Multiple Horizon Model Predictive Flight Control

Medagoda, Eran D. B.; Gibbens, Peter W.

doi:10.2514/1.62889

Cited by 16 publications

(13 citation statements)

References 9 publications

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“…(Gibbens and Medagoda, 2011;Lamburn, et al, 2014;Medagoda and Gibbens, 2014;Medagoda and Gibbens, 2010). …”

Section: Other Control Schemesmentioning

confidence: 99%

1-Bit processing based model predictive control for fractionated satellite missions

Bai

2014

Acta Astronautica

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In this thesis, a 1-bit processing based Model Predictive Control (OBMPC) structure is proposed for a fractionated satellite attitude control mission. Despite the appealing advantages of the MPC algorithm towards constrained MIMO control applications, implementing the MPC algorithm onboard a small satellite is certainly challenging due to the limited onboard resources. The proposed design is based on the 1-bit processing concept, which takes advantage of the affine relation between the 1-bit state feedback and multi-bit parameters to implement a multiplier free MPC controller.As multipliers are the major power consumer in online optimization, the OBMPC structure is proven to be more efficient in comparison to the conventional MPC implementation in term of power and circuit complexity. The system is in digital control nature, affected by quantization noise introduced by Δ∑ modulators. The stability issues and practical design criteria are also discussed in this work.Some other aspects are considered in this work to complete the control system. Firstly, the implementation of the OBMPC system relies on the 1-bit state feedbacks. Hence, 1-bit sensing components are needed to implement the OBMPC system. While the ∆∑ modulator based Microelectromechanical systems (MEMS) gyroscope is considered in this work, it is possible to implement this concept into other sensing components.Secondly, as the proposed attitude mission is based on the wireless inter-satellite link (ISL), a state estimator is required. However, conventional state estimators will once again introduce multi-bit signals, and compromise the simple, direct implementation of the OBMPC controller. Therefore, the 1-bit state estimator is also designed in this work to satisfy the requirements of the proposed fractionated attitude control mission.The simulation for the OBMPC is based on a 2U CubeSat model in a fractionated satellite structure, in which the payload and actuators are separated from the controller and controlled via the ISL. Matlab simulations and FPGA implementation based performance analysis shows that the OBMPC is feasible for fractionated satellite missions and is advantageous over the conventional MPC controllers. V VI

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“…(Gibbens and Medagoda, 2011;Lamburn, et al, 2014;Medagoda and Gibbens, 2014;Medagoda and Gibbens, 2010). …”

Section: Other Control Schemesmentioning

confidence: 99%

1-Bit processing based model predictive control for fractionated satellite missions

Bai

2014

Acta Astronautica

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“…Waypoints, which are usually used to definite the desired autonomous vehicle trajectory, [3][4][5][6][7][8] are the sets of coordinates that identify serial points in physical space. At the present time, for the specific navigation activities such as radio beacons, buoyage, satellites and the control points, waypoints are more often allied with physical artifacts to create the path planning assignments.…”

Section: Introductionmentioning

confidence: 99%

Flight Motion Controller Design using Genetic Algorithm for a Quadcopter

Tran

Nguyen

2018

Measurement and Control

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In this study, the Genetic Algorithm operability is assigned to optimize the proportional-integral-derivative controller parameters for both simulation and real-time operation of quadcopter flight motion. The optimized proportionalintegral-derivative gains, using Genetic Algorithm to minimum the fitness function via the integral of time multiplied by absolute error criterion, are then integrated to control the quadcopter flight motion. In addition, the proposed controller design is successfully implemented to the experimental real-time flight motion. The performance results are proven that the highly effective stability operation and the reliable of waypoint tracking.

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“…Thus, the aerial of maneuver achievements including hovering, navigation, flying path and obstacle avoidance are vital. UAVs (Cleave, 2004, Kim, 2002, Castillo, 2007, Medagoda, 2014, Borhaug, 2005, Cruz, 2005, Yoon, 2013, Chiou, 2013, Budiyono, 2007 are multiple input multiple output (MIMO), nonlinear, under-actuated, unstable and highly coupled systems (Yoon, 2013, Chiou, 2013. Because of these characteristics, the system controller is designed to face up the challenging missions.…”

Section: Introductionmentioning

confidence: 99%

“…Motion fly path planning of UAVs have been designed for flight route testing. Since the UAVs moving in 3D space for surveillance tasks, the popular motion is suggested (Kim, 2002, Castillo, 2007, Medagoda, 2014, Ana, 2012 the Helix flight path.…”

Section: Introductionmentioning

confidence: 99%

Design Genetic Algorithm Optimization Education Software based Fuzzy Controller for a Tricopter Fly Path Planning

Tran

Chiou

Peng

2016

EURASIA J MATH SCI T

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In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The proposed controller underlines the superior tracking performance over standard Fuzzy Logic Controller. It is highly adaptive and can counteract environmental disturbances while guaranteeing global asymptotic stability and robust waypoint tracking.

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Multiple Horizon Model Predictive Flight Control

Cited by 16 publications

References 9 publications

1-Bit processing based model predictive control for fractionated satellite missions

1-Bit processing based model predictive control for fractionated satellite missions

Flight Motion Controller Design using Genetic Algorithm for a Quadcopter

Design Genetic Algorithm Optimization Education Software based Fuzzy Controller for a Tricopter Fly Path Planning

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