protection in Gas Turbine Engines Based on Reference and Extended Command Governors

Kolmanovsky¹,

Merill²

2014

50th AIAA/ASME/SAE/ASEE Joint Propulsion Conference

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The paper considers the application of Reference Governors (RG), Command Governors (CG) and Extended Command Governors (ECG) to limit protection in gas turbine engines. The governors are add-on schemes to the nominal control design that operate by exploiting physical models of the constraints and predictively modifying the reference commands (set-points) to closed-loop systems as necessary to avoid constraint violation. It is shown that CG and ECG result in comparable speed of response, and both outperform the conventional RG. All three schemes have large constrained domains of attraction. The transient performance improvements in the CG and ECG cases are obtained at the expense of increased computing effort to solve a larger dimensional quadratic programming problem. Measured parametric uncertainties, unmeasured parametric uncertainties, time-varying disturbances and computational complexity reduction are addressed.

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“…where r(0) is the actual set-point at t = 0, while R = R T > 0 and Q = Q T > 0 are weight matrices, with Q satisfying (11). The solution of this problem has the form,…”

Section: B Ecg With Disturbancesmentioning

confidence: 99%

Section: Extended Command Governormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The matrix Q satisfying(11) was computed, based onĀ T QĀ − Q = −0.01I, where I is the identity matrix,…”

mentioning

confidence: 99%

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Limit Protection in Gas Turbine Engines Based on Reference and Extended Command Governors

Kolmanovsky¹,

Merill²

2014

50th AIAA/ASME/SAE/ASEE Joint Propulsion Conference

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“…The applied model was built on the basis of Rowen's model (Rowen, 1992) and by using real data for tuning the GT parameters. Kolmanovsky et al (2012) developed a robust control system for aero gas turbines. To develop stable control architectures for gas turbine engines, Pakmehr et al (2013) investigated a nonlinear physics-based dynamic model of a twin-shaft aero engine.…”

Section: White-box Modelsmentioning

confidence: 99%

Design of conventional and neural network based controllers for a single-shaft gas turbine

Asgari

Jegarkandi

Chen

et al. 2017

AEAT

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Purpose -The purpose of this paper is to develop and compare conventional and neural network based controllers for gas turbines.Design/methodology/approach -Design of two different controllers is considered. These controllers consist of a NARMA-L2 which is an ANN-based nonlinear autoregressive moving average (NARMA) controller with feedback linearization, and a conventional proportional-integrator-derivative (PID) controller for a low-power aero gas turbine.They are briefly described and their parameters are adjusted and tuned in Simulink-MATLAB environment according to the requirement of the gas turbine system and the control objectives. For this purpose, Simulink and neural network based modelling is employed. Performances of the controllers are explored and compared on the base of design criteria and performance indices.Findings -It is shown that NARMA-L2, as a neural network based controller, has a superior performance to the PID controller.Practical implications -Using artificial intelligence in gas turbine control systems.Originality/value -Providing a novel methodology for control of gas turbines.

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Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation

Liao‐McPherson

Huang

Kim

et al. 2020

Intl J Robust & Nonlinear

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This article presents the development and experimental validation of an emissions oriented model predictive controller for a diesel engine. The control objective is to minimize cumulative NOx and hydrocarbon emissions while limiting visible smoke production and without compromising fuel economy or torque response. This is accomplished by using a supervisory model predictive controller (SMPC) and nonlinear model predictive controller (NMPC) in tandem. The SMPC controller coordinates the exhaust gas recirculation (EGR) rate target and fuel supplied to the engine in real time to satisfy combustion quality constraints, while the NMPC controller tracks the EGR rate target by manipulating the EGR throttle, EGR valve, and variable geometry turbine. The NMPC controller uses MPC for feedforward and feedback in a novel configuration to simultaneously achieve fast tracking performance, disturbance rejection, and robustness. We demonstrate that the proposed diesel engine MPC controller is able to reduce cumulative emissions by 10% to 15% relative to a state of the art benchmark strategy when placed in closed loop with an engine on a transient dynamometer.

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Robust control and limit protection in aircraft gas turbine engines

Cited by 18 publications

References 11 publications

Limit Protection in Gas Turbine Engines Based on Reference and Extended Command Governors

Limit Protection in Gas Turbine Engines Based on Reference and Extended Command Governors

Design of conventional and neural network based controllers for a single-shaft gas turbine

Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation

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