FPGA Implementation of Modified Swarm Optimization Based Control Strategy for a Mobile Robot

2019 ◽  
pp. 280-290
Author(s):  
Sandipan Pine ◽  
B. B. Choudhury
Keyword(s):  
Mobile Robot ◽  
Control Strategy ◽  
Fpga Implementation ◽  
Swarm Optimization

Design and FPGA Implementation of a New Intelligent Behaviors Fusion for Mobile Robot Using Fuzzy Logic

2019 ◽  
Vol 12 (1) ◽  
pp. 1 ◽  
Author(s):  
Badr El Kari ◽  
Hassan Ayad ◽  
Abdeljalil El Kari ◽  
Mostafa Mjahed ◽  
Claudiu Pozna
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Fpga Implementation

DEVELOPMENT OF A CONTROL STRATEGY FOR MOBILE ROBOT NAVIGATION IN UNKNOWN TERRAIN

2019 ◽  
Author(s):  
Diego Gabriel Gomes Rosa ◽  
Carlos Luiz Machado de souza junior ◽  
Marco Antonio Meggiolaro ◽  
Luiz Fernando Martha
Keyword(s):  
Mobile Robot ◽  
Control Strategy ◽  
Robot Navigation ◽  
Mobile Robot Navigation

A multi-objective operation strategy optimization for ice storage systems based on decentralized control structure

2020 ◽  
Vol 42 (1) ◽  
pp. 62-81
Author(s):  
Yanhuan Ren ◽  
Junqi Yu ◽  
Anjun Zhao ◽  
Wenqiang Jing ◽  
Tong Ran ◽  
...  
Keyword(s):  
Energy Saving ◽  
Decentralized Control ◽  
Optimization Algorithm ◽  
Control Strategy ◽  
Load Distribution ◽  
Air Conditioning ◽  
Control Structure ◽  
Ice Storage ◽  
Swarm Optimization ◽  
Multi Objective

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.

scholarly journals A Hybrid Tracking Control Strategy for Nonholonomic Wheeled Mobile Robot Incorporating Deep Reinforcement Learning Approach

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 15592-15602
Author(s):  
Xueshan Gao ◽  
Rui Gao ◽  
Peng Liang ◽  
Qingfang Zhang ◽  
Rui Deng ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Mobile Robot ◽  
Control Strategy ◽  
Tracking Control ◽  
Wheeled Mobile Robot ◽  
Learning Approach

scholarly journals An Optimal Longitudinal Control Strategy of Platoons Using Improved Particle Swarm Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhizhou Wu ◽  
Zhibo Gao ◽  
Wei Hao ◽  
Jiaqi Ma
Keyword(s):  
Particle Swarm Optimization ◽  
Control Strategy ◽  
Ride Comfort ◽  
Particle Swarm ◽  
Experimental Simulation ◽  
Driving Safety ◽  
Relative Speed ◽  
Longitudinal Control ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization

Most existing longitudinal control strategies for connected and automated vehicles (CAVs) have unclear adaptability without scientific analysis regarding the key parameters of the control algorithm. This paper presents an optimal longitudinal control strategy for a homogeneous CAV platoon. First of all, the CAV platoon models with constant time-headway gap strategy and constant spacing gap strategy were, respectively, established based on the third-order linear vehicle dynamics model. Then, a linear-quadratic optimal controller was designed considering the perspectives of driving safety, efficiency, and ride comfort with three performance indicators including vehicle gap error, relative speed, and desired acceleration. An improved particle swarm optimization algorithm was used to optimize the weighting coefficients for the controller state and control variables. Based on the Matlab/Simulink experimental simulation, the analysis results show that the proposed strategy can significantly reduce the gap error and relative speed and improve the flexibility and initiative of the platoon control strategy compared with the unoptimized strategies. Sensitivity analysis was provided for communication lag and actuator lag in order to prove the applicability and effectiveness of this proposed strategy, which will achieve better distribution of system performance.

An adaptive control strategy for indoor leader-following of wheeled mobile robot

2020 ◽  
Vol 357 (4) ◽  
pp. 2131-2148 ◽  
Author(s):  
Ying Zou ◽  
Changyun Wen ◽  
Mao Shan ◽  
Mingyang Guan
Keyword(s):  
Adaptive Control ◽  
Mobile Robot ◽  
Control Strategy ◽  
Wheeled Mobile Robot ◽  
Leader Following ◽  
Adaptive Control Strategy
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