Unmanned Powerboat Motion Terminal Control in an Environment with Moving Obstacles

2021 ◽  
Vol 22 (3) ◽  
pp. 145-154
Author(s):  
V. I. Finaev ◽  
M. Yu. Medvedev ◽  
V. Kh. Pshikhopov ◽  
V. A. Pereverzev ◽  
V. V. Soloviev

The major point for consideration throughout this paper is controlling the motion of an unmanned powerboat in an obstructed environment with stationary and moving objects. It offers a procedure for the terminal control law development based on the powerboat programmed motion trajectory in a polynomial form and proposes position-trajectory-based control algorithms. A hybrid method based on virtual fields and unstable driving modes, taking into account powerboat speeds and obstacles, is used to plan motion trajectories for obstacle avoidance. There were experiments carried out to test the developed methods and algorithms meanwhile estimating the energy consumption for control, the length of the trajectory and the safety indicator for obstacle avoidance. The novelty of the proposed approach lies in the method used to develop a local movement trajectory in the field with obstacles and in the hybridization of trajectory scheduling methods. This approach allows us to achieve a given safe distance when avoiding obstacles and virtually eliminate the chances of an emergency collision. The presented results can be used in systems of boats autonomous motion control and allow safe stationary and dynamic obstacles avoidance.

2021 ◽  
pp. 13-21
Author(s):  
Eugenie L. Eremin ◽  
Larisa V. Nikiforova ◽  
Evgeniy A. Shelenok

The article studies control algorithms of multiply connected system for dynamic plants with control saturation and nonlinear cross-connections. The authors of the article offer a decentralized control law based on the hyperstability criterion. They also use this law to constuct the MIMO servo system with input saturation. To illustrate the capability of the proposed decentralized robust control system the authors use an inverted pendulums connected by a spring.


Author(s):  
V.P. Ivanov

The article deals with the problem of synthesis of terminal control. A functional, a nonlinear mathematical model of a dynamic object, restrictions on the maximum permissible values of control are given. The control law is synthesized. The following statement is proved: the synthesis of the optimal control is carried out using the entire initial mathematical model of the dynamical object, but to calculate the control at any particular moment of time, it is possible to use a reduced (truncated) model, which simplifies the computational algorithms. Thus, there is an informational dualism of the manage- ment task. The approach is an extension of the principle of information redefinition of Yu.B. Germeier to the area of optimal terminal control.


Author(s):  
Yimin Chen ◽  
Chuan Hu ◽  
Yechen Qin ◽  
Mingjun Li ◽  
Xiaolin Song

Obstacle avoidance strategy is important to ensure the driving safety of unmanned ground vehicles. In the presence of static and moving obstacles, it is challenging for the unmanned ground vehicles to plan and track the collision-free paths. This paper proposes an obstacle avoidance strategy consists of the path planning and the robust fuzzy output-feedback control. A path planner is formed to generate the collision-free paths that avoid static and moving obstacles. The quintic polynomial curves are employed for path generation considering computational efficiency and ride comfort. Then, a robust fuzzy output-feedback controller is designed to track the planned paths. The Takagi–Sugeno (T–S) fuzzy modeling technique is utilized to handle the system variables when forming the vehicle dynamic model. The robust output-feedback control approach is used to track the planned paths without using the lateral velocity signal. The proposed obstacle avoidance strategy is validated in CarSim® simulations. The simulation results show the unmanned ground vehicle can avoid the static and moving obstacles by applying the designed path planning and robust fuzzy output-feedback control approaches.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4082 ◽  
Author(s):  
Zhengjun Qiu ◽  
Nan Zhao ◽  
Lei Zhou ◽  
Mengcen Wang ◽  
Liangliang Yang ◽  
...  

Using intelligent agricultural machines in paddy fields has received great attention. An obstacle avoidance system is required with the development of agricultural machines. In order to make the machines more intelligent, detecting and tracking obstacles, especially the moving obstacles in paddy fields, is the basis of obstacle avoidance. To achieve this goal, a red, green and blue (RGB) camera and a computer were used to build a machine vision system, mounted on a transplanter. A method that combined the improved You Only Look Once version 3 (Yolov3) and deep Simple Online and Realtime Tracking (deep SORT) was used to detect and track typical moving obstacles, and figure out the center point positions of the obstacles in paddy fields. The improved Yolov3 has 23 residual blocks and upsamples only once, and has new loss calculation functions. Results showed that the improved Yolov3 obtained mean intersection over union (mIoU) score of 0.779 and was 27.3% faster in processing speed than standard Yolov3 on a self-created test dataset of moving obstacles (human and water buffalo) in paddy fields. An acceptable performance for detecting and tracking could be obtained in a real paddy field test with an average processing speed of 5–7 frames per second (FPS), which satisfies actual work demands. In future research, the proposed system could support the intelligent agriculture machines more flexible in autonomous navigation.


2013 ◽  
Vol 380-384 ◽  
pp. 591-594
Author(s):  
Nai Jian Chen ◽  
Fang Zhen Song ◽  
Hong Hua Zhao ◽  
Ying Jun Li

This paper studies a nonholonomic mobile manipulator that consists of a wheeled mobile platform with a mounted serial manipulator. It is designed and developed to navigate autonomously in handling moving objects subjected to nonholonomic constraints. A camera is mounted on the front of the platform and employed to identify and collect information about distance, velocity and direction of the object. With that information collected, a motion planning system determines the preferred operation region and the obstacle-avoidance area, and thus generates the expected trajectory of the mobile manipulator. Experimental results are shown that the mobile manipulator can identify the target, generate trajectories and grasp the moving object autonomously.


Author(s):  
Junyoung Park ◽  
Alan Palazzolo ◽  
Raymond Beach

Theory and simulation results have demonstrated that four, variable speed flywheels could potentially provide the energy storage and attitude control functions of existing batteries and control moment gyros on a satellite. Past modeling and control algorithms were based on the assumption of rigidity in the flywheel’s bearings and the satellite structure. This paper provides simulation results and theory, which eliminates this assumption utilizing control algorithms for active vibration control (AVC), flywheel shaft levitation, and integrated power transfer and attitude control (IPAC), that are effective even with low stiffness active magnetic bearings (AMBs) and flexible satellite appendages. The flywheel AVC and levitation tasks are provided by a multiple input–multiple output control law that enhances stability by reducing the dependence of the forward and backward gyroscopic poles with changes in flywheel speed. The control law is shown to be effective even for (1) large polar to transverse inertia ratios, which increases the stored energy density while causing the poles to become more speed dependent, and for (2) low bandwidth controllers shaped to suppress high frequency noise. Passive vibration dampers are designed to reduce the vibrations of flexible appendages of the satellite. Notch, low-pass, and bandpass filters are implemented in the AMB system to reduce and cancel high frequency, dynamic bearing forces and motor torques due to flywheel mass imbalance. Successful IPAC simulation results are presented with a 12% initial attitude error, large polar to transverse inertia ratio (IP∕IT), structural flexibility, and unbalance mass disturbance.


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