A control parametrization based path planning method for the quad-rotor uavs

Abstract

A time optimal path planning problem for the Quad-rotor unmanned aerial vehicles (UAVs) is investigated in this paper. A 3D environment with obstacles is considered, which makes the problem more challenging. To tackle this challenge, the problem is formulated as a nonlinear optimal control problem with continuous state inequality constraints and terminal equality constraints. A control parametrization based method is proposed. Particularly, the constraint transcription method together with a local smoothing technique is utilized to handle the continuous inequality constraints. The original problem is then transformed into a nonlinear program. The corresponding gradient formulas for both of the cost function and the constraints are derived, respectively. Simulation results show that the proposed path planning method has less tracking error than that of the rapid-exploring random tree (RRT) algorithm and that of the A star algorithm. In addition, the motor speed has less changes for the proposed algorithm than that of the other two algorithms.

Output feedback attitude control for rigid spacecraft under attitude constraints

“…By introducing the APF into the procedure of controller design, different control schemes have been proposed to guarantee the feasibility of attitude pointing constraints and the convergence of closed-loop system, such as APF-based proportional and derivative (PD) controller [7,3,9], APF-based backsteping controller [7], and APF-based sliding mode controller [23,15]. The angular velocity and input constrains are also considered in [9] by utilizing optimal control method [17,10,8,2,24,11]. Although most of the existing researches have obtained numerous admirable results for spacecraft attitude maneuver with attitude constraints, it is still a problem when the angular velocity and inertia matrix can not always be measured accurately.…”

Hybrid dynamic optimal tracking control of hydraulic cylinder speed in injection molding industry process

“…Control Paremeterization. In this section, we first introduce the control parameterization (CP) technique [20,21,22,23,24,25,26,27,28,29,30,31] to parameterize the controller U (t) in a sequence, which can easily transform the original optimal control problem into a sequence optimal parameter selection problem. The purpose of this step is to facilitate the design and implementation of our subsequent optimization algorithm.…”