Obfuscated Hardware Accelerators for Image Processing Filters—Application Specific and Functionally Reconfigurable Processors

Sengupta, Anirban; Rathor, Mahendra

doi:10.1109/tce.2020.3027760

Cited by 5 publications

(1 citation statement)

References 32 publications

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“…In the common sliding mode variable structure controller, the third-order derivation of the angle control variable is required, which makes the control law derivation process cumbersome and complicated. The combination of sliding mode variable structure control design and other control methods is the direction of further research on sliding mode variable structure controller, and this combination often further increases the tediousness and complexity of the control law [ 17 , 18 ]. In recent years, due to the ability of artificial neural network to approximate any nonlinear mapping through learning, most literature use neural network to approximate the entire robot dynamics model, and the other type uses neural network to compensate for the uncertainty of the model [ 19 ].…”

Section: Related Workmentioning

confidence: 99%

Design of Multimodal Neural Network Control System for Mechanically Driven Reconfigurable Robot

Zhang

Gongyong

2022

Computational Intelligence and Neuroscience

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According to the characteristics and division rules of the modules, this paper divides the rotary module, the swing module, and the mobile module. In order to realize the rapid identification of modules, according to the basic principles of module design, the above modules are put into the module library established by Access. According to the modular modeling method, kinematic models are established, respectively. In order to automatically establish the kinematic model of the robot, a unified expression of modules is established. According to the unified expression of the modules, the kinematics of the reconfigurable robot is analyzed. According to the characteristics of the configuration plane, the configuration plane is divided, and the expression form of the position and attitude of the configuration plane is given. Combined with the principle of neural network and multimodal information fusion, a multimodal information fusion model based on long- and short-term memory neural network is established. Aiming at the control problem of mechanically driven reconfigurable robots, a specific long- and short-term memory neural network model is designed, and the long- and short-term memory neural network algorithm is applied to the robot control problem based on multimodal information fusion. The design of the controller and driver of each joint is the basis of the distributed control system. This paper discusses the hardware design of the joint controller and driver and the realization of the position control system and discusses the method of realizing distributed control based on the Modbus protocol of RS485 communication. Through the comprehensive experiment of the configuration, the point control and the continuous path control are carried out to verify the correctness of the theoretical analysis of the system and the reliability of the system hardware and software operation.

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Section: Related Workmentioning

confidence: 99%