Integrated/coordinated control of aircraft gas turbine engine and electrical power system: Towards large electrical load handling

Seok, Jinwoo; Kolmanovsky, Ilya; Girard, Anouck

doi:10.1109/cdc.2016.7798747

Cited by 16 publications

(13 citation statements)

References 20 publications

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“…This work extends and goes much beyond our previous work that appeared in a conference paper [30]. In particular, in this paper, the system configuration with the energy storage elements is treated, the power split strategy for the tradeoff between the fuel consumption and the surge margin (rather than just fuel consumption) is optimized, and MPC controllers for the large operating range of the engine are developed and demonstrated to accommodate simultaneous transients in electrical load and thrust.…”

Section: Introductionmentioning

confidence: 71%

“…In the previous work [30], the optimal power split map was based on a point that minimized fuel consumption for a given thrust and total electrical power output. In this paper, we generalize this approach and define the optimal power split range in which the fuel consumption deviates from the optimal fuel consumption by no more than 0.3%.…”

Section: B Optimal Power Splitmentioning

confidence: 99%

“…where d k is the 2 × 1 surge margin offset states vector, δ x k1 is the 2 × 1 compensated surge margin deviations vector, and F 0 2×4 I 2×2 . The cost function to be minimized is given by subject to the constraints δx min ≤ δx kjt ≤ δx max ; k 0; :::;N; δu min ≤ δu kjt ≤ δu max ; k 0; :::;N − 1; Δu min ≤ Δu kjt ≤ Δu max ; k 0; :::;N − 1 (30) where N is the prediction horizon; Q is a 5 × 5 diagonal weight matrix associated with the five errors; R is a 4 × 4 diagonal weight matrix associated with the four inputs; e kjt is the predicted error k steps ahead when the prediction is made at time instant t; δu kjt is the predicted input k steps ahead when the prediction is made at time instant t; δx min and δx max designate state bounds; and δu min ; δu max ; Δu min , and Δu max designate the bounds on the control inputs and their time rates of change.…”

Section: Rate-based Mpcmentioning

confidence: 99%

See 2 more Smart Citations

Coordinated Model Predictive Control of Aircraft Gas Turbine Engine and Power System

Seok

Kolmanovsky

Girard

2017

Journal of Guidance, Control, and Dynamics

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Motivated by the growing need to accommodate large transient thrust and electrical load requests in future more-electric aircraft, a coordinated control strategy for a gas turbine engine, generators, and energy storage is developed. An advanced two-generator configuration, with each generator connected to a shaft of the gas turbine engine, is treated. Model predictive control maximizes system performance and protects this system against constraint violations. The controller design is exploits rate-based linear prediction models. In addition, an auxiliary offset state improves the match between the linear prediction model and the nonlinear system. The auxiliary offset state allows the system to be controlled over the large operating range without requiring multiple linearizations/ controllers. The advantages of different energy storages are also compared to complement the two-generator configuration in a more electric aircraft. Primary results indicate that the coordinated model predictive control with an auxiliary offset state yields better performance than other control strategies, and it successfully controls the considered system to satisfy specified requirements over a large operating range. The battery-ultracapacitor pack allows improvement of the overall system performance.

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Section: Introductionmentioning

confidence: 71%

Section: B Optimal Power Splitmentioning

confidence: 99%

Section: Rate-based Mpcmentioning

confidence: 99%

See 1 more Smart Citation

Coordinated Model Predictive Control of Aircraft Gas Turbine Engine and Power System

Seok

Kolmanovsky

Girard

2017

Journal of Guidance, Control, and Dynamics

Self Cite

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“…The simulation results which are based on the nonlinear model were reported as the paper conclusion. 139 They proposed an engine linear model and its controller and widely discussed model predictive control (MPC) design procedure.…”

Section: More Electric and Electronic Control Algorithms Since 2004mentioning

confidence: 99%

A scientometric analysis and critical review of gas turbine aero-engines control: From Whittle engine to more-electric propulsion

Mohammadi

Fashandi

Jafari

et al. 2020

Measurement and Control

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The gas turbine aero-engine control systems over the past eight decades have been thoroughly investigated. This review purposes are to present a comprehensive reference for aero-engine control design and development based on a systematic scientometric analysis and to categorize different methods, algorithms, and approaches taken into account to improve the performance and operability of aircraft engines from the first days to present to enable this challenging technology to be adopted by aero-engine manufacturers. Initially, the benefits of the control systems are restated in terms of improved engine efficiency, reduced carbon dioxide emissions, and improved fuel economy. This is followed by a historical coverage of the proposed concepts dating back to 1936. A comprehensive scientometric analysis is then presented to introduce the main milestones in aero-engines control. Possible control strategies and concepts are classified into four distinct phases, including Single input- single output control algorithms, MIN-MAX or Cascade control algorithms, advanced control algorithms, More-electric and electronic control algorithms and critically reviewed. The advantages and disadvantages of milestones are discussed to cover all practical aspects of the review to enable the researchers to identify the current challenges in aircraft engine control systems.

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“…However, the majority of work found in the EPS diagnostics literature has focused mainly on faults at the components level like wires [11] and relays [8], and the subsystems level like generators [12] and induction motors [13,14]. While most researchers work on the performance of the linked systems like the engine and the fuel pump [1,15,16], there is a lack of investigation in isolating the faults from the EPS, which have propagating effects into other aircraft systems.…”

Section: Introductionmentioning

confidence: 99%

A System-Level Failure Propagation Detectability Using ANFIS for an Aircraft Electrical Power System

Ezhilarasu

Jennions

2020

Applied Sciences

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The Electrical Power System (EPS) in an aircraft is designed to interact extensively with other systems. With a growing trend towards more electric aircraft, the complexity of interactions between the EPS and other systems has grown. This has resulted in an increased necessity of implementing health monitoring methods like diagnosis and prognosis of the EPS at the systems level. This paper focuses on developing a diagnostic algorithm for the EPS to detect and isolate faults and their root causes that occur at the Line Replaceable Units (LRUs) connecting with aircraft systems like the engine and the fuel system. This paper aims to achieve this in two steps: (i) developing an EPS digital twin and presenting the simulation results for both healthy and fault scenarios, (ii) developing an Adaptive Neuro-Fuzzy Inference System (ANFIS) monitor to detect faults in the EPS. The results from the ANFIS monitor are processed in two methods: (i) a crisp boundary approach, and (ii) a fuzzy boundary approach. The former approach has a poor misclassification rate; hence the latter method is chosen to combine with causal reasoning for isolating root causes of these interacting faults. The results from both these methods are presented through examples in this paper.

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Integrated/coordinated control of aircraft gas turbine engine and electrical power system: Towards large electrical load handling

Cited by 16 publications

References 20 publications

Coordinated Model Predictive Control of Aircraft Gas Turbine Engine and Power System

Coordinated Model Predictive Control of Aircraft Gas Turbine Engine and Power System

A scientometric analysis and critical review of gas turbine aero-engines control: From Whittle engine to more-electric propulsion

A System-Level Failure Propagation Detectability Using ANFIS for an Aircraft Electrical Power System

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