Flocking Behavior of Boids Driven by Hyperchaotic MACM System

This paper presents a new design for formation control on a group of autonomous humanoid robots with obstacle and collision avoidance ability that inspired by human walking behavior in a pedestrian crowd. This human walking behavior model is known as Social Force Model (SFM) and has been widely used to predict individual movement in a crowd in many variety of situation. We combine consensus algorithm with virtual structure approach for formation control and SFM for obstacle and collision avoidance. In this research, we induced some factors in SFM into consensus equation and then implemented into a group of humanoid robots. The aim of the integration is to create a group of robots that are capable of carrying out its collective tasks while still able to maintain its safety. The use of perception effect, distinct obstacle and collision avoidance function on the algorithm will differentiate algorithm with the others. The attractive feature of this new design is the various behaviors of robots to go back to their initial formation after they avoid obstacles. In the case of robot is trapped in a crowded situation (singularity condition), robot will still trying to look a new position, until it find a condition that allow him to move forward. We verify the proposed algorithm by some simulations and experiments.

Based on the chaos anti-control theory, a new four-dimensional autonomous hyperchaotic system is formulated by adding a periodic driving signal rsin(cos(¿t)) to the second equation of the three-dimensional autonomous Chen chaotic system in this paper. The basic dynamical behavior of the new hyperchaotic system was not only demonstrated by numerical simulation, but also verified with Lyapunov exponents and bifurcation analysis. The new hyperchaotic system can be periodic, quasi-periodic, chaotic and hyperchaotic with the variation of the parameter ¿. It also has broad and stable hyperchaotic region which makes the new hyperchaotic system has a good application prospect.

The paper presents a new four-dimensional autonomous hyper-chaotic system by introducing a state variable into the three-dimensional autonomous chaotic system based on studying and analyzing some hyper-chaos. Compared with other hyper-chaotic systems，the bigger positive Lyapunov exponent of the new system is bigger, and the range of hyper-chaos is also wider when the parameter varies. Numerical simulations and bifurcation analysis are done in this paper, and an analog electronic circuit is designed to verify the new system. The experiment results show that various attractors of the hyper-chaotic circuit, including periodic attractor, quasi-periodic attractor，chaotic attractor，hyper-chaotic attractor，are well agree with the simulation results.

In this paper, some basic dynamical properties of a four-dimensional autonomous hyperchaotic system are investigated by means of Poincaré mapping, Lyapunov exponents and bifurcation diagram. The dynamical behaviours of this new hyperchaotic system are proved not only by performing numerical simulation and brief theoretical analysis but also by conducting an electronic circuit experiment. An efficient approaching is developed for global asymptotic stabilization of this four-dimensional hyperchaotic system. Based on the method of inverse optimal control for nonlinear systems, a linear state feedback is electronically implemented. It is remarkably simple as compared with other chaos control ways, like nonlinear state feedback.

This paper considers a rendezvous problem, where a group of wheeled mobile robots with sensing and power constraints is tasked to meet at a common destination. Each robot is modeled in the wheel kinematic level, which is governed by the wheel actuation power constraints. The group of robots is of a leader-follower network structure, where only the leader robot is aware of the desired destination and the follower robots are driven by the leader to the common destination via local sensing of neighboring robots. To ensure the availability of inter-robot communication, the motion of robots is constrained to preserve network connectivity, enabling leader-based guidance via connected paths. In addition, the motion of robots is further constrained to avoid collisions with other robots. To achieve these objectives, a guidance function based decentralized controller is developed to control the wheel velocities of each robot, which ensures global convergence to the destination while guaranteeing the network connectivity, collision avoidance, and not violating its sensing and actuator power capabilities. The simulation results demonstrate the effectiveness of the developed controller.

Controlling chaotic and hyperchaotic systems via energy regulation

In this paper, a four-dimensional hyperchaotic system is constructed by adding a state feedback controller into a chaotic system. Numerical simulations and theoretical analysis show that this four-dimensional system will take on periodic,complex periodic, quasi-periodic chaotic hyperchaotic dynamical behaviours as parameters vary. Moreover, an electronic circuit diagram is designed for demonstrating the existence of the hyperchaos. Finally, an adaptive tracking controller is proposed to acquire adaptive tracking control for this hyperchaotic system.

A new hyperchaotic system and its generalized synchronization

In this paper autonomous formation control for Unmanned Aerial Vehicles (UAVs) has been discussed and a real time solution has been put forward by benefiting General Purpose Graphical Processing Units (GPGPU) accelerated potential field approach while ensuring obstacle and collision avoidance in unknown environment by using real-time sensors. GPGPU accelerated real time formation control for UAVs was designed and the basic model of the approach has been explained in our previous work (Cetin and Yilmaz 2014). As the deficiencies of the previous approach, autonomous real time collision and coordinated obstacle avoidance features in unknown environments are also handled while maintaining formation flight conditions in this work. With these features, improved autonomous formation control approach is discussed as a real time solution. The computation is performed by using Graphical Processing Units (GPUs) as parallel computation architectures by benefiting from Single Instruction Multiple Data (SIMD) type parallel algorithms. Classic binary map conversation, connected component labeling and minimum bounding box algorithms which are commonly used for image processing applications, has been evaluated for real time obstacle detection and avoidance features by developing GPGPU suitable parallel algorithms. Real-time solution has been developed by integrated these parallel algorithms with parallel Artificial Potential Field (APF) computation algorithm. Simulation results are proved that this novel autonomous improved formation control approach is successful and it would be used in real time applications like UAV formation flight missions.

A four-dimensional autonomous hyperchaotic system is constructed, and the basic characteristics of the system are studied by the power spectrum, Poincaré maps, 0–1 test and Lyapunov exponents. The system has rich dynamical behaviors, such as bursting oscillations, offset boosting, transient chaos, intermittent chaos and coexistence of attractors. In addition, by studying the coexisting phenomenon and spectral entropy (SE) complexity of different initial values, an initial value that is more suitable for chaotic secure communication is selected. The circuit simulation of the system using Multisim and then the actual hardware implementation of the system by Field Programmable Gate Array (FPGA), these prove the practical existence of the system. Finally, combining the methods of backstepping control, multi-switching synchronization and synchronization of different systems, a set of controllers are proposed which can realize the backstepping multi-switching synchronization of this system with a memristive chaotic system.

A new four-dimensional continuous-time autonomous hyperchaotic system is proposed in this paper，which is built by adding a nonlinear controller to a three-dimensional continuous-time autonomous chaotic system. The hyperchaotic system is analyzed by studying the Lyapunov exponent spectrum and bifurcation diagram. The system will take on periodic and complex periodic，chaotic and hyperchaotic behaviors with change of the parameter. Also，an electronic circuit is designed and realized，the experimental results verify the conclusions.

Collision avoidance is very important problem in the domain of multi-robot interaction. In this paper we propose a new approach of collision avoidance in the context of the optimal control system synthesis problem definition with minimal information available. It is assumed that robots have a certain scope within which they can interact with static and dynamic phase constraints. A group of robots is considered to be homogeneous, and control system unit for reaching terminal states already available to robots. The control system which is responsible for collision avoidance is only activated when the nearest neighbor is located in the scope of the considered robot. The first important feature of this work is the fact that the collision avoidance between two robots is reciprocal with joint control system, without assigning priorities. Another key feature of this work is the complete absence of information about the environment and the current state of other robots at given time. Robots only share information with nearest neighbors if they locate in the scope of each other. We also present a computational experiment with mobile robots as control objects. A multilayer perceptron was used to approximate the control function. Weights of the perceptron were optimized in unsupervised paradigm by an algorithm belonging to the evolutionary strategies class. At the beginning of each epoch we generate a sample of collision scenarios for optimization, while the quality criterion of the achieved weights at the end of epoch is evaluated on a fixed test sample. Experimental results demonstrate strong ability of the optimized multilayer perceptron to map the relative state of two mobile robots to controls in order to avoid collisions.

This paper reports a new four-dimensional hyperchaotic system obtained by adding a controller to a three-dimensional autonomous chaotic system. The new system has two parameters and each equation of the system has one quadratic cross-product term. Some basic properties of the new system are analysed. The different dynamic behaviours of the new system are studied when the system parameter a or b is varied. The system is hyperchaotic in several different regions of the parameter b. Especially, the two positive Lyapunov exponents are both larger and the hyperchaotic region is also larger when this system is hyperchaotic in the case of varying a. The hyperchaotic system is analysed by Lyapunov-exponents spectrum, bifurcation diagrams and Poincaré sections.

A new four-dimensional hyperchaotic system with three quadratic nonlinearities is proposed in this paper. The dynamical properties of the new hyperchaotic system are explored in terms of phase portraits, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. Also, a detailed dynamical analysis of the new hyperchaotic system has been carried out with bifurcation diagram and Lyapunov exponents. As an engineering application, an electronic circuit realization of the new hyperchaotic system is designed via MultiSIM to confirm the feasibility of the theoretical hyperchaotic model.

This paper presents a distributed consensus formation control with collision and obstacle avoidance using fuzzy wavelet neural networks (FWNNs) for a group of networked mobile Mecanum-wheeled omnidirectional robots (MWORs) with uncertainties. The dynamic behavior of each uncertain MWOR is modeled by a reduced three-input–three-output second-order state equation with uncertainties, and the multi-MWOR system is modeled by graph theory. Using the Lyapunov stability theory and online learning the system uncertainties via FWNNs, an adaptive and distributed consensus backstepping control approach is presented to carry out formation control in the presence of uncertainties. Collision and obstacle-avoidance methods are provided to avoid any collisions among MWORs and their working environments. Five simulations are conducted to show the effectiveness and merit of the proposed method .