scholarly journals Combined Optimal Control and Combinatorial Optimization for Searching and Tracking Using an Unmanned Aerial Vehicle

2018 ◽  
Vol 95 (2) ◽  
pp. 691-706 ◽  
Author(s):  
Anders Albert ◽  
Lars Imsland
Keyword(s):  
Optimal Control ◽  
Combinatorial Optimization ◽  
Unmanned Aerial Vehicle ◽  
Aerial Vehicle

Optimal Control of a Multirotor Unmanned Aerial Vehicle Based on a Multiphysical Model

2020 ◽  
Author(s):  
Nicolas Michel ◽  
Zhaodan Kong ◽  
Xinfan Lin
Keyword(s):  
Optimal Control ◽  
Unmanned Aerial Vehicle ◽  
Operation Time ◽  
Rigid Body Dynamics ◽  
System Level ◽  
Optimal Velocity ◽  
Rotor Aerodynamics ◽  
Time Optimal ◽  
Aerial Vehicle ◽  
Level Model

Abstract Electric multirotor aircraft with vertical-take-off-and-landing capabilities are emerging as a revolutionary transportation mode. This paper studies optimal control of a multirotor unmanned aerial vehicle based on a system-level multiphysical model. The model considers aerodynamics of the rotor-propeller assembly, electro-mechanical dynamics of the motor and motor controller, and rigid-body dynamics of the vehicle, as control based on a system-level model incorporating all these dynamics and their coupling is missing in literature. A forward flight operation is considered for time-optimal and energy-optimal control, as well as battery voltages of 25 V and 21 V. Energy-optimal control is shown to reduce the energy required for the operation by 38.5% at 25 V, while reducing the battery voltage increases the minimum operation time by 19.8%. The energy-optimal cruise velocity is also examined, demonstrating that the optimal velocity predicted without considering rotor aerodynamics uses 35.2% more energy per meter travelled than is required at the true optimal velocity.

scholarly journals Formation of unmanned aircraft trajectory when flying around prohibited areas

2022 ◽  
pp. 47-53
Author(s):  
A. A. Lobaty ◽  
A. Y. Bumai ◽  
A. M. Avsievich
Keyword(s):  
Optimal Control ◽  
Unmanned Aerial Vehicle ◽  
Center Of Mass ◽  
Unmanned Aircraft ◽  
Control Synthesis ◽  
Initial Stage ◽  
Aerial Vehicle ◽  
Aircraft Trajectory ◽  
Flight Route ◽  
Definition Of

Considered the problem of flying over restricted areas by an unmanned aerial vehicle (UAV), which have various shapes and restrictions, set on the basis of the international airspace classification system for aviation in accordance with the Chicago Convention and the recommended principles for the formation of forbidden zones, rules for creating a flight route along forbidden zones and actions in case of border violations of restricted areas. The problem of analytical synthesis of the control acceleration of an unmanned aerial vehicle (UAV) is solved during its flight along a route passing along the boundaries of the forbidden zone of a given shape, along a given trajectory, which consists of subsequent segments located at the same height relative to the earth’s surface, in a given coordinate system. The optimal control synthesis problem is solved as an analytical definition of the optimal control of a linear non-stationary system based on the quadratic quality functional. A mathematical model of UAV motion in the horizontal plane is proposed, in the form of a system of ordinary differential equations in the Cauchy form. A law for measuring the control acceleration of the UAV’s center of mass is obtained on the basis of specifying the minimized quality functional and the corresponding constraints, which is a feature of the considered method of solving the problem. The proposed quality functional takes into account the parameters of coordinates and speed of the UAV, which correspond to the given points in the airspace, which characterize the necessary trajectory for flying around the restricted area. The derived mathematical dependences make it possible to implement them on board a UAV and minimize energy costs when guiding a UAV moving through specified points in space. Computer modeling of the derived analytical results, mathematical dependencies representing the optimal trajectory of the UAV flight along the boundaries of the forbidden zone, as well as the corresponding processes of changing the control acceleration and speed of the UAV movement was carried out, which made it possible to draw conclusions about the efficiency of the proposed method and the feasibility of its further use as a basis. for the initial stage of the synthesis of the UAV control system.

Dubins Vehicle Tracking of a Target With Unpredictable Trajectory

2011 ◽  
Author(s):  
Ross Anderson ◽  
Dejan Milutinovic´
Keyword(s):  
Optimal Control ◽  
Markov Chain ◽  
Random Walk ◽  
Cost Function ◽  
Unmanned Aerial Vehicle ◽  
Bellman Equation ◽  
Control Policy ◽  
Vehicle Tracking ◽  
Dubins Vehicle ◽  
Aerial Vehicle

Motivated by a fixed-speed, fixed-altitude Unmanned Aerial Vehicle (UAV), we seek to control the turning rate of a planar Dubins vehicle that tracks an unpredictable target at a nominal standoff distance. To account for all realizations of the uncertain target kinematics, we model the target motion as a planar random walk. A Bellman equation and an approximating Markov chain that is consistent with the stochastic kinematics is used to compute an optimal control policy that minimizes the expected value of a cost function based on the nominal distance. Our results illustrate that the control can further be applied to a class of continuous, smooth trajectories with no need for further computation.

Optimal Control Surface Mixing of a Rhomboid-Wing Unmanned Aerial Vehicle

2017 ◽  
Vol 54 (3) ◽  
pp. 1035-1046
Author(s):  
E. Miles ◽  
B. A. Broughton
Keyword(s):  
Optimal Control ◽  
Unmanned Aerial Vehicle ◽  
Control Surface ◽  
Surface Mixing ◽  
Aerial Vehicle

scholarly journals Optimal control and state estimation for unmanned aerial vehicle under random vibration and uncertainty

2019 ◽  
Vol 52 (9-10) ◽  
pp. 1264-1271 ◽  
Author(s):  
Mohammad Abdulrahman Al-Mashhadani
Keyword(s):  
Optimal Control ◽  
State Estimation ◽  
Unmanned Aerial Vehicle ◽  
Random Vibration ◽  
Large Scale ◽  
A Priori ◽  
Number Of Factors ◽  
Aerial Vehicle ◽  
Vibration Noise ◽  
Complicated Task

In the past decade, many approaches that attempted to solve the problem of optimal control and parameter estimation of an unmanned aerial vehicle with a priori uncertain parameters simply implied two ways to solve such problem. First, by the formation of optimal control based on a refined mathematical model of the unmanned aerial vehicle, and second, by using the estimation and identification methods of the model parameter of the unmanned aerial vehicle based on measured data from flight tests. However, the identification of the dynamic parameters of the unmanned aerial vehicle is a complicated task because of a number of factors such as random vibration noise, disturbance, and uncertainty of the sensor measurements. Due to the influence of random vibration noise, the problem of correlated vibration noises and uncertainty has encountered inevitably, and the accuracy of the state estimation for unmanned aerial vehicle is degraded. This study concentrates on the optimal control and state estimation for the unmanned aerial vehicle under the combination of both random vibration noise and uncertainty collected by the sensors. The effects of random vibrations at various stages of a large-scale flight that are a priori uncertain require the inclusion of identification algorithms in the optimal control loop. The results showed that the method used in the analysis had been able to provide accurate estimations.

scholarly journals Stochastic Drift Counteraction Optimal Control of a Fuel Cell-Powered Small Unmanned Aerial Vehicle

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1304
Author(s):  
Jiadi Zhang ◽  
Ilya Kolmanovsky ◽  
Mohammad Reza Amini
Keyword(s):  
Optimal Control ◽  
Fuel Cell ◽  
Power Management ◽  
Unmanned Aerial Vehicle ◽  
Power Output ◽  
Optimal Policy ◽  
Flight Time ◽  
Aerial Vehicle ◽  
Optimal Coordination ◽  
Value Iterations

This paper investigates optimal power management of a fuel cell hybrid small unmanned aerial vehicle (sUAV) from the perspective of endurance (time of flight) maximization in a stochastic environment. Stochastic drift counteraction optimal control is exploited to obtain an optimal policy for power management that coordinates the operation of the fuel cell and battery to maximize the expected flight time while accounting for the limits on the rate of change of fuel cell power output and the orientation dependence of fuel cell efficiency. The proposed power management strategy accounts for known statistics in transitions of propeller power and climb angle during the mission, but does not require the exact preview of their time histories. The optimal control policy is generated offline using value iterations implemented in Cython, demonstrating an order of magnitude speedup as compared to MATLAB. It is also shown that the value iterations can be further sped up using a discount factor, but at the cost of decreased performance. Simulation results for a 1.5 kg sUAV are reported that illustrate the optimal coordination between the fuel cell and the battery during aircraft maneuvers, including a turnpike in the battery state of charge (SOC) trajectory. As the fuel cell is not able to support fast changes in power output, the optimal policy is shown to charge the battery to the turnpike value if starting from a low initial SOC value. If starting from a high SOC value, the battery energy is used till a turnpike value of the SOC is reached with further discharge delayed to later in the flight. For the specific scenarios and simulated sUAV parameters considered, the results indicate the capability of up to 2.7 h of flight time.

Optimal Control for Thrust Vectoring Unmanned Aerial Vehicle

2010 ◽  
Vol 439-440 ◽  
pp. 292-297 ◽  
Author(s):  
Chao Zhang ◽  
Zi Yang Zhen ◽  
Dao Bo Wang ◽  
Xin Yu Meng
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Unmanned Aerial Vehicle ◽  
Control Method ◽  
Stability Control ◽  
Control Variables ◽  
Thrust Vectoring ◽  
Lq Optimal Control ◽  
Aerial Vehicle ◽  
The Common

In this paper the application of linear quadratic (LQ) optimal control based techniques to a thrust vectoring unmanned aerial vehicle (TV-UAV) control problem is considered. A general nonlinear dynamic model of the TV-UAV is built, which is different from the common UAV. The longitudinal and lateral linearization models are derived in a benchmark flight state. Two thrust deflections are considered as control variables, associated with the rudder control variables. LQ optimal control method based multivariable control system is designed for the attitude stability control problem. Simulations of a nonlinear model described UAV is carried out, results of which show the superiority of the hybrid control strategy, and also show that the TV-UAV has better properties than the common UAV, in the aspects of anti-disturbance and control efficiency.

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