scholarly journals Finite Time Controller for Point Stabilization of a Spherical Underwater Roving Robot

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Zhimin Liu ◽  
Hanxu Sun ◽  
Yansheng Li ◽  
Qingxuan Jia ◽  
Ming Chu
Keyword(s):  
Finite Time ◽  
Cfd Simulation ◽  
Dimensional Space ◽  
Convergence Time ◽  
Hydrodynamic Characteristics ◽  
Control Effort ◽  
Physical Prototype ◽  
Simulation And Experiment ◽  
The Stability ◽  
Point Stabilization

The finite time controller is proposed to solve the point stabilization problem for a novel underwater spherical roving robot (BYSQ-3) in two-dimensional space. The finite time design scheme is a new method; the main advantage of this control scheme is that it can steer the robot to the origin in fast converging times without excessive control effort. Firstly, the physical prototype of BYSQ-3 is introduced and the equations describing the kinematics and dynamics of BYSQ-3 are established. Secondly, the finite time controller is constructed based on the backstepping method; the explicit form of the finite time controller is more concise compared with the other finite time controllers; there is no virtual input in the design process and the stability analysis is simple; the designed controller is easy for engineering implementation. Thirdly, the hydrodynamic characteristics is analyzed by CFD simulation; the simulation and experiment results are presented to validate the shorter convergence time and better stability character of the controller.

Variable Gain Super-Twisting Control of GMAW Process for Pipeline Welding

2015 ◽  
Vol 137 (7) ◽  
Author(s):  
Manas Kr. Bera ◽  
Bijnan Bandyopadhyay ◽  
A. K. Paul
Keyword(s):  
Finite Time ◽  
Sliding Mode ◽  
Gas Metal Arc Welding ◽  
Control Effort ◽  
Variable Gain ◽  
Output Tracking ◽  
Pipeline Welding ◽  
The Stability ◽  
Twisting Control ◽  
Super Twisting Control

Quality control is the key issue that needs to be addressed in any gas metal arc welding (GMAW) system, especially in robotic pipeline welding system. This paper explores a second-order sliding mode control (SMC) strategy—a variable gain super-twisting control, to maximize the productivity, consistency in welding quality. This is achieved by the robust finite time output tracking of GMAW system. A nonlinear multi-input multi-output (MIMO) model of GMAW system has been considered here for the design of variable gain super-twisting (VGST) controller by which complete rejection of the bounded uncertainties/disturbances is possible and the adaptive characteristic of its gains help to use the control effort effectively. The stability of internal dynamics of the system is studied to establish the feasibility of solving the robust finite time output tracking problem. The stability of the overall system has been analyzed using Lyapunov stability criterion. The performance of the controller is demonstrated using the model of the system emulating the realistic conditions of operation. The simulation results are presented to illustrate the efficacy of the controller.

Distributed learning and mutual adaptation

2006 ◽  
Vol 14 (2) ◽  
pp. 313-332 ◽  
Author(s):  
Daniel L. Schwartz ◽  
Taylor Martin
Keyword(s):  
Distributed Cognition ◽  
Dimensional Space ◽  
Distributed Learning ◽  
Early Learning ◽  
Learning Technologies ◽  
Two Dimensional ◽  
Present Evidence ◽  
Mutual Adaptation ◽  
Initial Learning ◽  
The Stability

If distributed cognition is to become a general analytic frame, it needs to handle more aspects of cognition than just highly efficient problem solving. It should also handle learning. We identify four classes of distributed learning: induction, repurposing, symbiotic tuning, and mutual adaptation. The four classes of distributed learning fit into a two-dimensional space defined by the stability and adaptability of individuals and their environments. In all four classes of learning, people and their environments are highly interdependent during initial learning. At the same time, we present evidence indicating that certain types of interdependence in early learning, most notably mutual adaptation, can help prepare people to be less dependent on their immediate environment and more adaptive when they confront new environments. We also describe and test examples of learning technologies that implement mutual adaptation.

scholarly journals TRAVERSABLE WORMHOLES IN A STRING CLOUD

2008 ◽  
Vol 17 (08) ◽  
pp. 1179-1196 ◽  
Author(s):  
MARTÍN G. RICHARTE ◽  
CLAUDIO SIMEONE
Keyword(s):  
Thin Shell ◽  
Dimensional Space ◽  
Space Time ◽  
Exotic Matter ◽  
Spherically Symmetric ◽  
Related Model ◽  
Traversable Wormholes ◽  
Dimensional Space Time ◽  
Thin Shell Wormholes ◽  
The Stability

We study spherically symmetric thin shell wormholes in a string cloud background in (3 + 1)-dimensional space–time. The amount of exotic matter required for the construction, the traversability and the stability of such wormholes under radial perturbations are analyzed as functions of the parameters of the model. In addition, in the appendices a nonperturbative approach to the dynamics and a possible extension of the analysis to a related model are briefly discussed.

A finite-time H-infinite adaptive fault-tolerant controller considering time delay for flutter suppression of airfoil flutter

2019 ◽  
Vol 234 (2) ◽  
pp. 293-307
Author(s):  
Gao Ming-Zhou ◽  
Chen Xin-Yi ◽  
Han Rong ◽  
Yao Jian-Yong
Keyword(s):  
Finite Time ◽  
Control Method ◽  
Controller Design ◽  
Fault Tolerant ◽  
Linear Matrix ◽  
Control Methods ◽  
Actuator Faults ◽  
Control Delay ◽  
Modeling Uncertainties ◽  
The Stability

To suppress airfoil flutter, a lot of control methods have been proposed, such as classical control methods and optimal control methods. However, these methods did not consider the influence of actuator faults and control delay. This paper proposes a new finite-time H∞ adaptive fault-tolerant flutter controller by radial basis function neural network technology and adaptive fault-tolerant control method, taking into account actuator faults, control delay, modeling uncertainties, and external disturbances. The theoretic section of this paper is about airfoil flutter dynamic modeling and adaptive fault-tolerant controller design. Lyapunov function and linear matrix inequality are employed to prove the stability of the proposed control method of this paper. The numeral simulation section further proves the effectiveness and robustness of the proposed control algorithm of this paper.

scholarly journals Finite-time stabilization in optimal time of homogeneous quasilinear hyperbolic systems in one dimensional space

2020 ◽  
Vol 26 ◽  
pp. 119 ◽  
Author(s):  
Jean-Michel Coron ◽  
Hoai-Minh Nguyen
Keyword(s):  
Finite Time ◽  
Nonlinear Boundary ◽  
Dimensional Space ◽  
Hyperbolic Systems ◽  
Optimal Time ◽  
Local Boundary ◽  
Quasilinear Hyperbolic Systems ◽  
Non Local ◽  
Linearized System ◽  
Finite Time Stabilization

We consider the finite-time stabilization of homogeneous quasilinear hyperbolic systems with one side controls and with nonlinear boundary condition at the other side. We present time-independent feedbacks leading to the finite-time stabilization in any time larger than the optimal time for the null controllability of the linearized system if the initial condition is sufficiently small. One of the key technical points is to establish the local well-posedness of quasilinear hyperbolic systems with nonlinear, non-local boundary conditions.

scholarly journals Recursive Calculation of Survival Probabilities

1991 ◽  
Vol 21 (2) ◽  
pp. 199-221 ◽  
Author(s):  
David C. M. Dickson ◽  
Howard R. Waters
Keyword(s):  
Finite Time ◽  
Approximate Calculation ◽  
Risk Model ◽  
Classical Risk Model ◽  
Infinite Time ◽  
Numerical Examples ◽  
Survival Probabilities ◽  
Recursive Calculation ◽  
The Stability ◽  
The Classical Risk Model

AbstractIn this paper we present an algorithm for the approximate calculation of finite time survival probabilities for the classical risk model. We also show how this algorithm can be applied to the calculation of infinite time survival probabilities. Numerical examples are given and the stability of the algorithms is discussed.

Quaternionic Neural Networks

2009 ◽  
pp. 411-439 ◽  
Author(s):  
Teijiro Isokawa ◽  
Nobuyuki Matsui ◽  
Haruhiko Nishimura
Keyword(s):  
Neural Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Network Models ◽  
Recurrent Network ◽  
Affine Transformations ◽  
Neural Network Models ◽  
Fundamental Properties ◽  
Modern Physics ◽  
The Stability

Quaternions are a class of hypercomplex number systems, a four-dimensional extension of imaginary numbers, which are extensively used in various fields such as modern physics and computer graphics. Although the number of applications of neural networks employing quaternions is comparatively less than that of complex-valued neural networks, it has been increasing recently. In this chapter, the authors describe two types of quaternionic neural network models. One type is a multilayer perceptron based on 3D geometrical affine transformations by quaternions. The operations that can be performed in this network are translation, dilatation, and spatial rotation in three-dimensional space. Several examples are provided in order to demonstrate the utility of this network. The other type is a Hopfield-type recurrent network whose parameters are directly encoded into quaternions. The stability of this network is demonstrated by proving that the energy decreases monotonically with respect to the change in neuron states. The fundamental properties of this network are presented through the network with three neurons.

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