scholarly journals A Novel Relative Navigation Control Strategy Based on Relation Space Method for Autonomous Underground Articulated Vehicles

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Fengqian Dou ◽  
Yu Meng ◽  
Li Liu ◽  
Qing Gu
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Speed Control ◽  
Relative Navigation ◽  
Competitive Neural Network ◽  
Articulated Vehicles ◽  
Navigation Control ◽  
Control Modules ◽  
Optimal Driving ◽  
Space Method

This paper proposes a novel relative navigation control strategy based on the relation space method (RSM) for articulated underground trackless vehicles. In the RSM, a self-organizing, competitive neural network is used to identify the space around the vehicle, and the spatial geometric relationships of the identified space are used to determine the vehicle’s optimal driving direction. For driving control, the trajectories of the articulated vehicles are analyzed, and data-based steering and speed control modules are developed to reduce modeling complexity. Simulation shows that the proposed RSM can choose the correct directions for articulated vehicles in different tunnels. The effectiveness and feasibility of the resulting novel relative navigation control strategy are validated through experiments.

scholarly journals Robust Quadrotor Control through Reinforcement Learning with Disturbance Compensation

2021 ◽  
Vol 11 (7) ◽  
pp. 3257
Author(s):  
Chen-Huan Pi ◽  
Wei-Yuan Ye ◽  
Stone Cheng
Keyword(s):  
Neural Network ◽  
Reinforcement Learning ◽  
Control Strategy ◽  
External Disturbance ◽  
Control Agent ◽  
Network Control ◽  
Outdoor Environment ◽  
Disturbance Compensation ◽  
Tracking Accuracy ◽  
Control Scheme

In this paper, a novel control strategy is presented for reinforcement learning with disturbance compensation to solve the problem of quadrotor positioning under external disturbance. The proposed control scheme applies a trained neural-network-based reinforcement learning agent to control the quadrotor, and its output is directly mapped to four actuators in an end-to-end manner. The proposed control scheme constructs a disturbance observer to estimate the external forces exerted on the three axes of the quadrotor, such as wind gusts in an outdoor environment. By introducing an interference compensator into the neural network control agent, the tracking accuracy and robustness were significantly increased in indoor and outdoor experiments. The experimental results indicate that the proposed control strategy is highly robust to external disturbances. In the experiments, compensation improved control accuracy and reduced positioning error by 75%. To the best of our knowledge, this study is the first to achieve quadrotor positioning control through low-level reinforcement learning by using a global positioning system in an outdoor environment.

Speed regulation control of tractors’ new dual-flow transmission system based on slip rate resistance classification

2021 ◽  
pp. 095440702110105
Author(s):  
Guang Xia ◽  
Yan Xia ◽  
Xiwen Tang ◽  
Linfeng Zhao ◽  
Baoqun Sun
Keyword(s):  
Control Strategy ◽  
Control Algorithm ◽  
Production Efficiency ◽  
Sliding Mode ◽  
Slip Rate ◽  
Speed Control ◽  
Working Environment ◽  
Vehicle Speed ◽  
Speed Change ◽  
Simulation Results

Fluctuations in operation resistance during the operating process lead to reduced efficiency in tractor production. To address this problem, the project team independently developed and designed a new type of hydraulic mechanical continuously variable transmission (HMCVT). Based on introducing the mechanical structure and transmission principle of the HMCVT system, the priority of slip rate control and vehicle speed control is determined by classifying the slip rate. In the process of vehicle speed control, the driving mode of HMCVT system suitable for the current resistance state is determined by classifying the operation resistance. The speed change rule under HMT and HST modes is formulated with the goal of the highest production efficiency, and the displacement ratio adjustment surfaces under HMT and HST modes are determined. A sliding mode control algorithm based on feedforward compensation is proposed to address the problem that the oil pressure fluctuation has influences on the adjustment accuracy of hydraulic pump displacement. The simulation results of Simulink show that this algorithm can not only accurately follow the expected signal changes, but has better tracking stability than traditional PID control algorithm. The HMCVT system and speed control strategy models were built, and simulation results show that the speed control strategy can restrict the slip rate of driving wheels within the allowable range when load or road conditions change. When the tractor speed is lower than the lower limit of the high-efficiency speed range, the speed change law formulated in this paper can improve the tractor speed faster than the traditional rule, and effectively ensure the production efficiency. The research results are of great significance for improving tractor’s adaptability to complex and changeable working environment and promoting agricultural production efficiency.

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