Chaos Control in Bonhoeffer-van der Pol System Using Fuzzy Estimation

Volume 1 ◽  
2004 ◽  
Author(s):  
Aria Alasty ◽  
Hassan Salarieh

This paper illustrates the control of chaos using a fuzzy estimating system based on batch training and recursive least square methods for a continuous time dynamic system. The fuzzy estimator system is trained on both Ott-Geobogi-Yorke (OGY) control algorithm and Pyragas’s delayed feedback control algorithm. The system, considered for this study, is a Bonhoeffer-van der Pol (BVP) oscillator. It is found that the implemented fuzzy control system constructed on OGY algorithm results in smaller control transient response than that of the OGY control algorithm itself. The transient response of Pyragas fuzzy control does not show a significant improvement in compare to the Pyragas control itself. In general the proposed control techniques show very effective low cost energy behavior in chaos control in compare to conventional nonlinear control methods.

Author(s):  
M. H. Toufighi ◽  
S. H. Sadati ◽  
F. Najafi ◽  
A. A. Jafari

The dynamics of hydraulic systems involves slow and fast modes. These modes are associated with the mechanical components and those involving fluid flow, respectively. As such, controllers for electro-hydraulic servo systems (EHSS) can be designed and analyzed using singular perturbation theory. In this paper, a singular perturbation control (SPC) algorithm is proposed and investigated on a rotary EHSS modeled based on a two-time-scale behavior of the system. For modeling, the components of the hydraulic system, specifically the nonlinear model of the orifice in servo valve, are modeled. A mathematical modeling and nonlinear control analysis that validated by experiment is presented. The controlled system with the SPC algorithm tracks a fairly smooth trajectory with very small error. As well, the control algorithm is successfully verified by experiment as the main contribution of the paper. In addition, this is robust to variations in the hydraulic fluid bulk modulus such that only its nominal value is sufficient. Furthermore, the proposed control design will not require derivatives of the control pressures and any output acceleration feedback. Hence, it can be implemented easier in the real system setup. The controller design approach addresses the nonlinearities of the rotary EHSS. The parameters of the real system model are experimentally identified using the continuous recursive least square method.


Author(s):  
Xubin Song ◽  
Mehdi Ahmadian ◽  
Steve Southward

In general, a vehicle suspension system can be characterized as a nonlinear dynamic system that is subjected to unknown vibration sources, dependent on road roughness and vehicle speed. In this paper, we will present a nonlinear-model-based adaptive semiactive control algorithm developed for nonlinear systems exposed to broadband non-stationary random vibration sources that are assumed to be unknown or not measurable. If there exist unknown and/or varying parameters of the dynamic system such as mass and stiffness, then the adaptive algorithm can include a recursive least square (RLS) method for on-line system identification. Since the adaptive algorithm is developed for semiactive systems, stability is guaranteed based on the fact that the system is energy conservative. The convergence of the adaptive system, however is not guaranteed, and is investigated through a numerical approach for a specific case. The simulation results for a magneto-rheological seat suspension system with the suggested adaptive control are presented. The results are compared with low-damping and high-damping cases, as well æ other configurations of skyhook control, in order to show the extent of the procurement that can be expected with the suggested adaptive skyhook control provides a better broadbandk performance for the suspension, as compared to the other damping configurations that are included here.


Author(s):  
Imene Mahmoud ◽  
Ines Chihi ◽  
Afef Abedlkrim ◽  
Mohamed Benrejeb

<span lang="EN-US">Handwriting movement is one of the most complex activities of human motions. It’s a blend of kinesthetic, cognitive, perceptual and motor components. The study of this biological process shows that bell-shaped velocity profiles are generally observed in the handwriting motion. In this paper, an identification technique, based on Recursive Least Square algorithm (RLS), is proposed to identify the pen-tip movement in human handwriting process, by using input and output data which present EMG signals and velocities according to x and y coordinates.  Using the estimated coordinates that have resulted from the velocity model; we propose a novel algorithm to generate handwritten graphic traces, which is inspired from the idea of tracing circles by Bresenham bi-axis control algorithm. The effectiveness of this approach should be observed on predicting cursive Arabic letters and Arabic word written on (</span><em><span lang="EN-US">x,y</span></em><span lang="EN-US">) plane, these shapes constituting a recorded experimental basis.</span>


Author(s):  
Longke Wang ◽  
Wayne J. Book ◽  
James D. Huggins

This paper proposes a robot control approach using a discrete recursive least square algorithm. The scheme shows robustness when the system suffers from measurement noise and has a fast parameter convergence rate. The control algorithm is computationally efficient and numerically stable. Guaranteed trajectory tracking can be achieved by simple parameter design if disturbances are bounded.


Author(s):  
Baoyu Shi ◽  
Hongtao Wu

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.


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