A learning-based flexible autonomous motion control method for UAV in dynamic unknown environments

In this article, we propose an efficient intelligent decision method for a bionic motion unmanned system to simulate the formation change during the hunting process of the wolves. Path planning is a burning research focus for the unmanned system to realize the formation change, and some traditional techniques are designed to solve it. The intelligent decision based on evolutionary algorithms is one of the famous path planning approaches. However, time consumption remains to be a problem in the intelligent decisions of the unmanned system. To solve the time-consuming problem, we simplify the multi-objective optimization as the single-objective optimization, which was regarded as a multiple traveling salesman problem in the traditional methods. Besides, we present the improved genetic algorithm instead of evolutionary algorithms to solve the intelligent decision problem. As the unmanned system’s intelligent decision is solved, the bionic motion control, especially collision avoidance when the system moves, should be guaranteed. Accordingly, we project a novel unmanned system bionic motion control of complex nonlinear dynamics. The control method can effectively avoid collision in the process of system motion. Simulation results show that the proposed simplification, improved genetic algorithm, and bionic motion control method are stable and effective.

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Chaotic motion control of a vibro-impact system based on data-driven control method

Journal of Vibration and Control ◽

10.1177/10775463211043320 ◽

2021 ◽

pp. 107754632110433

Author(s):

Xiao-juan Wei ◽

Ning-zhou Li ◽

Wang-cai Ding

Keyword(s):

Motion Control ◽

Data Model ◽

Chaotic Motion ◽

Control Method ◽

Data Driven ◽

Damping Coefficient ◽

Input Output ◽

Output Data ◽

Controlled System ◽

Impact System

For the chaotic motion control of a vibro-impact system with clearance, the parameter feedback chaos control strategy based on the data-driven control method is presented in this article. The pseudo-partial-derivative is estimated on-line by using the input/output data of the controlled system so that the compact form dynamic linearization (CFDL) data model of the controlled system can be established. And then, the chaos controller is designed based on the CFDL data model of the controlled system. And the distance between two adjacent points on the Poincaré section is used as the judgment basis to guide the controller to output a small perturbation to adjust the damping coefficient of the controlled system, so the chaotic motion can be controlled to a periodic motion by dynamically and slightly adjusting the damping coefficient of the controlled system. In this method, the design of the controller is independent of the order of the controlled system and the structure of the mathematical model. Only the input/output data of the controlled system can be used to complete the design of the controller. In the simulation experiment, the effectiveness and feasibility of the proposed control method in this article are verified by simulation results.

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DUTY-CYCLED SPINNING BASED 3D MOTION CONTROL APPROACH FOR BEVEL-TIPPED FLEXIBLE NEEDLE INSERTION

Journal of Mechanics in Medicine and Biology ◽

10.1142/s0219519418400171 ◽

2018 ◽

Vol 18 (07) ◽

pp. 1840017 ◽

Cited By ~ 1

Author(s):

QIN YAO ◽

XUMING ZHANG

Keyword(s):

Motion Control ◽

Control Method ◽

Tracking Error ◽

Open Loop ◽

Loop Control ◽

3D Motion ◽

Control Approach ◽

Target Error ◽

The Mean ◽

Simulation Results

Flexible needle has been widely used in the therapy delivery because it can advance along the curved lines to avoid the obstacles like important organs and bones. However, most control algorithms for the flexible needle are still limited to address its motion along a set of arcs in the two-dimensional (2D) plane. To resolve this problem, this paper has proposed an improved duty-cycled spinning based three-dimensional (3D) motion control approach to ensure that the beveled-tip flexible needle can track a desired trajectory to reach the target within the tissue. Compared with the existing open-loop duty-cycled spinning method which is limited to tracking 2D trajectory comprised of few arcs, the proposed closed-loop control method can be used for tracking any 3D trajectory comprised of numerous arcs. Distinctively, the proposed method is independent of the tissue parameters and robust to such disturbances as tissue deformation. In the trajectory tracking simulation, the designed controller is tested on the helical trajectory, the trajectory generated by rapidly-exploring random tree (RRT) algorithm and the helical trajectory. The simulation results show that the mean tracking error and the target error are less than 0.02[Formula: see text]mm for the former two kinds of trajectories. In the case of tracking the helical trajectory, the mean tracking error target error is less than 0.5[Formula: see text]mm and 1.5[Formula: see text]mm, respectively. The simulation results prove the effectiveness of the proposed method.

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A Motion Control Method Based on the Knowledge Discovery and Data Mining for Humanoid Robots

Journal of the Robotics Society of Japan ◽

10.7210/jrsj.25.402 ◽

2007 ◽

Vol 25 (3) ◽

pp. 402-409

Author(s):

Kiyotake Kuwayama ◽

Shohei Kato ◽

Hidenori Itoh

Keyword(s):

Data Mining ◽

Knowledge Discovery ◽

Motion Control ◽

Control Method ◽

Humanoid Robots

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Motion Control of an Omni-Directional Walker for Walking Support

Advances in Bioinformatics and Biomedical Engineering - Biomedical Engineering and Cognitive Neuroscience for Healthcare ◽

10.4018/978-1-4666-2113-8.ch003 ◽

2013 ◽

pp. 20-28

Author(s):

Renpeng Tan ◽

Shuoyu Wang ◽

Yinlai Jiang ◽

Kenji Ishida ◽

Masakatsu G. Fujie

Keyword(s):

Adaptive Control ◽

Motion Control ◽

Control Method ◽

Center Of Gravity ◽

Path Tracking ◽

Reference Trajectory ◽

Tracking Errors ◽

Directed Movement ◽

Load Change

With the increase in the percentage of the population defined as elderly, increasing numbers of people suffer from walking disabilities due to illness or accidents. An omni-directional walker (ODW) has been developed that can support people with walking disabilities and allow them to perform indoor walking. The ODW can identify the user’s directional intention based on the user’s forearm pressures and then supports movement in the intended direction. In this chapter, a reference trajectory is generated based on the intended direction in order to support directed movement. The ODW needs to follow the generated path. However, path tracking errors occur because the center of gravity (COG) of the system shifts and the load changes due to user`s pressure. An adaptive control method is proposed to deal with this issue. The results of simulations indicate that the ODW can accurately follow the user’s intended direction by inhibiting the influence of COG shifts and the resulting load change. The proposed scheme is feasible for supporting indoor movement.

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