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This paper aims at enhancing the level of security in chaotic communication for which a switching synchronisation scheme is designed. The authors propose a novel fractional-order chaotic system (FOCS) which undergoes switching between integer-order and fractional-order dynamical subsystems with the help of the synchronisation scheme put forward. The new fractional-order model displays rich bifurcations...
This paper presents a new fractional-order hidden strange attractor generated by a chaotic system without equilibria. The proposed non-equilibrium fractional-order chaotic system (FOCS) is asymmetric, dissimilar, topologically inequivalent to typical chaotic systems and challenges the conventional notion that the presence of unstable equilibria is mandatory to ensure the existence of chaos. The new...
This paper presents a new fractional-order model of a chaotic system that generates only stable equilibria. The proposed fractional-order chaotic system (FOCS) having exponential nonlinearity, is topologically inequivalent to typical chaotic systems and challenges the conventional notion of the presence of unstable equilibria to ensure the existence of chaos in fractional dynamics. This work investigates...
Ball and Plate system is a well-known benchmark to test control strategies because of its multivariable nonlinear coupled dynamics, open loop instability and under actuation. Moreover, presence of parameter uncertainty and external disturbance makes it further challenging and interesting. This calls for a robust controller which not only stabilises the ball on the plate but also makes the ball follow...
In this paper two types of sliding mode control (SMC): normal sliding mode control (normal-SMC) and Quasi sliding mode control (Quasi-SMC) are used in controlling single-link rotational base flexible manipulator for three different payloads. The dynamic equations of the system are done by using Lumped parameter method. Quasi-SMC is used for chattering elimination which is present in the case of normal-SMC...
This paper presents a comparative study of two control approaches; fuzzy proportional derivative control (PD) and sliding mode control (SMC) for a two degree of freedom (2-DOF) robot manipulator. It presents the implementation of both model based and model free based control. SimMechanics is used for modelling of the robot which requires a little knowledge regarding the dynamics of the system. A robust...
A comparative analysis on chattering based on Sliding Mode Controller (SMC) techniques for a single link flexible manipulator is presented in this paper. The proposed controller techniques include i) normal-SMC ii) Quasi-SMC iii) Asymptotic-SMC. These controllers are used in controlling the tip position as well as the tip deflection of the system. Lyapunov stability theory is used to achieve the stability...
In this paper, we propose a novel Non-Overlapping Camera Network Tracking Dataset (CamNeT) for evaluating multi-target tracking algorithms. The dataset is composed of five to eight cameras covering both indoor and outdoor scenes at a university. This dataset consists of six scenarios. Within each scenario are challenges relevant to lighting changes, complex topographies, crowded scenes, and changing...
Active distributed optimal control of PTZ (pan, tilt, zoom) camera networks can yield accurate target tracking with high resolution imagery at opportunistic time instants, even when the number of targets exceeds the number of cameras. However, one step ahead methods have limited ability to simultaneously tradeoff competing objectives, potentially sacrificing smoothness of the PTZ trajectory. In addition...
Motion and image analysis are both important for robust solutions to video search of activities; the physics-based, data-driven Hamiltonian Monte Carlo (HMC), a Markov chain Monte Carlo variant that is efficient in searching large dimensional spaces, simultaneously examines the combined motion and image space. In this paper, we generalize the data-driven HMC to no longer depend upon ad hoc Guide Hamiltonians...
This paper concentrates on the problem of modelling and recognition of complex behaviours involving multi-object interactions in video. We use motion patterns of individual objects to construct models which characterize pairs by correlating them in phase space. These models of complex interactions allow for: recognition of group activities, which occur when individual people or objects start interacting...
The Neurobiological model of motion recognition posits a Motion Energy Pathway and a Form Pathway but leaves the mechanism for Integration open. In this paper, we present a stochastic Integration methodology, based on the Hamiltonian Monte Carlo, which explores both the Motion and Form space by creating data-driven proposals in the image/form space which are then confirmed in the motion space. We...
In this paper, we develop a neurobiologically-motivated statistical method for video analysis that simultaneously searches the combined motion and form space in a concerted and efficient manner using well-known Markov chain Monte Carlo (MCMC) techniques. Specifically, we leverage upon an MCMC variant called the Hamiltonian Monte Carlo (HMC), which we extend to utilize data-based proposals rather than...
Understanding activities arising out of the interactions of a configuration of moving objects is an important problem in video understanding, with applications in surveillance and monitoring. A special situation is when the objects are small enough to be represented as points on a 2D plane. In this paper, we introduce a novel method of representing the activity by the deformations of the point configuration...
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