PDE solution to UAV/UGV trajectory planning problem by spatio-temporal estimation during wildfires

Radmanesh, Mohammadreza; Sharma, Balaji R.; Kumar, Manish; French, Donald A.

doi:10.1016/j.cja.2020.11.002

Cited by 16 publications

(7 citation statements)

References 17 publications

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“…Invoking (1), ( 4), (5) and Figure 3, the tracking errors e(k) and 𝜃 e (k) can be transformed as follows [17]:…”

Section: The Establishment Of Tracking Control Modelmentioning

confidence: 99%

“…The air-ground cooperative tracking control problem has received considerable interest for many applications, such as collaborative path planning and trajectory tracking [3][4][5][6]. The establishment of cooperative control model will affect the controller design, and enhancing control performance can cope with more complex practical cooperative tracking tasks [7,8].…”

Section: Introductionmentioning

confidence: 99%

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Air–ground trajectory tracking for autonomous mobile robot based on model predictive hybrid tracking control and multiple harmonics time‐varying disturbance observer

Xiong

Chen

Wei

et al. 2022

IET Control Theory & Appl

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This paper studies a model predictive hybrid tracking control scheme under a multiple harmonics time-varying disturbance observer for a discrete-time dynamics nonholonomic autonomous mobile robot (AMR) with disturbance. To solve the robust tracking control problem of the AMR and unmanned aerial vehicle (UAV) air-ground cooperative, a hybrid tracking control strategy combined with improved model predictive control (MPC) method is presented. First, a time-varying air-ground cooperative tracking control model based on the nonholonomic constraints AMR and UAV is established by polar coordinate transformation. Second, to estimate disturbances of the time-varying model, a multiple harmonics disturbance observer with time-varying gains is designed. A hybrid tracking control scheme for the AMR based on the estimated states and MPC method with relaxing factor and kinematics constraints is proposed. Finally, experimental results show the effectiveness of the proposed control strategy.

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“…Invoking (1), ( 4), (5) and Figure 3, the tracking errors e(k) and 𝜃 e (k) can be transformed as follows [17]:…”

Section: The Establishment Of Tracking Control Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Air–ground trajectory tracking for autonomous mobile robot based on model predictive hybrid tracking control and multiple harmonics time‐varying disturbance observer

Xiong

Chen

Wei

et al. 2022

IET Control Theory & Appl

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show abstract

“…Kim et al (2022) studied the influence of varying the frequency of a synthetic jet on flow separation over an airfoil using POD. Radmanesh et al (2021) used POD to estimate wildfires and plan UAV paths.…”

Section: Introductionmentioning

confidence: 99%

Fast Prediction of Multiple Parameters Related to Iced Airfoil Based on POD and Kriging Methods

Jin

Sang²,

Li³

et al. 2023

JAFM

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Ice accretion threatens aircraft safety. With the wide application of unmanned aerial vehicles (UAVs), the design of ice-tolerant UAVs has become a problem that must be solved. Forty conditions for the continuous/intermittent maximum icing conditions were sampled in Appendix C of Federal Aviation Regulations Part 25. Herein, numerical simulations of icing were performed on an NACA 0009 airfoil for 5, 15, and 30 min, and the ice mass and ice shapes were obtained at different times. Numerical simulations of the aerodynamic characteristics of the iced configuration at 5, 15, and 30 min were conducted, and the coefficients of lift, drag, and pitch moment were obtained. Surrogate models of the ice shape, mass of the ice accretion, lift coefficient, drag coefficient, and pitch moment coefficient at different moments were built based on proper orthogonal decomposition and kriging interpolation. The results demonstrate that the surrogate models accurately predicted the ice shape, ice mass, lift coefficient, drag coefficient, and pitch moment coefficient at different moments. Compared with the numerical simulation results, the maximum relative errors of the ice mass, lift coefficient, drag, and pitch moment predicted by the surrogate models were 7.8%, 3.4%, 3.9%, and 7.6%, respectively. This method can help in designing the ice-tolerant UAVs and envelope determination under icing conditions.

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“…While the use of Bernstein surfaces in path planning applications is novel to the best of the author's knowledge, the use of other polynomial bases in PDE based OCPs has been explored to some extent. Power series [30], proper orthogonal decomposition [31], and fifth degree polynomial curves [32] are examples of such polynomial bases which have been used for solutions in cases of multi-agent path planning, or planning in complex flow environments. Even so, the geometric properties and efficiency of Bernstein surfaces make them ideal in the case of Cosserat rod path planning, as they can guarantee safe trajectories and constraint satisfaction at low orders of approximation.…”

Section: Introductionmentioning

confidence: 99%

Robust and Adaptive Sampled-Data Control of Twisted and Coiled Artificial Muscles

Hammond

Cichella

Weerakkody

et al. 2022

IEEE Control Syst. Lett.

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This paper presents a method for optimal motion planning of continuum robots by employing Bernstein surfaces to approximate the system's dynamics and impose complex constraints, including collision avoidance. The main contribution is the approximation of infinite-dimensional continuous problems into their discrete counterparts, facilitating their solution using standard optimization solvers. This discretization leverages the unique properties of Bernstein surface, providing a framework that extends previous works which focused on ODEs approximated by Bernstein polynomials. Numerical validations are conducted through several numerical scenarios. The presented methodology offers a promising direction for solving complex optimal control problems in the realm of soft robotics.

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PDE solution to UAV/UGV trajectory planning problem by spatio-temporal estimation during wildfires

Cited by 16 publications

References 17 publications

Air–ground trajectory tracking for autonomous mobile robot based on model predictive hybrid tracking control and multiple harmonics time‐varying disturbance observer

Air–ground trajectory tracking for autonomous mobile robot based on model predictive hybrid tracking control and multiple harmonics time‐varying disturbance observer

Fast Prediction of Multiple Parameters Related to Iced Airfoil Based on POD and Kriging Methods

Robust and Adaptive Sampled-Data Control of Twisted and Coiled Artificial Muscles

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