scholarly journals Gain-Scheduled H∞ for Vehicle High-Level Motion Control

2018 ◽  
Author(s):  
Moad Kissai ◽  
Bruno Monsuez ◽  
Adriana Tapus ◽  
Xavier Mouton ◽  
Didier Martinez
Keyword(s):  
Motion Control ◽  
High Level ◽  
Gain Scheduled

Design of Five Axis Cooperation Machine Based on Motion Control Board

2013 ◽  
Vol 300-301 ◽  
pp. 1463-1466
Author(s):  
Shang Wei Yang ◽  
Shu Kun Cao ◽  
Jia Jia
Keyword(s):  
Motion Control ◽  
Visual Basic ◽  
Cnc Machine ◽  
Cnc System ◽  
Control Card ◽  
Open Cnc ◽  
Motion Control Card ◽  
Open Cnc System ◽  
High Level ◽  
Five Axis

Abstract. PC-based open CNC system can fully take advantage of the computer's hardware and software resources, which can use a common high-level language: Visual C++ or Visual Basic to program. User can mix and use the standardized peripherals, application software flexibly, we use the self-developed five-axis CNC machine is experimental platform, which can develop open CNC system based on PC and motion control card. Using of five-axis machine motion control design based on "PC + motion control card" on Visual C++ platform.

1311 Motion control of a motorcycle using gain-scheduled control

2009 ◽  
Vol 2009.47 (0) ◽  
pp. 447-448
Author(s):  
Takayuki FUNO ◽  
Fumitake FUJII ◽  
Kenzo WADA
Keyword(s):  
Motion Control ◽  
Gain Scheduled

scholarly journals Gain Scheduled Motion Control of an Overhead Traveling Crane

2000 ◽  
Vol 33 (13) ◽  
pp. 573-578 ◽  
Author(s):  
H. Aschemann ◽  
S. Lahres ◽  
O. Sawodny ◽  
E.P. Hofer
Keyword(s):  
Motion Control ◽  
Gain Scheduled

Hierarchical control of soft manipulators towards unstructured interactions

2021 ◽  
pp. 027836492097936
Author(s):  
Hao Jiang ◽  
Zhanchi Wang ◽  
Yusong Jin ◽  
Xiaotong Chen ◽  
Peijin Li ◽  
...  
Keyword(s):  
Control System ◽  
Motion Control ◽  
Control Method ◽  
Hierarchical Control ◽  
Training Data ◽  
Text Learning ◽  
Low Level ◽  
Feedback Control Method ◽  
New Perspective ◽  
High Level

Performing daily interaction tasks such as opening doors and pulling drawers in unstructured environments is a challenging problem for robots. The emergence of soft-bodied robots brings a new perspective to solving this problem. In this paper, inspired by humans performing interaction tasks through simple behaviors, we propose a hierarchical control system for soft arms, in which the low-level controller achieves motion control of the arm tip, the high-level controller controls the behaviors of the arm based on the low-level controller, and the top-level planner chooses what behaviors should be taken according to tasks. To realize the motion control of the soft arm in interacting with environments, we propose two control methods. The first is a feedback control method based on a simplified Jacobian model utilizing the motion laws of the soft arm that are not affected by environments during interaction. The second is a control method based on [Formula: see text]-learning, in which we present a novel method to increase training data by setting virtual goals. We implement the hierarchical control system on a platform with the Honeycomb Pneumatic Networks Arm (HPN Arm) and validate the effectiveness of this system on a series of typical daily interaction tasks, which demonstrates this proposed hierarchical control system could render the soft arms to perform interaction tasks as simply as humans, without force sensors or accurate models of the environments. This work provides a new direction for the application of soft-bodied arms and offers a new perspective for the physical interactions between robots and environments.

A novel hybrid closed-loop control approach for dexterous prosthetic hand based on myoelectric control and electrical stimulation

2018 ◽  
Vol 45 (4) ◽  
pp. 526-538 ◽  
Author(s):  
Li Jiang ◽  
Qi Huang ◽  
Dapeng Yang ◽  
Shaowei Fan ◽  
Hong Liu
Keyword(s):  
Motion Control ◽  
Sensory Feedback ◽  
Closed Loop ◽  
Control Method ◽  
Human Motion ◽  
Prosthetic Hand ◽  
Closed Loop Control ◽  
Content Type ◽  
Loop Control ◽  
High Level

Purpose The purpose of this study is to present a novel hybrid closed-loop control method together with its performance validation for the dexterous prosthetic hand. Design/methodology/approach The hybrid closed-loop control is composed of a high-level closed-loop control with the user in the closed loop and a low-level closed-loop control for the direct robot motion control. The authors construct the high-level control loop by using electromyography (EMG)-based human motion intent decoding and electrical stimulation (ES)-based sensory feedback. The human motion intent is decoded by a finite state machine, which can achieve both the patterned motion control and the proportional force control. The sensory feedback is in the form of transcutaneous electrical nerve stimulation (TENS) with spatial-frequency modulation. To suppress the TENS interfering noise, the authors propose biphasic TENS to concentrate the stimulation current and the variable step-size least mean square adaptive filter to cancel the noise. Eight subjects participated in the validation experiments, including pattern selection and egg grasping tasks, to investigate the feasibility of the hybrid closed-loop control in clinical use. Findings The proposed noise cancellation method largely reduces the ES noise artifacts in the EMG electrodes by 18.5 dB on average. Compared with the open-loop control, the proposed hybrid closed-loop control method significantly improves both the pattern selection efficiency and the egg grasping success rate, both in blind operating scenarios (improved by 1.86 s, p < 0.001, and 63.7 per cent, p < 0.001) or in common operating scenarios (improved by 0.49 s, p = 0.008, and 41.3 per cent, p < 0.001). Practical implications The proposed hybrid closed-loop control method can be implemented on a prosthetic hand to improve the operation efficiency and accuracy for fragile objects such as eggs. Originality/value The primary contribution is the proposal of the hybrid closed-loop control, the spatial-frequency modulation method for the sensory feedback and the noise cancellation method for the integrating of the myoelectric control and the ES-based sensory feedback.

scholarly journals Research on Coordinated Robotic Motion Control Based on Fuzzy Decoupling Method in Fluidic Environments

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Wei Zhang ◽  
Haitian Chen ◽  
Tao Chen ◽  
Zheping Yan ◽  
Hongliang Ren
Keyword(s):  
Motion Control ◽  
Control Method ◽  
Fuzzy Theory ◽  
Autonomous Underwater Vehicles ◽  
Strong Nonlinearity ◽  
Water Tank ◽  
Level Control ◽  
Decoupling Method ◽  
Heading Control ◽  
High Level

The underwater recovery of autonomous underwater vehicles (AUV) is a process of 6-DOF motion control, which is related to characteristics with strong nonlinearity and coupling. In the recovery mission, the vehicle requires high level control accuracy. Considering an AUV called BSAV, this paper established a kinetic model to describe the motion of AUV in the horizontal plane, which consisted of nonlinear equations. On the basis of this model, the main coupling variables were analyzed during recovery. Aiming at the strong coupling problem between the heading control and sway motion, we designed a decoupling compensator based on the fuzzy theory and the decoupling theory. We analyzed to the rules of fuzzy compensation, the input and output membership functions of fuzzy compensator, through compose operation and clear operation of fuzzy reasoning, and obtained decoupling compensation quantity. Simulation results show that the fuzzy decoupling controller effectively reduces the overshoot of the system, and improves the control precision. Through the water tank experiments and analysis of experimental data, the effectiveness and feasibility of AUV recovery movement coordinated control based on fuzzy decoupling method are validated successful, and show that the fuzzy decoupling control method has a high practical value in the recovery mission.

Automated driving, technical approach with motion control architecture

2015 ◽  
Vol 63 (3) ◽  
Author(s):  
Thomas Raste ◽  
Stefan Lüke ◽  
Alfred Eckert
Keyword(s):  
Motion Control ◽  
State Feedback ◽  
State Feedback Control ◽  
Automated Driving ◽  
Property A ◽  
Technical Approach ◽  
Personal Transportation ◽  
Optimal State Feedback ◽  
Transportation Motion ◽  
High Level

AbstractAutomated Driving is the key technology for greater safety, comfort and efficiency in personal transportation. Motion Control ensures that the high-level behavior planning is carried out properly even in case of failures and disturbances. Based on the flatness property a feedforward trajectory control is obtained to ensure lateral motion along prescribed trajectories. An optimal state feedback control reduces the effects of disturbances like side wind or road bank to a minimum.

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