Integration of MATLAB Simulink® Models with the Vertical Motion Simulator

Lewis, Emily K.; Vuong, Nghia

doi:10.2514/6.2012-4797

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…The implementation results of the proposed control algorithms in software in the loop test bed are shown in Figures (11) -(14). According to figures (5) - (14), Comparing simulation and implementation result show some deviation among these results. The major source of deviation is originated from delay time corresponding to transmission data between on-board electronic and simulator computer.…”

Section:   mentioning

confidence: 99%

“…Note that since in real operation in orbit, there is no need to transfer data between the on-board electronic and the computer, so the mentioned error is not problematic. To compared and show these deviations, the mean error ( ), error variance ( ) and steady-state error ( ) for the two proposed approaches are summarized in Table (3) According to the figures (5)- (14) and Table (3), it is obvious that the convergence speed of parameter estimation using the second approach is higher, but it is less accurate than the first approach. These results are compared in table (4) in brief.…”

Section:   mentioning

confidence: 99%

“…Therefore, it seems necessary to design and provide an appropriate test bed with low cost and high flexibility for the implementation of various control algorithms. In this paper, a test bed for evaluation of the control algorithm in real-time mode has been made using the RTW toolbox of MATLAB software which will be called software in the loop test bed so on [13,14].…”

Section: Software In the Loop Test Bedmentioning

confidence: 99%

See 2 more Smart Citations

Unified Model Reference Adaptive Attitude Control of a Satellite in Presence of Uncertain Parameters: Design and Implementation

Saberi¹,

Dastgerdi²,

Zandieh³

2015

IJCA

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In this paper, a discrete-time model reference adaptive attitude control algorithm (MRAC) will be designed based on unified approach for a three-axis stabilized satellite. In this algorithm, environmental disturbances and nonlinear dynamic terms will be estimated as a time-varying unknown parameter. In this method, nonlinear dynamic equation of satellite is rewritten as a linear model with uncertain parameters as the main novel idea. Therefore, MRAC algorithm is designed for the linear model in the presence of uncertain parameters, and then it will be applied to the nonlinear model of the satellite in presence of uncertain or unknown parameters. The proposed method is capable of simultaneous tracking and regulation. The designed algorithm will be implemented in software in the loop test bed with the use of ARM microcontroller in real time mode in order to evaluation and verification of its performance.

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Section:   mentioning

confidence: 99%

Section:   mentioning

confidence: 99%

Section: Software In the Loop Test Bedmentioning

confidence: 99%

See 1 more Smart Citation

Unified Model Reference Adaptive Attitude Control of a Satellite in Presence of Uncertain Parameters: Design and Implementation

Saberi¹,

Dastgerdi²,

Zandieh³

2015

IJCA

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Piloted Simulator Evaluation Results of Flight Physics Based Stall Recovery Guidance

Lombaerts

Schuet

Stepanyan

et al. 2018

2018 AIAA Guidance, Navigation, and Control Conference

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Recent studies have shown that loss of control in flight is the most frequent primary cause of accidents. A significant share of accidents in this category can be remedied by upset prevention if possible, and by upset recovery if necessary, in this order of priorities. One of the most important upsets to recover from is stall. Recent accidents have shown that a correct stall recovery maneuver remains a big challenge in civil aviation, partly due to a lack of pilot training. A possible strategy to support the flight crew in this demanding context is calculating a recovery guidance signal, and showing this signal in an intuitive way on one of the cockpit displays, for example by means of the flight director. Different methods for calculating the recovery signal, one based on fast model predictive control and another using an energy based approach, have been evaluated in four relevant operational scenarios by experienced commercial as well as test pilots in the Vertical Motion Simulator at NASA Ames Research Center. Evaluation results show that this approach supports the pilots in improving their stall recovery performance.

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Command and Control Concepts for a Lift Plus Cruise Electric Vertical Takeoff and Landing Vehicle

Kaneshige

Lombaerts

Shish

et al. 2023

AIAA AVIATION 2023 Forum

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Integration of MATLAB Simulink® Models with the Vertical Motion Simulator

Cited by 4 publications

References 4 publications

Unified Model Reference Adaptive Attitude Control of a Satellite in Presence of Uncertain Parameters: Design and Implementation

Unified Model Reference Adaptive Attitude Control of a Satellite in Presence of Uncertain Parameters: Design and Implementation

Piloted Simulator Evaluation Results of Flight Physics Based Stall Recovery Guidance

Command and Control Concepts for a Lift Plus Cruise Electric Vertical Takeoff and Landing Vehicle

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