Control and simulation evaluation have experienced a rapid development during the last few decades. Due to the occurrence of complex networked control systems, traditional control and evaluation approaches face new challenges such as strong coupling, serious nonlinearity, complex uncertainty, wasteful energy consumption and weak safety. The result is that more intelligent control and simulation evaluation approaches urgently need to be proposed for guaranteeing control performance. To this end, learning mechanism, adaptive neural network/fuzzy approximation, expert experience and some other advanced technologies are integrated into traditional control approaches. The purpose of this Special Issue is to present a collection of articles showing novel developments and results in the intelligent control and simulation evaluation. Both theoretical and experimental studies are welcome, as well as comprehensive review and survey papers.
A total of eight papers in various fields of control and simulation evaluation are presented in this Special Issue. In [1], a PID controller that combines a back-propagation neural network and adversarial learning-based grey wolf optimization is presented. To enhance the unpredictable behavior and capacity for exploration of the grey wolf, a new parameter-learning technique is developed. In [2], a data-driven nonlinear control approach, called error-dynamics-based dual heuristic dynamic programming, is proposed for air vehicle attitude control. To solve the optimal tracking control problem, the augmented system is defined by the derived error dynamics and reference trajectory so that the actor neural network can learn the feed-forward and feedback control terms at the same time. In [3], several simulation tools for cloud computing in the literature are reviewed, and a parametric evaluation of cloud simulation tools is presented based on the identified parameters. In [4], parallel hierarchical scheduling of multi-core processors in avionics hypervisor is studied. A new response time analysis algorithm is proposed, which offers a general limit for other execution sequences of noncritical joints. In [5], the performance evaluation of the existing load-balancing algorithms such as particle swarm optimization, round robin, equally spread current execution and throttled load balancing is conducted. In [6], a multi-level fuzzy evaluation model based on combined empowerment is proposed for the reliability evaluation of an integrated energy system. In [7], the UAV cluster behavior modeling is studied, where a novel representation framework based on the Petri nets is proposed. Based on multi-core multi-threaded processors, a security hardware unit with micro-kernel virtualization technology and a virtualization airborne trusted general computing service architecture is proposed in [8], where key technologies including a high-performance processing, high-security hardware unit, a virtualization management software unit and a virtualization security protection architecture are designed.
Although submissions for this Special Issue have been closed, more in-depth research in the field of control and simulation evaluation continues to address the challenges.
Author Contributions
Writing—review and editing, Y.G.; writing—original draft preparation, J.L.; supervision, Q.L. and Z.L. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Acknowledgments
Thanks to all the authors and peer reviewers for their valuable contributions to this Special Issue “Advanced Technology of Intelligent Control and Simulation Evaluation”. I would also like to express my gratitude to all the staff and people involved in this Special Issue.
Conflicts of Interest
The authors declare no conflict of interest.
References
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