Contributed by: Kay Tancock, k.tancock@elsevier.com
Control Engineering Practice
Volume 108, March 2021
Frontiers in Control Engineering Practice:
-T. Hagglund., A feedforward approach to mid-ranging control ¨
Regular Papers:
- Hossein Parastvand, Airlie Chapman, Octavian Bass, Stefan Lachowicz., Graph automorphic approaches to the robustness of complex networks
- Zihao Liu, Arash M. Dizqah, Jose M. Herreros, Joschka Schaub, Olivier Haas., Simultaneous control of NOx, soot and fuel economy of a diesel engine with dual-loop EGR and VNT using economic MPC
- Mahshad Valipour, Kathryn M. Toffolo, Luis A. Ricardez-Sandoval., State estimation and sensor location for Entrained-Flow Gasification Systems using Kalman Filter
- Shengquan Li, Chaowei Zhu, Qibo Mao, Jinya Su, Juan Li., Active disturbance rejection vibration control for an all-clamped piezoelectric plate with delay
- Yuhua Qi, Yang Zhu, Jianan Wang, Jiayuan Shan, Hugh H.T. Liu., MUDE-based control of quadrotor for accurate attitude tracking
- Roya Firoozi, Xiaojing Zhang, Francesco Borrelli., Formation and reconfiguration of tight multi-lane platoons
- Abdul-Basset A. Al-Hussein, Fadhil Rahma Tahir, Viet-Thanh Pham., Fixed-time synergetic control for chaos suppression in endocrine glucose–insulin regulatory system
- Manne Held, Oscar Flardh, Jonas M ¨ artensson., Experimental evaluation of a look-ahead controller for a heavy-duty vehicle with varying velocity demands
- Haoran Tan, Yaonan Wang, Hang Zhong, Min Wu, Yiming Jiang., Coordination of low-power nonlinear multi-agent systems using cloud computing and a data-driven hybrid predictive control method
- Dzung Tran, Tansel Yucelen, Selahattin Burak Sarsilmaz., Finite-time control of multiagent networks as systems with time transformation and separation principle
Virtual Special Section on Machine Learning and Advanced Data Analytics in Control Engineering Practice;
Edited by Aditya Tulsyan, Manabu Kano, Margret Bauer and Zhiqiang Ge.
- Yongxiang Lei, Hamid Reza Karimi, Lihui Cen, Xiaofang Chen, Yongfang Xie., Processes soft modeling based on stacked autoencoders and wavelet extreme learning machine for aluminum plant-wide application
