205 research outputs found
Adaptive Backstepping Control for Fractional-Order Nonlinear Systems with External Disturbance and Uncertain Parameters Using Smooth Control
In this paper, we consider controlling a class of single-input-single-output
(SISO) commensurate fractional-order nonlinear systems with parametric
uncertainty and external disturbance. Based on backstepping approach, an
adaptive controller is proposed with adaptive laws that are used to estimate
the unknown system parameters and the bound of unknown disturbance. Instead of
using discontinuous functions such as the function, an
auxiliary function is employed to obtain a smooth control input that is still
able to achieve perfect tracking in the presence of bounded disturbances.
Indeed, global boundedness of all closed-loop signals and asymptotic perfect
tracking of fractional-order system output to a given reference trajectory are
proved by using fractional directed Lyapunov method. To verify the
effectiveness of the proposed control method, simulation examples are
presented.Comment: Accepted by the IEEE Transactions on Systems, Man and Cybernetics:
Systems with Minor Revision
Solving specified-time distributed optimization problem via sampled-data-based algorithm
Despite significant advances on distributed continuous-time optimization of
multi-agent networks, there is still lack of an efficient algorithm to achieve
the goal of distributed optimization at a pre-specified time. Herein, we design
a specified-time distributed optimization algorithm for connected agents with
directed topologies to collectively minimize the sum of individual objective
functions subject to an equality constraint. With the designed algorithm, the
settling time of distributed optimization can be exactly predefined. The
specified selection of such a settling time is independent of not only the
initial conditions of agents, but also the algorithm parameters and the
communication topologies. Furthermore, the proposed algorithm can realize
specified-time optimization by exchanging information among neighbours only at
discrete sampling instants and thus reduces the communication burden. In
addition, the equality constraint is always satisfied during the whole process,
which makes the proposed algorithm applicable to online solving distributed
optimization problems such as economic dispatch. For the special case of
undirected communication topologies, a reduced-order algorithm is also
designed. Finally, the effectiveness of the theoretical analysis is justified
by numerical simulations
Intensity Mapping Functions For HDR Panorama Imaging: Weighted Histogram Averaging
It is challenging to stitch multiple images with different exposures due to
possible color distortion and loss of details in the brightest and darkest
regions of input images. In this paper, a novel intensity mapping algorithm is
first proposed by introducing a new concept of weighted histogram averaging
(WHA). The proposed WHA algorithm leverages the correspondence between the
histogram bins of two images which are built up by using the non-decreasing
property of the intensity mapping functions (IMFs). The WHA algorithm is then
adopted to synthesize a set of differently exposed panorama images. The
intermediate panorama images are finally fused via a state-of-the-art
multi-scale exposure fusion (MEF) algorithm to produce the final panorama
image. Extensive experiments indicate that the proposed WHA algorithm
significantly surpasses the related state-of-the-art intensity mapping methods.
The proposed high dynamic range (HDR) stitching algorithm also preserves
details in the brightest and darkest regions of the input images well. The
related materials will be publicly accessible at
https://github.com/yilun-xu/WHA for reproducible research.Comment: 11 pages, 5 figure
Resilient Multi-Dimensional Consensus in Adversarial Environment
This paper considers the multi-dimensional consensus in networked systems,
where some of the agents might be misbehaving (or faulty). Despite the
influence of these misbehaviors, the healthy agents aim to reach an agreement
within the convex hull of their initial states. Towards this end, this paper
develops a resilient consensus algorithm, where each healthy agent sorts its
received values on one dimension, computes two "middle points" based on the
sorted values, and moves its state toward these middle points. We further show
that the computation of middle points can be efficiently achieved by linear
programming. Compared with the existing works, this approach has lower
computational complexity. Assuming that the number of malicious agents is upper
bounded, sufficient conditions on the network topology are then presented to
guarantee the achievement of resilient consensus. Some numerical examples are
finally provided to verify the theoretical results.Comment: arXiv admin note: substantial text overlap with arXiv:1911.1083
Quantized control of non-Lipschitz nonlinear systems: a novel control framework with prescribed transient performance and lower design complexity
A novel control design framework is proposed for a class of non-Lipschitz
nonlinear systems with quantized states, meanwhile prescribed transient
performance and lower control design complexity could be guaranteed. Firstly,
different from all existing control methods for systems with state
quantization, global stability of strict-feedback nonlinear systems is achieved
without requiring the condition that the nonlinearities of the system model
satisfy global Lipschitz continuity. Secondly, a novel barrier function-free
prescribed performance control (BFPPC) method is proposed, which can guarantee
prescribed transient performance under quantized states. Thirdly, a new
\textit{W}-function-based control scheme is designed such that virtual control
signals are not required to be differentiated repeatedly and the controller
could be designed in a simple way, which guarantees global stability and lower
design complexity compared with traditional dynamic surface control (DSC).
Simulation results demonstrate the effectiveness of our method
Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems : a unified approach
Author's accepted manuscript.Available from 16/05/2022.acceptedVersio
- …