Motion Control for Caterpillar Vehicles Using a MIMO Robust Servo Controller

2020 ◽  
pp. 52-63
Author(s):  
Van Lanh Nguyen ◽  
Sung Won Kim ◽  
Huy Hung Nguyen ◽  
Dae Hwan Kim ◽  
Choong Hwan Lee ◽  
...  
Keyword(s):  
Motion Control ◽  
Servo Controller ◽  
Caterpillar Vehicles

Neural Network Applications for Robotic Motion Control

1990 ◽  
Vol 2 (3) ◽  
pp. 157-161
Author(s):  
Toshio Fukuda ◽  
◽  
Takanori Shibata
Keyword(s):  
Neural Network ◽  
Dynamic System ◽  
Motion Control ◽  
Force Control ◽  
Robotic Manipulators ◽  
Network Applications ◽  
The Neural Network ◽  
Robotic Motion ◽  
Servo Controller ◽  
Neural Network Applications

This paper deals with neural network applications for the robotic motion control. The neural network can be employed for both the long term ""learning"" of the control process and the short term ""adaptation"" of the dynamic process. In this paper, we demonstrate some dynamic controls of robotic manipulators using the ""Neural Servo Controller"" which is applicable to the position and force control of robotic manipulators. The ""Neural Servo Controller"" is based on the neural network which here consists of two hidden layers and input/output layers. The controller can adjust the neural network output to the robot in the forward manner to cooperate with the feedback loop, depending on unknown characteristics of handling objects. In particular, the proposed neural network has time delay elements in itself, so that the neural network can learn the dynamics of the system. Simulations are carried out for position and force control of a two dimensional robotic manipulator. Moreover, we propose a ""Fuzzy Turbo"" so that the neural network can learn the dynamic system quickly. The results show the applicability and adaptability of the proposed ""Neural Servo Controller"" to the nonlinear and dynamic system, and the ability of the proposed ""Fuzzy Turbo"" on the adaptive process.

Vibration and Motion Control of Flexible Structures by Hybrid Dynamic Absorber(Influence of Vibration System with Nonlinear Element)

1994 ◽  
Vol 6 (3) ◽  
pp. 230-236
Author(s):  
Shinji Mitsuta ◽  
◽  
Kazuto Seto ◽  
Hiroyuki Ito ◽  
Akio Nagamatsu ◽  
...  
Keyword(s):  
Vibration Control ◽  
Motion Control ◽  
Control Method ◽  
Flexible Structures ◽  
Sine Wave ◽  
Flexible Structure ◽  
Control Force ◽  
Control Effect ◽  
Dynamic Absorber ◽  
Servo Controller

Recently, the necessity for making machines weighing less and operating at high speeds has increased. This paper is concerned with vibration and motion control by a control system which combines a servo controller and a hybrid dynamic absorber. In our method, vibration control and motion control are designed independently. First, the dynamics of a tower structure and a servo motor are modeled. Then, it is shown experimentally that although vibration control by the servo controller alone causes instability due to nonlinear elements such as friction or rattle, the hybrid dynamic absorber does not easily cause this sort of instability. On the comparison of vibration control effect and control force, the hybrid dynamic absorber requires less force. Finally, to know the effect of the new method, we evaluated the motions (triangular wave and sine wave) of the flexible structure. The effectiveness of this vibration and motion control method for the flexible structure was demonstrated by simulations and experiments.

scholarly journals Intelligent Parameter Identification for Robot Servo Controller Based on Improved Integration Method

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4177
Author(s):  
Ye Li ◽  
Dazhi Wang ◽  
Shuai Zhou ◽  
Xian Wang
Keyword(s):  
Parameter Identification ◽  
Motion Control ◽  
Integration Method ◽  
Classical Method ◽  
Search Algorithm ◽  
Probabilistic Neural Network ◽  
Gravitational Search Algorithm ◽  
Optimization Approach ◽  
Parameter Mismatch ◽  
Servo Controller

With the rise of smart robots in the field of industrial automation, the motion control theory of the robot servo controller has become a research hotspot. The parameter mismatch of the controller will reduce the efficiency of the equipment and damage the equipment in serious cases. Compared to other parameters of servo controllers, the moment of inertia and friction viscous coefficient have a significant effect on the dynamic performance in motion control; furthermore, accurate real-time identification is essential for servo controller design. An improved integration method is proposed that increases the sampling period by redefining the update condition in this paper; it then expands the applied range of the classical method that is more suitable for the working characteristics of a robot servo controller and reducesthe speed quantization error generated by the encoder. Then, an optimization approach using the incremental probabilistic neural network with improved Gravitational Search Algorithm (IGSA-IPNN) is proposed to filter the speed error by a nonlinear process and provide more precise input for parameter identification. The identified inertia and friction coefficient areused for the PI parameter self-tuning of the speed loop. The experiments prove that the validity of the proposed method and, compared to the classical method, it is more accurate, stable and suitable for the robot servo controller.

scholarly journals ModelSim/Simulink Cosimulation and FPGA Realization of a Multiaxis Motion Controller

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Ying-Shieh Kung ◽  
Jin-Mu Lin ◽  
Yu-Jen Chen ◽  
Hsin-Hung Chou
Keyword(s):  
Motion Control ◽  
Trajectory Planning ◽  
Motion Trajectory ◽  
Motion Controller ◽  
Motion Platform ◽  
Nios Ii ◽  
Chip Technology ◽  
Current Controller ◽  
Field Programmable ◽  
Servo Controller

This paper is to implement a multiaxis servo controller and a motion trajectory planning within one chip. At first, SoPC (system on a programmable chip) technology which is composed of an Altera FPGA (field programmable gate arrays) chip and an embedded soft-core Nios II processor is taken as the development of a multiaxis motion control IC. The multiaxis motion control IC has two modules. The first module is Nios II processor which realizes the motion trajectory planning by software. It includes the step, circular, window, star, and helical motion trajectory. The second module presents a function of the multiaxis position/speed/current controller IP (intellectual property) by hardware. And VHDL (VHSIC Hardware Description Language) is applied to describe the multiaxis servo controller behavior. Before the FPGA realization, a cosimulation work by ModelSim/Simulink is applied to test the VHDL code. Then, this IP combined by Nios II processor will be downloaded to FPGA. Therefore, a fully digital multiaxis motion controller can be realized by a single FPGA chip. Finally, to verify the effectiveness and correctness of the proposed multiaxis motion control IP, a three-axis motion platform (XYZtable) is constructed and some experimental results are presented.

Virtual Hand Representation and Motion Control for Smart Wheelchair with Touch-Based Extended Hand Projection

2019 ◽  
Vol 139 (5) ◽  
pp. 662-669
Author(s):  
Yuki Asai ◽  
Ryuichi Enomoto ◽  
Yuta Ueda ◽  
Daisuke Iwai ◽  
Kosuke Sato
Keyword(s):  
Motion Control ◽  
Virtual Hand ◽  
Smart Wheelchair

Motion Control of Industrial Robot by Considering Vibration Suppression and Fast Path Tracking

2010 ◽  
Vol 130 (3) ◽  
pp. 375-384
Author(s):  
Satoru Kumagai ◽  
Toshimasa Miyazaki ◽  
Kiyoshi Ohishi
Keyword(s):  
Motion Control ◽  
Vibration Suppression ◽  
Industrial Robot ◽  
Path Tracking

Development of Semicircular Tubular Core-less Linear Motor and Its Motion Control

2015 ◽  
Vol 135 (3) ◽  
pp. 246-257 ◽  
Author(s):  
Mototsugu Omura ◽  
Tomoyuki Shimono ◽  
Yasutaka Fujimoto
Keyword(s):  
Motion Control ◽  
Linear Motor

The Design of Optimal Lateral Motion Control of an UAV Using the Linear-Quadratic Optimization Method in the Complex Domain

2020 ◽  
Vol 13 (6) ◽  
pp. 217
Author(s):  
Vadim Kramar ◽  
Vasiliy Alchakov ◽  
Aleksey Kabanov ◽  
Sergey Dudnikov ◽  
Aleksandr Dmitriev
Keyword(s):  
Motion Control ◽  
Optimization Method ◽  
Quadratic Optimization ◽  
Complex Domain ◽  
Lateral Motion ◽  
Linear Quadratic
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