scholarly journals Proposed Fuzzy Real-Time HaPticS Protocol Carrying Haptic Data and Multisensory Streams

Author(s):  
Sotirios Kontogiannis ◽  
George Kokkonis

Sensory and haptic data transfers to critical real-time applications over the Internet require better than best effort transport, strict timely and reliable ordered deliveries. Multi-sensory applications usually include video and audio streams with real-time control and sensory data, which aggravate and compress within real-time flows. Such real-time are vulnerable to synchronization to synchronization problems, if combined with poor Internet links. Apart from the use of differentiated QoS and MPLS services, several haptic transport protocols have been proposed to confront such issues, focusing on minimizing flows rate disruption while maintaining a steady transmission rate at the sender. Nevertheless, these protocols fail to cope with network variations and queuing delays posed by the Internet routers. This paper proposes a new haptic protocol that tries to alleviate such inadequacies using three different metrics: mean frame delay, jitter and frame loss calculated at the receiver end and propagated to the sender. In order to dynamically adjust flow rate in a fuzzy controlled manners, the proposed protocol includes a fuzzy controller to its protocol structure. The proposed FRTPS protocol (Fuzzy Real-Time haPticS protocol), utilizes crisp inputs into a fuzzification process followed by fuzzy control rules in order to calculate a crisp level output service class, denoted as Service Rate Level (SRL). The experimental results of FRTPS over RTP show that FRTPS outperforms RTP in cases of congestion incidents, out of order deliveries and goodput.

2014 ◽  
Vol 1056 ◽  
pp. 162-165
Author(s):  
Zheng Cai Yang ◽  
Bao Hua Wang

A Two-Wheeled Self-Balancing Electric vehicle control system was developed base on the system design, hardware development and software strategies.The paper designed the posture acquisition module by gyroscopes and accelerometer sensors, and improved the control ccuracy using Calman filtering algorithm. Based on the system structure model, construction of Two-Wheeled Self-Balancing Electric vehicle dynamic equations by using the analysis method of Newtonian echanics was developed.A fuzzy PD controller was designed,the displacement and velocity as the input variable is controlled by fuzzy controller, and the tilt angle and angular velocity is controlled by PD controller. Finally, the platform of real-time control system was established for parameters adjustment and real-time control.Experiments show that the system has good robustness,high real-time response and has a higher market value.


2019 ◽  
Vol 52 (5-6) ◽  
pp. 418-431 ◽  
Author(s):  
Liu Jun ◽  
Xie Shouyong ◽  
Chen Chong ◽  
Xie Dan ◽  
Yang Mingjin

Fuzzy control, an intelligent control method, is generally employed to deal with complex nonlinear controlled objects that cannot be expressed by accurate mathematical model. Memristor, whose unique advantages are automatic successive memory and nonvolatility, brought new opportunity for solving the key question of fuzzy control. With the design idea of software harden, this paper first constructed membership function in the fuzzy controller based on the unique feature of crossbar array of the spintronic memristor and elaborated the whole construction process. After that, this paper simulated the construction process with MATLAB simulation software, verifying its reasonability and feasibility. Furthermore, a typical fuzzy control water tank system was chosen to explore and discuss the flexibility of spintronic memristor crossbar array in the real-time control system, and the proposed control strategy and the typical fuzzy control strategy were compared. The results revealed that the proposed control strategy was able to attain the effectiveness of the typical fuzzy control system in the real-time control system. This sets light to future research on the implementation of memristor crossbar array in the real-time control system and also promotes the application of fuzzy controller design idea. The problems needed to be solved when implementing memristor crossbar array in the real-time control system were discussed in the final section.


Author(s):  
Noel S. Gunay ◽  
◽  
Elmer P. Dadios

Any real-time control application run by a digital computer (or any sequential machine) demands a very fast processor in order to make the time-lag from data sensing to issuance of a control action closest to zero. In some instances, the algorithm used requires a relatively large primary memory which is crucial especially when implemented in a microcontroller. This paper presents a novel implementation of a multi-output fuzzy controller (which is known in this paper as MultiOFuz), which utilizes lesser memory and executes faster than a type of an existing multiple single-output fuzzy logic controllers. The design and implementation of the developed controller employed the object-oriented approach with program level code optimizations. MultiOFuz is a reusable software component and the simplicity of how to interface this to control applications is presented. Comparative analyses of algorithms, memory usage and simulations are presented to support our claim of increased efficiency in both execution time and storage use. Future directions of MultiOFuz are also discussed.


Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1328 ◽  
Author(s):  
Hsu-Chih Huang ◽  
Chin-Wang Tao ◽  
Chen-Chia Chuang ◽  
Jing-Jun Xu

This study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is proposed, called CS-fuzzy. The CS’s computational intelligence was employed to optimize the structure of fuzzy systems. The proposed CS-fuzzy computing scheme was then applied to design an optimal real-time control method for omni-Mecanum-wheeled autonomous vehicles with four wheels. Both vehicle model and CS-fuzzy optimization are considered to achieve intelligent tracking control of Mecanum mobile vehicles. The control parameters of the Mecanum fuzzy controller are online-adjusted to provide real-time capability. This methodology outperforms the traditional offline-tuned controllers without computational intelligences in terms of real-time control, performance, intelligent control and evolutionary optimization. The mechatronic design of the experimental CS-fuzzy based autonomous mobile vehicle was developed using FPGA realization. Some experimental results and comparative analysis are discussed to examine the effectiveness, performance, and merit of the proposed methods against other existing approaches.


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