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This paper considers the application of finite-time control to a Cucker-Smale flocking model of autonomous agents with collision avoidance. A mathematical expression for the upper bound on the flocking time is derived. Previous results without considering collision avoidance showed that the flocking time decreases as the number of robots in the flock increases, which is counter-intuitive. We showed...
In this paper is proposed the methodology for determining the true chaos from the position of nonlinear dynamics for distributed mechanical systems in the form of a beam structure of two beams described by the kinematic firstapproximation hypothesis (Euler-Bernoulli). There is a small gap between the beams. The lower beam (beam 2) will be considered as an elastic base for the upper beam (beam 1)....
Recurrent neural network has been widely used as auto-regressive model for time series. The most commonly used training method for recurrent neural network is back propagation. However, recurrent neural networks trained with back propagation can get trapped at local minima and saddle points. In these cases, auto-regressive models cannot effectively model time series patterns. In order to address these...
Local community detection (or local clustering) is of fundamental importance in large network analysis. Random walk based methods have been routinely used in this task. Most existing random walk methods are based on the single-walker model. However, without any guidance, a single-walker may not be adequate to effectively capture the local cluster. In this paper, we study a multi-walker chain (MWC)...
In this paper, an adaptive adjustment method for the kernel parameter used in the kernel adaptive filters (KAFs) is proposed. The KAF is one of the linear-in-the-parameters (LIP) nonlinear filters, and is based on the kernel method used in machine learning. Typically, the Gaussian kernel function is used, but there is no effective method for automatically adjusting its parameter that influences the...
Reaching law approach is a straightforward method of ensuring the desired dynamic response of a variable structure system. In our paper, this method is used to design a new non-switching type discrete time sliding mode control strategy. The strategy is shown to ensure a finite time reaching phase, stability of the sliding motion and bounded convergence rate of the sliding variable to the vicinity...
In the last few decades, many opinion formation models have been proposed to describe how opinion interactions among individuals result in different distributions of opinions within social systems. Emotion plays a key role when people try to influence others' opinions, but applying emotion to opinion formation models has attracted little attention. In this paper, we discuss how emotion can affect...
Underwater acoustic (UWA) channel is a complex time-space- and frequency-variant channel, which is one of the most difficult wireless communication channels so far. Coherent communication has become a hotspot in high speed underwater acoustic communication. To achieve the low bit error rate and high data transmission rate, the channel equalization technique must be introduced for coherent underwater...
In this paper, the dynamic model of the two-link flexible manipulator with payload is analyzed using Euler-Lagrange equation. And then, a fast nonsingular terminal sliding mode controller is proposed for trajectory tracking problem of the manipulator. The stability of the control system is proved by the Lyapunov theory. Finally, simulation experiments were carried out in MATLAB and the results illustrate...
This paper presents the cascaded PI-continuous second order sliding mode control for induction motor in the presence of operational constraints. The inner-loop Sliding Mode Control (SMC) is designed to control the current dynamics of the motor while the outer-loop control is the PI control of speed. The main advantages of the proposed method are that the PI control provides reference to inner-loop...
The method principal component (PCA) allows to allocate from a matrix of these several objects with a large amount of signs only 1–3 vectors containing 90–95% of information. Usually measuring problem of assessment of these main components is solved by the iterative NIPALS procedure or the algebraic SVD procedure, however both of these methods often give ambiguous estimates. For the purpose of elimination...
In this work, super twisting controller is tested for paraplegic knee stimulation. In contrary to the literature controllers proposed for the paraplegic patient, our command assures a uniform global convergence using the Lyapunov function. We studied, firstly, the performances of the controller by comparing them with those of literature. Then, we proposed an adaptive super twisting controller assuring...
In this paper, the convergence and the stability analysis of two Induction Motor (IM) rotor time constant (Tr) estimators are performed. Both estimators are Model Reference Adaptive System (MRAS) based, first considering the rotor flux vector, second the reactive power as the state variable. The stability analysis is based on Lyapunov and Popov criteria, passivity formalism and positive real function...
This paper has as a start point the metaheuristic Particle Swarm Optimization (PSO), which has very good abilities to solve many types of optimization problems. As a main contribution, this work proposes an intelligent algorithm derived from PSO. This algorithm has two main characteristics. The first one consists in the use of an improved version of PSO, namely Hybrid Topology Particle Swarm Optimization...
This paper presents a stabilizing model predictive control (MPC) algorithm based on the off-line computation of sequence of 1-step controllable sets for linear parameter varying systems and a parameter learning technique that improves its performance. The presented MPC algorithm guarantees non-monotone convergence towards a suitably chosen terminal set regardless of the system parameters, while the...
This paper presents a real-time implementation of an identification-based linear control law on a twin rotor MIMO system. Identification is performed via dynamical neural networks which-under mild conditions-guarantee exponential convergence to zero of the identification error. Once the plant model is obtained and linearized, a stabilizing linear state feedback control law is synthesized via linear...
Due to the rapid growth in scale and complexity of information networks, self-organizing systems have been focused on for realizing new network control architectures that have high scalability, adaptability, and robustness. However, in self-organizing systems, the uncertainty (incompleteness, ambiguity, and dynamicity) of information observable for components in the system can lead to the slow adaptation...
In this paper sliding mode controller is designed in comparison with the linear state space feedback controllers namely the pole placement controller and linear quadratic regulator to eliminate the chaotic limit cycle oscillations in Van der Pol system induced by an external sinusoidal excitation in order to avoid failure in physical structures. The controller design is based on the mathematical model...
This paper focuses on solving the ship course tracking problem by using Zhang dynamics (ZD) method and a new Zhang finite difference (ZFD) formula. Via ZD method, which is a powerful class of dynamics to solve online time-varying problems, the so called ZD controller of ship course tracking is designed. Then, a 1-node-ahead differentiation formula within ZFD framework termed as 4-node g-square finite...
The dynamic characteristics of a hydraulic turbine governing system is determined by the parameters of the hydraulic turbine governor. There are several drawbacks of the conventional particle swarm algorithm in parameter optimization, such as low speed of convergence, low accuracy and being inclined to result in partial optimization during the process of optimization. This paper introduced concave...
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