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linear model predictive control for vision-based UAV pursuit

JOURNAL OF UNMANNED VEHICLE SYSTEMS 2020年第4期8卷 334-363页

作者： Surma, Christopher C. Barczyk, Martin Univ Alberta Dept Mech Engn Edmonton AB T6G 1H9 Canada

This article develops and implements a vision-based unmanned aerial vehicle (UAV)-to-UAV pursuit system using a commercial off-the-shelf Parrot *** 2.0 quadrotor. This technology is intended as a countermeasure to rogue drones carrying out activities such as flying in restricted airspace, performing unauthorized aerial videography, transporting contraband and other criminal activities, or being used as improvised weapons. The proposed approach offers benefits over other current solutions, such as wide-area radio-frequency jamming that interferes with regular communication devices or high-energy military laser systems that are expensive and time consuming to set up. A linear dynamics model of the *** 2.0 vehicle stabilized by its onboard feedback control system is derived, and its parameters are experimentally identified. A linear model predictive control is developed to track specified flight trajectories, then implemented and validated in hardware flight tests. Detection and ranging of the target UAV from the pursuer UAV's onboard monocular camera are performed using the YOLO v2 convolutional neural network algorithm. The combined control and vision design is implemented in hardware and tested quantitatively in flight experiments.

关键词： UAVs linear model predictive control modeling computer vision detection following

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linear model predictive control of the locomotion of Pepper, a humanoid robot with omnidirectional wheels 14

Linear Model Predictive Control of the locomotion of Pepper,...

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14th IEEE-RAS International Conference on Humanoid Robots (Humanoids)

作者： Lafaye, Jory Gouaillier, David Wieber, Pierre-Brice Aldebaran Grenoble France Inria Grenoble Grenoble France

ISBN: (纸本)9781479971749

The goal of this paper is to present a new real-time controller based on linear model predictive control for an omnidirectionnal wheeled humanoid robot. It is able to control both the mobile base of the robot and its body, while taking into account dynamical constraints. It makes it possible to have high velocity and acceleration motions by predicting the dynamic behavior of the robot in the future. Experimental results are proposed on the robot Pepper made by Aldebaran, showing good performance in terms of robustness and tracking control, efficiently managing kinematic and dynamical constraints.

关键词： Humanoid Robotics Mobile Robotics Omnidirectional Wheeled Robot linear model predictive control Balance control Quadratic Programming Aldebaran Pepper Robot

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linear model predictive control of Induction Machine

Linear Model Predictive Control of Induction Machine

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作者： Mynář, Z. Brno University of Technology

This article presents new control algorithm for induction machine based on linear model predictive control (MPC). controller works in similar manners as field oriented control (FOC), but control is performed in stator coordinates. This reduces computational demands as Park’s transformation is absent and induction machine mathematical model in stator coordinates contains less nonlinear elements. Another aim of proposed controller was to achieve fast torque response.

关键词： linear model predictive control MPC induction machine ACIM

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Using linear model predictive control Via Feedback linearization for Dynamic Encirclement

Using Linear Model Predictive Control Via Feedback Lineariza...

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American control Conference

作者： Hafez, A. T. Iskandarani, M. Givigi, S. N. Yousefi, S. Rabbath, Camille Alain Beaulieu, A. Queens Univ Dept Elect & Comp Engn Kingston ON Canada

ISBN: (纸本)9781479932740

An Unmanned Aerial Vehicle (UAV) team formed from two or more UAVs is used in the autonomous encirclement of a stationary target in simulation. The encirclement tactic is defined as the situation in which a target is surrounded by a UAV team in formation. This tactic can be employed by a team of UAVs to neutralize a target by restricting its movement. A combination of linear model predictive control (LMPC) and Feedback linearization (FL) is implemented on a team of UAVs in order to accomplish dynamic encirclement. The linear plant, representing each UAV, is found through System Identification then linearized using an FL technique. The contributions of this paper lay in the application of LMPC and FL to the problem of encirclement using an autonomous team of UAVs in simulation.

关键词： linear model predictive control Unmanned Aerial Vehicles Feedback linearization

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Unmanned Aerial Vehicle Formation Flying using linear model predictive control

Unmanned Aerial Vehicle Formation Flying using Linear Model ...

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8th Annual IEEE Systems Conference (SysCon)

作者： Iskandarani, M. Givigi, S. N. Fusina, G. Beaulieu, A. Royal Mil Coll Canada Kingston ON Canada Def Res & Dev Canada Toronto ON Canada

ISBN: (纸本)9781479920860

A team of three Unmanned Aerial Vehicles (UAVs) accomplishes a line abreast, triangular and cross formation based on high-level linear model predictive control (LMPC). All flight tests respect Reynold's rules of flocking, where the UAVs avoid collisions with nearby flockmates, attempt to match velocity of other team members and attempt to stay close to other flockmates. A linear system identification model is at the base of the error dynamics describing the formation control algorithm. The main contribution of this paper lies in the use of LMPC to implement multiple formations on UAVs in simulation and using the Qball-X4 quadrotor.

关键词： linear model predictive control Unmanned Aerial Vehicles Autonomous robotics Cooperative robotics

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Design of linear model predictive control for Level control Process with Output Feedback from Wireless Transmitter

Design of Linear Model Predictive Control for Level Control ...

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International Automatic control Conference (CACS)

作者： Suwannik, Podcharapol Jennawasin, Tanagorn Banjerdpongchai, David Chulalongkorn Univ Fac Engn Dept Elect Engn 254 Phayathai Rd Bangkok 10330 Thailand

ISBN: (纸本)9781509041091

This paper aims to design linear model predictive control (MPC) for level control loop using measured output from wireless transmitter. First, the level control process is identified by applying step input and measuring process variable. Then, the controller is designed. After that the time responses of process variable and manipulated variable are simulated. The effect of each MPC parameter on the responses is also discussed during tuning procedure. Finally, the simulation results of the level process show that MPC with output feedback via wireless devices gives satisfactory performance.

关键词： linear model predictive control PID control wireless transmitter level process

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Safe Formation control with Constrained linear model predictive control 16

Safe Formation Control with Constrained Linear Model Predict...

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16th International Conference on Informatics in control, Automation and Robotics (ICINCO)

作者： Feyel, Philippe Safran Elect & Def Massy France

ISBN: (纸本)9789897583803

This paper proposes a safe formation control technic based on the virtual leader-follower principle employed to build agents' trajectory. Each agent tracks its own trajectory using exclusively constrained linear model predictive control (MPC). To ensure non-collision during formation control and transient phases such as formation reconfigurations, and thanks to the flexibility of MPC, a simple and flexible method for establishing collision and obstacle avoidance linear constraints is proposed. The efficiency of the approach is illustrated by the safe formation control and reconfiguration of a swarm of quadrotor helicopters.

关键词： linear model predictive control Formation Virtual Leader Agents Obstacles Collision Avoidance Swarm

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Using Multiple Quadrotor Aircraft and linear model predictive control for the Encirclement of a Target

Using Multiple Quadrotor Aircraft and Linear Model Predictiv...

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7th Annual IEEE International Systems Conference (SysCon)

作者： Iskandarani, Mohamad Hafez, Ahmed T. Givigi, Sidney N. Beaulieu, Alain Rabbath, Camille Alain Royal Mil Coll Canada Kingston ON Canada Queens Univ Dept Elect & Comp Engn Kingston ON Canada Concordia Univ Dept Mech & Ind Engn Montreal PQ Canada

ISBN: (纸本)9781467331081;9781467331074

A Multi-Unmanned Aerial Vehicle (UAV) team formed from two or more UAVs is used in the encirclement of a target. Encirclement is defined as the situation in which a target is isolated and surrounded by a UAV team in order to maintain awareness and containment of that target. In this paper, the problem of maintaining a circular path around a target is considered and a linear model predictive control (LMPC) strategy is implemented on a team of Qball-X4 quadrotor aircraft in order to follow the circular path. The linear plant controlled by the LMPC is a combination of process models found through system identification and a linear cartesian to polar transformation. A collision avoidance system, based on potential fields, is successfully implemented between the Qball-X4 quadrotors. The contribution of this paper lay in the application of LMPC to the problem of encirclement using a team of Qball-X4 quadrotors and the ability of these UAVs to apply a collision avoidance policy.

关键词： linear model predictive control Unmanned Aerial Vehicles Collision Avoidance

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Optimal and suboptimal event-triggering in linear model predictive control

Optimal and suboptimal event-triggering in linear model pred...

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European control Conference (ECC)

作者： Jost, Michael Darup, Moritz Schulze Moennigmann, Martin Ruhr Univ Bochum Automat Control & Syst Theory Dept Mech Engn Bochum Germany

ISBN: (纸本)9783952426937

We present two event-triggered MPC laws that do not require to solve a quadratic program (QP) in every time step but only upon certain events. We prove one of the control laws results in exactly the same closed-loop behavior as classical MPC. The second control law requires even fewer QPs per time. It is suboptimal w.r.t. the MPC cost function, but still results in asymptotically stable closed-loop behavior. We illustrate the event-triggered MPC laws with two examples.

关键词： asymptotic stability closed loop systems linear systems optimal control predictive control asymptotically stable closed-loop behavior event-triggered MPC laws linear model predictive control optimal event-triggering suboptimal event-triggering Aerospace electronics Cost function Lyapunov methods Optimal control predictive control

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Encirclement of Moving Target Using linear model predictive control Via Feedback linearization

Encirclement of Moving Target Using Linear Model Predictive ...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Hafez, A. T. Iskandaram, M. Givigi, S. N. Yousefi, S. Noureldin, Aboelmaged Beaulieu, A. Queens Univ Dept Elect & Comp Engn Kingston ON Canada Royal Mil Coll Canada Kingston ON Canada

ISBN: (纸本)9781479938407

A team of Unmanned Aerial Vehicles (UAVs) is used for the dynamic encirclement of a moving target in simulation. The encirclement tactic is defined for the situation in which a target is isolated and surrounded by a group of UAVs. It may be employed by a team of UAVs to neutralize the target and restrict its movement. A combination of decentralized linear model predictive control (LMPC) and Feedback linearization (FL) is implemented on the team of UAVs in order to accomplish dynamic encirclement around a moving target. The main contribution of this paper lays in the application of LMPC and FL to solve the problem of encirclement of a moving target using an autonomous team of UAVs in simulation.

关键词： linear model predictive control Unmanned Aerial Vehicles Feedback linearization Cooperative Robotics

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