Applying a finite-horizon numerical optimization method to a periodic optimal control problem

Automatica ◽  
2008 ◽  
Vol 44 (6) ◽  
pp. 1642-1651 ◽  
Author(s):  
Jeffrey Azzato ◽  
Jacek B. Krawczyk
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Numerical Optimization ◽  
Optimization Method ◽  
Finite Horizon

Energy efficiency path planning for a quadrotor aerial vehicle

2021 ◽  
pp. 014233122110585
Author(s):  
Fouad Yacef ◽  
Nassim Rizoug ◽  
Laid Degaa ◽  
Omar Bouhali ◽  
Mustapha Hamerlain
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Weather Conditions ◽  
Optimization Method ◽  
Control Approach ◽  
Mission Success ◽  
Aerial Vehicle ◽  
Vehicle Trajectory ◽  
Point To Point

Unmanned aerial vehicles are used today in many real-world applications. In all these applications, the vehicle endurance (flight time) is an important constraint that affects mission success. This study investigates the limitations of embedded energy for a quadrotor aerial vehicle. We consider a quadrotor simple tasked to travel from an initial hover configuration to a final hover configuration. In order to have a precise approximation of the consumed energy, we propose a power consumption model with battery dynamic, motor dynamic, and rotor efficiency function. We then introduce an optimization algorithm to minimize the energy consumption during quadrotor aerial vehicle mission. The proposed algorithm is based on an optimal control problem formulated for the quadrotor model and solved using nonlinear programming. In the optimal control problem, we seek to find control inputs (rotor velocity) and vehicle trajectory between initial and final configurations that minimize the consumed energy during a point-to-point mission. We extensively test in simulation experiments the proposed algorithm under normal and windy weather conditions. We compare the proposed optimization method with a nonlinear adaptive control approach to highlight the saved amount of energy.

Optimal motion planning of juggling by 3-DOF manipulators using adaptive PSO algorithm

Robotica ◽  
2013 ◽  
Vol 32 (6) ◽  
pp. 967-984 ◽  
Author(s):  
Adel Akbarimajd
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Minimum Energy ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Horizontal Distance ◽  
Optimal Motion Planning ◽  
Adaptive Pso ◽  
Joint Motions

SUMMARYThree-DOF manipulators were employed for juggling of polygonal objects in order to have full control over object's configuration. Dynamic grasp condition is obtained for the instances that the manipulators carry the object on their palms. Manipulation problem is modeled as a nonlinear optimal control problem. In this optimal control problem, time of free flight is used as a free parameter to determine throw and catch times. Cost function is selected to get maximum covered horizontal distance using minimum energy. By selecting third-order polynomials for joint motions, the problem is changed to a constrained parameter selection problem. Adaptive particle swarm optimization method is consequently employed to solve the optimization problem. Effectiveness of the optimization algorithm is verified by a set of simulations in MSC. ADAMS.

scholarly journals Multiphase Return Trajectory Optimization Based on Hybrid Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yi Yang ◽  
Ying Nan
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Trajectory Optimization ◽  
Pseudospectral Method ◽  
Optimization Method ◽  
Natural Computation ◽  
Improve Calculation ◽  
Computation Algorithm ◽  
The Right

A hybrid trajectory optimization method consisting of Gauss pseudospectral method (GPM) and natural computation algorithm has been developed and utilized to solve multiphase return trajectory optimization problem, where a phase is defined as a subinterval in which the right-hand side of the differential equation is continuous. GPM converts the optimal control problem to a nonlinear programming problem (NLP), which helps to improve calculation accuracy and speed of natural computation algorithm. Through numerical simulations, it is found that the multiphase optimal control problem could be solved perfectly.

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