scholarly journals Reactive Autonomous Navigation of UAVs for Dynamic Sensing Coverage of Mobile Ground Targets

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3720 ◽  
Author(s):  
Hailong Huang ◽  
Andrey V. Savkin ◽  
Xiaohui Li
Keyword(s):  
Autonomous Navigation ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Complex Case ◽  
Multiple Targets ◽  
Video Cameras ◽  
Sensing Coverage ◽  
Navigation Algorithm ◽  
Multiple Uavs ◽  
Simulation Results

This paper addresses a problem of autonomous navigation of unmanned aerial vehicles (UAVs) for the surveillance of multiple moving ground targets. The ground can be flat or uneven. A reactive real-time sliding mode control algorithm is proposed that navigates a team of communicating UAVs, equipped with ground-facing video cameras, towards moving targets to increase some measure of sensing coverage of the targets by the UAVs. Moreover, the Voronoi partitioning technique is adopted to reduce the movement range of the UAVs and decrease the revisit times of the targets. Extensive computer simulations, from the simple case with one UAV and multiple targets to the complex case with multiple UAVs and multiple targets, are conducted to demonstrate the performance of the developed autonomous navigation algorithm. The scenarios where the terrain is uneven are also considered. As shown in the simulation results, although the additional VP technique leads to some extra computation burden, the usage of the VP technique considerably reduces the target revisit time compared to the algorithm without this technique.

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.

scholarly journals Validation of a Dynamic Planning Navigation Strategy Applied to Mobile Terrestrial Robots

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4322 ◽  
Author(s):  
Caroline Silva ◽  
Átila de Oliveira ◽  
Marcelo Fernandes
Keyword(s):  
Genetic Algorithm ◽  
Population Size ◽  
Autonomous Navigation ◽  
Genetic Parameters ◽  
Dynamic Environments ◽  
Dynamic Planning ◽  
Navigation Algorithm ◽  
Navigation Strategy ◽  
Terrestrial Environments ◽  
Simulation Results

This work describes the performance of a DPNA-GA (Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm) algorithm applied to autonomous navigation in unknown static and dynamic terrestrial environments. The main aim was to validate the functionality and robustness of the DPNA-GA, with variations of genetic parameters including the crossover rate and population size. To this end, simulations were performed of static and dynamic environments, applying the different conditions. The simulation results showed satisfactory efficiency and robustness of the DPNA-GA technique, validating it for real applications involving mobile terrestrial robots.

Path Tracking of a Fixed-Wing Autonomous Aerial Vehicle by High Order Sliding Mode Control

2011 ◽  
Author(s):  
Herman Castan˜eda Cuevas ◽  
Jesu´s de Leo´n Morales ◽  
Ernesto Olgui´n-Di´az
Keyword(s):  
Control Algorithm ◽  
Sliding Mode ◽  
Time Derivative ◽  
Control Design ◽  
Unmodeled Dynamics ◽  
Sliding Modes ◽  
Motion Models ◽  
Tracking Controller ◽  
Aerial Vehicle ◽  
Simulation Results

In this paper, a robust control algorithm, based on sliding modes techniques, designed for trajectory tracking is applied to a fixed-wing small Autonomous Aerial Vehicle (AAV). Based on a mathematical modeling, parameters identification, and aerodynamics of both the AAV fuselage and its mobile surfaces a full dynamical model is obtained, where the control is proven. However, for control design, simplified versions of the motion models are studied resulting in simplified independent controller for the roll, pitch and yaw trajectories. Due to the nature of such controller, time derivative of control variables are needed but not available. Numerical differentiators also based on sliding modes are used in order to estimate those derivatives. Simulation results are given to illustrate the performance of the proposed tracking controller under parametric and unmodeled dynamics.

scholarly journals PRM navigation in trading drone and Gazebo simulation

2020 ◽  
Vol 14 (1) ◽  
pp. 43-50
Author(s):  
Franklin Pineda Torres ◽  
Luis Alejandro Arias Barragán
Keyword(s):  
Operating System ◽  
Mean Square Error ◽  
Autonomous Navigation ◽  
Control Algorithm ◽  
Simulation Software ◽  
Location Information ◽  
Mean Square ◽  
Navigation Algorithm ◽  
Propagation Delays ◽  
The Mean

Starting from a commercial drone AR Dron Parrot 2.0, an autonomous navigation process is developed with a PRM probabilistic route planner in real time, through a ROS network between the drone and the Gazebo simulation software. Using the robotics system toolbox from software Matlab that interacts with Gazebo, it is possible to study the desired trajectory planner, in addition, the creation and connection of the ROS network on the Linux operating system, where the navigation algorithm is analyzed from the practical vs., simulation points of views. The errors that are presented are minimal, taking into account the propagation delays and the control algorithm; this is in charge of receiving location information in order to correct and minimized the mean square error.

scholarly journals Anti-Disturbance Fault-Tolerant Sliding Mode Control for Systems with Unknown Faults and Disturbances

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1487
Author(s):  
Xiaoli Zhang ◽  
Zhengyu Zhu ◽  
Yang Yi
Keyword(s):  
Control Algorithm ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Actuator Faults ◽  
Controlled System ◽  
Simulation Results ◽  
The Stability ◽  
Mismatched Disturbances ◽  
The Impact

In this paper, a novel control algorithm with the capacity of fault tolerance and anti-disturbance is discussed for the systems subjected to actuator faults and mismatched disturbances. The fault diagnosis observer (FDO) and the disturbance observer (DO) are successively designed to estimate the dynamics of unknown faults and disturbances. Furthermore, with the help of the observed information, a sliding surface and the corresponding sliding mode controller are proposed to compensate the actuator faults and eliminate the impact of mismatched disturbances simultaneously. Meanwhile, the convex optimization algorithm is discussed to guarantee the stability of the controlled system. The favorable anti-disturbance and fault-tolerant results can also be proved. Finally, the validity of the algorithm is certified by the simulation results for typical unmanned aerial vehicles (UAV) systems.

Sliding Adaptive Control of a Chinese Medicine Sugar Precipitation Process

2013 ◽  
Vol 380-384 ◽  
pp. 441-445 ◽  
Author(s):  
Hong Jun Duan ◽  
Li Zhao
Keyword(s):  
Adaptive Control ◽  
Chinese Medicine ◽  
Control Algorithm ◽  
Crystal Size ◽  
Sliding Mode ◽  
Precipitation Process ◽  
Mixed Solution ◽  
Modeling Error ◽  
Simulation Results ◽  
Adaptive Control Algorithm

A dynamic model dedicated to Chinese medicine sugar precipitation was designed, without consideration of crystal size distribution. A batch crystallizer was extended for studying the crystallization kinetics. Sliding mode adaptive control algorithm was proposed for the uncertain nonlinear systems. The scheme is robust for the uncertainties and overcomes the chattering in the input of sliding mode control in presence of disturbances and modeling error. It was applied to the precipitation control of sucrose-glucose mixed solution, and the validity of the proposed algorithm was supported by simulation results.

Model Predictive Sliding Mode Control: For Constraint Satisfaction and Robustness

2013 ◽  
Author(s):  
Yizhou Wang ◽  
Wenjie Chen ◽  
Masayoshi Tomizuka ◽  
Badr N. Alsuwaidan
Keyword(s):  
Sliding Mode Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Closed Loop ◽  
Sliding Mode ◽  
Input Constraints ◽  
Robust Performance ◽  
Mode Control ◽  
Time Optimal ◽  
Simulation Results

A novel combination of model predictive control (MPC) and sliding mode control (SMC) is presented in this paper. The motivation is to inherit the ability to explicitly deal with state and input constraints from MPC, and the good robustness property from SMC. The design of the finite-time optimal control problem and the conditions for the persistent feasibility and the closed-loop stability are discussed. Simulation results are shown to demonstrate the nominal and robust performance of the proposed control algorithm.

Design of Intelligent Controller for Ship Motion with Input Saturation Based on Optimized Radial Basis Function Neural Network

2020 ◽  
Vol 13 ◽  
Author(s):  
Renqiang Wang ◽  
Qinrong Li ◽  
Shengze Miao ◽  
Keyin Miao ◽  
Hua Deng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Sliding Mode Control ◽  
Intelligent Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Input Saturation ◽  
Ship Motion ◽  
Mode Control

Abstract: The purpose of this paper was to design an intelligent controller of ship motion based on sliding mode control with a Radial Basis Function (RBF) neural network optimized by the genetic algorithm and expansion observer. First, the improved genetic algorithm based on the distributed genetic algorithm with adaptive fitness and adaptive mutation was used to automatically optimize the RBF neural network. Then, with the compensation designed by the RBF neural network, anti-saturation control was realized. Additionally, the intelligent control algorithm was introduced by Sliding Mode Control (SMC) with the stability theory. A comparative study of sliding mode control integrated with the RBF neural network and proportional–integral–derivative control combined with the fuzzy optimization model showed that the stabilization time of the intelligent control system was 43.75% faster and the average overshoot was reduced by 52% compared with the previous two attempts. Background: It was known that the Proportional-Integral-Derivative (PID) control and self-adaptation control cannot really solve the problems of frequent disturbance from external wind and waves, as well as the problems with ship nonlinearity and input saturation. So, the previous ship motion controller should be transformed by advanced intelligent technology, on the basis of referring to the latest relevant patent design methods. Objective: An intelligent controller of ship motion was designed based on optimized Radial Basis Function Neural Network (RBFNN) in the presence of non-linearity, uncertainty, and limited input. Methods: The previous ship motion controller was remodeled based on Sliding Mode Control (SMC) with RBFNN optimized by improved genetic algorithm and expansion observer. The intelligent control algorithm integrated with genetic neural network solved the problem of system model uncertainty, limited control input, and external interference. Distributed genetic with adaptive fitness and adaptive mutation method guaranteed the adequacy of search and the global optimal convergence results, which enhanced the approximation ability of RBFNN. With the compensation designed by the optimized RBFNN, it was realized anti-saturation control. The chattering caused by external disturbance in SMC controller was reduced by the expansion observer. Results: A comparative study with RBFNN-SMC control and fuzzy-PID control, the stabilization time of the intelligent control system was 43.75% faster, the average overshoot was reduced by 52%, compared to the previous two attempts. Conclusion: The intelligent control algorithm succeed in dealing with the problems of nonlinearity, uncertainty, input saturation, and external interference. The intelligent control algorithm can be applied into research and development ship steering system, which would be created a new patent.

scholarly journals Research of Active Power Filter Modeling with Grid Impedance in Feedback Linearization and Quasi-Sliding Mode Control

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Zeyu Shi ◽  
Yingpin Wang ◽  
Yunxiang Xie ◽  
Lanfang Li ◽  
Xiaogang Xu
Keyword(s):  
Sliding Mode Control ◽  
Feedback Linearization ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Active Power Filter ◽  
Active Power ◽  
Pi Control ◽  
Power Filter ◽  
Mode Control ◽  
Grid Impedance

Active power filter (APF) is the most popular device in regulating power quality issues. Currently, most literatures ignored the impact of grid impedance and assumed the load voltage is ideal, which had not described the system accurately. In addition, the controllers applied PI control; thus it is hard to improve the compensation quality. This paper establishes a precise model which consists of APF, load, and grid impedance. The Bode diagram of traditional simplified model is obviously different with complete model, which means the descriptions of the system based on the traditional simplified model are inaccurate and incomplete. And then design exact feedback linearization and quasi-sliding mode control (FBL-QSMC) is based on precise model in inner current loop. The system performances in different parameters are analyzed and dynamic performance of proposed algorithm is compared with traditional PI control algorithm. At last, simulations are taken in three cases to verify the performance of proposed control algorithm. The results proved that the proposed feedback linearization and quasi-sliding mode control algorithm has fast response and robustness; the compensation performance is superior to PI control obviously, which also means the complete modeling and proposed control algorithm are correct.

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