全文截稿: 2021-07-01
影响因子: 3.193
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 3区
• 小类 : 自动化与控制系统 - 3区
• 小类 : 工程：电子与电气 - 3区
网址：
https://www.journals.elsevier.com/control-engineering-practice
During the past decades, autonomous systems have attracted considerable attention due to their capability of performing various operations with minimal or without human supervision. Because of the salient features of high autonomy and mobility, they are vitally important tools for numerous applications in civilian and military missions covering the areas of marine, ground, aeronautics, and aerospace. However, with the ever-increasing mission complexity, the traditional control algorithms can barely satisfy the need for high control efficiency and enhanced control performance, especially under diverse and challenging environmental conditions. In view of this, intelligent control of autonomous systems has been evolving by taking advantage of advanced technologies including neural networks, fuzzy logic systems, learning and adaptive control, model predictive control, and so on. Moreover, since the cooperative operations of multiple autonomous systems offer great advantages with improved capability and swarm intelligence, a critical trend is intelligent collaborative control of autonomous systems. Other topics such as system safety, performance optimization, fault detection and accommodation, human-machine interaction for autonomous systems are also remained to be further investigated. This Special Issue will present the recent major theoretical and technical advances of intelligent control methods for autonomous systems through simulations and experiments. The purpose of the Special Issue is to: 1) increase the control efficiency, robustness, and self-adaptation of autonomous systems to unexpected internal and external environmental changes; 2) improve the operational intelligence of single or multiple autonomous systems; 3) explore the future control strategy and mission planning for autonomous systems. The Special Issue is aimed at both academia and industry: articles presenting applications in the real case are solicited together with more academic articles with innovative theoretical aspects, but which always present at least simulations by a benchmark representative of the real case.
Potential topics of interest include, but are not limited to:
Intelligent control of autonomous surface/underwater/ground/aerial vehicles
Adaptive and learning control of autonomous systems
Neural network and fuzzy control of autonomous systems
Approximate/adaptive dynamic programming for intelligent control of autonomous systems
Deep learning, reinforcement learning, and meta learning of autonomous systems
Fuzzy inference systems, artificial neural networks, and genetic algorithms for autonomous systems
Swarm intelligence and collaborative control of autonomous systems
Hybrid evolutionary systems: neurofuzzy systems, fuzzy genetic algorithm, evolutionary neurofuzzy systems, genetic learning-PSO for autonomous systems
Human-machine interactions and shared control autonomous systems
Evolutionary control of autonomous systems
Intelligent optimization of autonomous systems
Intelligent mission planning for single or multiple autonomous systems
Intelligent fault detection and fault-tolerant control of autonomous systems
Intelligent model predictive control of autonomous systems
Adaptive disturbance estimation, state observation of autonomous systems
Design, development, validation, and applications of intelligent autonomous systems
Control Engineering Practice is a premier IFAC journal that publishes papers with direct applications of profound control theory and its supporting tools in all possible areas of automation.
