1,466 research outputs found
Event-triggered gain scheduling of reaction-diffusion PDEs
This paper deals with the problem of boundary stabilization of 1D
reaction-diffusion PDEs with a time- and space- varying reaction coefficient.
The boundary control design relies on the backstepping approach. The gains of
the boundary control are scheduled under two suitable event-triggered
mechanisms. More precisely, gains are computed/updated on events according to
two state-dependent event-triggering conditions: static-based and dynamic-based
conditions, under which, the Zeno behavior is avoided and well-posedness as
well as exponential stability of the closed-loop system are guaranteed.
Numerical simulations are presented to illustrate the results.Comment: 20 pages, 5 figures, submitted to SICO
Predictor-Feedback Stabilization of Multi-Input Nonlinear Systems
We develop a predictor-feedback control design for multi-input nonlinear
systems with distinct input delays, of arbitrary length, in each individual
input channel. Due to the fact that different input signals reach the plant at
different time instants, the key design challenge, which we resolve, is the
construction of the predictors of the plant's state over distinct prediction
horizons such that the corresponding input delays are compensated. Global
asymptotic stability of the closed-loop system is established by utilizing
arguments based on Lyapunov functionals or estimates on solutions. We
specialize our methodology to linear systems for which the predictor-feedback
control laws are available explicitly and for which global exponential
stability is achievable. A detailed example is provided dealing with the
stabilization of the nonholonomic unicycle, subject to two different input
delays affecting the speed and turning rate, for the illustration of our
methodology.Comment: Submitted to IEEE Transactions on Automatic Control on May 19 201
Time-and event-driven communication process for networked control systems: A survey
Copyright © 2014 Lei Zou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In recent years, theoretical and practical research topics on networked control systems (NCSs) have gained an increasing interest from many researchers in a variety of disciplines owing to the extensive applications of NCSs in practice. In particular, an urgent need has arisen to understand the effects of communication processes on system performances. Sampling and protocol are two fundamental aspects of a communication process which have attracted a great deal of research attention. Most research focus has been on the analysis and control of dynamical behaviors under certain sampling procedures and communication protocols. In this paper, we aim to survey some recent advances on the analysis and synthesis issues of NCSs with different sampling procedures (time-and event-driven sampling) and protocols (static and dynamic protocols). First, these sampling procedures and protocols are introduced in detail according to their engineering backgrounds as well as dynamic natures. Then, the developments of the stabilization, control, and filtering problems are systematically reviewed and discussed in great detail. Finally, we conclude the paper by outlining future research challenges for analysis and synthesis problems of NCSs with different communication processes.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Aerial Remote Sensing in Agriculture: A Practical Approach to Area Coverage and Path Planning for Fleets of Mini Aerial Robots
In this paper, a system that allows applying precision agriculture techniques is described. The application is based on the deployment of a team of unmanned aerial vehicles that are able to take georeferenced pictures in order to create a full map by applying mosaicking procedures for postprocessing. The main contribution of this work is practical experimentation with an integrated tool. Contributions in different fields are also reported. Among them is a new one-phase automatic task partitioning manager, which is based on negotiation among the aerial vehicles, considering their state and capabilities. Once the individual tasks are assigned, an optimal path planning algorithm is in charge of determining the best path for each vehicle to follow. Also, a robust flight control based on the use of a control law that improves the maneuverability of the quadrotors has been designed. A set of field tests was performed in order to analyze all the capabilities of the system, from task negotiations to final performance. These experiments also allowed testing control robustness under different weather conditions
Tracking control with adaption of kites
A novel tracking paradigm for flying geometric trajectories using tethered
kites is presented. It is shown how the differential-geometric notion of
turning angle can be used as a one-dimensional representation of the kite
trajectory, and how this leads to a single-input single-output (SISO) tracking
problem. Based on this principle a Lyapunov-based nonlinear adaptive controller
is developed that only needs control derivatives of the kite aerodynamic model.
The resulting controller is validated using simulations with a point-mass kite
model.Comment: 20 pages, 12 figure
Adaptive and Optimal Motion Control of Multi-UAV Systems
This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations
and experiments on a multi-quadrotor UAV system testbed
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