On-Line Determination Of A Go-Nogo State Using A Continous Estimation Of The System Response

McPhee, Johanna; Irani, Rishad A.

doi:10.25071/10315/35395

Cited by 4 publications

(9 citation statements)

References 3 publications

(6 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This chapter is based on a paper that was presented at the Canadian Society for Mechanical Engineering International Congress 2018 (CSME 2018) [37]. Additionally the work was used as part of an unmanned aerial vehicle landing study which was presented at the IEEE Oceans 18 conference [38].…”

Section: Chapter 4 Advancing a Wave Prediction Algorithm For Breach Cmentioning

confidence: 99%

Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

McPhee¹

Self Cite

View full text Add to dashboard Cite

Improvements to launch and recovery operations at sea are driven by the desire to increase safety and operational availability. This thesis presents various tools to improve motion compensation strategies in maritime launch and recovery: a 3D computer simulator to examine wave synchronization, a signal prediction algorithm for Go-NoGo states and a hardware setup to simulate ship and wave motion. The 3D simulator of towed body dynamics was advanced to model the wave interactions with the cable and towed body as the body exits the water. Small scale simulations were run to investigate the inclusion of wave synchronization in established active heave compensation strategies where the hypothesis that wave synchronization would reduce variations in cable tension was not supported; the simulations demonstrated that wave synchronization increased variations in cable tension compared to simulations not using motion compensation. The use of a signal prediction method that forecasts a periodic signal based only on historic data of the signal was explored. The method is a means to predict safe breach events where the prediction algorithm was advanced and tuned to determine Go-NoGo states. A Go scenario identified by the mean and one standard deviation of the predicted signal was found to produce a Go-NoGo signal that agreed most with the desired Go-NoGo signal for forecasts up to 10 s. For the development of laboratory equipment for the Carleton University flume tank, a ship motion simulator was designed and built to emulate 5 degrees-of-freedom of ship motion and a kinematic analysis was performed to characterize the system workspace. For producing waves in the flume tank, a design methodology was developed for the design of a plunger-type wavemaker. A numerical model for determining the wave amplitude to actuator stroke length ratio was advanced to include the effects of a flow current. The design methodology enables the designer to select an appropriate actuator and plunger shape based on an operating point that incorporates multiple design variables.

show abstract

Section: Chapter 4 Advancing a Wave Prediction Algorithm For Breach Cmentioning

confidence: 99%

Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

McPhee¹

Self Cite

View full text Add to dashboard Cite

show abstract

“…The SPA utilizes an FFT and a linear Kalman filter to predict ship motion. Figure 2.3 is a schematic diagram of the SPA which was advanced by McPhee [8], where ship motion, such as roll, is observed over an evaluation window T F F T to initialize an FFT. The FFT and a peak detection algorithm are used to find the dominate modes N and corresponding amplitude A F F T , frequency f F F T and phase Φ F F T of the signal.…”

Section: Ship Motion Predictionmentioning

confidence: 99%

“…The predicted signal S P red is evaluated against a threshold value, if S P red is below the threshold value over the prediction horizon, the SPA will output a Go signal. It is hypothesized that a similar motion prediction algorithm used by Woodacre et al [7] and advanced by McPhee [8] could prove beneficial to UAV-ship landings by allowing UAVs to land within specified motion thresholds and improve landing efficiency by decreasing the number of landing attempts. Using the SPA to facilitate the landing of a UAV on a ship will be tested in simulation on a Quad Rotor (QR) helicopter.…”

Section: Ship Motion Predictionmentioning

confidence: 99%

“…A signal prediction algorithm developed by Kuchler et al [84], used by Woodacre et al [7], and further developed by McPhee and Irani [8] is used extensively throughout the presented work to predict ship motion. Ship motion, which is primarily influenced by wave actions, may be decomposed into a set of N sine waves using an FFT such that the ship motion s can be described as function of time t…”

Section: Signal Prediction Algorithmmentioning

confidence: 99%

“…Signal prediction independent of vessel type is currently used for Active Heave Compensation (AHC) on ships utilizing towing winches, allowing the system to actively pay-out or reel-in line to the towed object to attenuate the transmission of the ship's motion to the submerged equipment [7]. It is hypothesized that the same Signal Prediction Algorithm (SPA) used by Woodacre [7] and improved upon by McPhee [8,9] may be used on-board a UAV to facilitate landing. The second outcome of this thesis is the methodology for landing the UAV on a dynamic platform using the same signal prediction algorithm previously improved upon by McPhee.…”

Section: Chapter 1 Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Development of a Landing Period Indicator and the Use of Signal Prediction to Improve Landing Methodologies of Autonomous Unmanned Aerial Vehicles on Maritime Vessels

Abujoub¹

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) are becoming more prevalent in maritime operations. One of the key challenges to the safe operation of UAVs at sea is the relative motion that exists between the UAV and ship. The scope of this thesis is the creation and evaluation of a methodology for improving the overall landing performance for UAVs using signal prediction and a developed Landing Period Indicator (LPI). The research is conducted in a synthetic environment, where the test vehicle is a quad rotor UAV that is equipped with a Light Detection and Ranging (LIDAR) system to aerially detect ship motion. The observed ship motion is forecasted using signal prediction which identifies and notifies the UAV of potential landing opportunities.The Signal Prediction Algorithm (SPA) is also used for Active Heave Compensation (AHC) to facilitate the UAV in maintaining a safe low hover position above the ship deck. Further, an algorithm is developed to use the AHC system to plan trajectories that land the UAV with a specified impact velocity. The development of the LPI system is presented and its performance as a standalone and supplemental system is evaluated. ShipMo3D was used to generate 105 sets of ship motion in sea states 2-6. The results in this thesis indicate that the developed landing methodologies can improve the landing performance of ocean going helicopters. For the 105 sets of ship motion, using a combination of the SPA, AHC, and the LPI improved landing performance by 25% in two separate test groups. Moreover, the results indicate that with further tuning of the SPA, the likelihood of a safe landing can be further improved.

show abstract

Unmanned Aerial Vehicle Landing on Maritime Vessels using Signal Prediction of the Ship Motion

Abujoub

McPhee

Westin

et al. 2018

OCEANS 2018 MTS/IEEE Charleston

View full text Add to dashboard Cite

On-Line Determination Of A Go-Nogo State Using A Continous Estimation Of The System Response

Cited by 4 publications

References 3 publications

Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

Control, Simulation, and Testbed Development for Improving Maritime Launch and Recovery Operations

Development of a Landing Period Indicator and the Use of Signal Prediction to Improve Landing Methodologies of Autonomous Unmanned Aerial Vehicles on Maritime Vessels

Unmanned Aerial Vehicle Landing on Maritime Vessels using Signal Prediction of the Ship Motion

Contact Info

Product

Resources

About