Professor Deqing Huang received the B.S. and Ph.D. degrees from Sichuan University, Chengdu, China, in 2002 and 2007, respectively, and the second Ph.D. degree with a major in control engineering from the Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore, in 2011. From January 2010 to February 2013, he was a Research Fellow with the Department of Electrical and Computer Engineering, NUS. From March 2013 to January 2016, he was a Research Associate with the Department of Aeronautics, Imperial College London, London, U.K. In January 2016, he joined the Department of Electronic and Information Engineering, Southwest Jiaotong University, Chengdu, China, as a Professor and the Department Head. His current research interests include modern control theory, artificial intelligence, and fault diagnosis as well as robotics Dr Wei Yu received the B.S. degree in rail transportation signal and control from Henan Polytechnic University, Jiaozuo, China, in 2018, the M.S. degree in control science and engineering from the School of Electric Engineering and Automation, Henan Polytechnic University, Jiaozuo, China, in 2021 and the Ph.D. degree in control science and engineering with Southwest Jiaotong University, Chengdu, China, in 2024. He is currently conducting Boya postdoctoral research at Peking University. His research interests include high-speed train control, data-driven control, iterative learning control and networked system control

• 1. Introduction2. Preliminaries3. Coordinated MFAC of MHSTs Under Faded Channels and DoS Attacks4. DD Consensus of MHSTs Via Random Topologies with Recovery Mechanism5. Weighted T2T Communication-Based DD Consensus of MHSTs Under DA6. Active Quantizer-Based DMFAC for MHSTs Against Sensor Bias7. HOIM Based Data-Driven ILC of HSTs Subject to Faded Channels8. Fading-Based Coordinated MFAILC of MHSTs Against DoS Attacks9. Attack Recovery-Based DMFAILC for MHSTs with Fading Compensation10. Event-Triggered DMFAILC for MHSTs with Switching Topologies11. DMFAILC for MHSTs under Weighted Communication and Saturations12. DMFAILC for MHSTs Considering Quantizations and Measurement Bias

Professor Deqing Huang received the B.S. and Ph.D. degrees from Sichuan University, Chengdu, China, in 2002 and 2007, respectively, and the second Ph.D. degree with a major in control engineering from the Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore, in 2011. From January 2010 to February 2013, he was a Research Fellow with the Department of Electrical and Computer Engineering, NUS. From March 2013 to January 2016, he was a Research Associate with the Department of Aeronautics, Imperial College London, London, U.K. In January 2016, he joined the Department of Electronic and Information Engineering, Southwest Jiaotong University, Chengdu, China, as a Professor and the Department Head. His current research interests include modern control theory, artificial intelligence, and fault diagnosis as well as robotics Dr Wei Yu received the B.S. degree in rail transportation signal and control from Henan Polytechnic University, Jiaozuo, China, in 2018, the M.S. degree in control science and engineering from the School of Electric Engineering and Automation, Henan Polytechnic University, Jiaozuo, China, in 2021 and the Ph.D. degree in control science and engineering with Southwest Jiaotong University, Chengdu, China, in 2024. He is currently conducting Boya postdoctoral research at Peking University. His research interests include high-speed train control, data-driven control, iterative learning control and networked system control

• 1. Introduction2. Preliminaries3. Coordinated MFAC of MHSTs Under Faded Channels and DoS Attacks4. DD Consensus of MHSTs Via Random Topologies with Recovery Mechanism5. Weighted T2T Communication-Based DD Consensus of MHSTs Under DA6. Active Quantizer-Based DMFAC for MHSTs Against Sensor Bias7. HOIM Based Data-Driven ILC of HSTs Subject to Faded Channels8. Fading-Based Coordinated MFAILC of MHSTs Against DoS Attacks9. Attack Recovery-Based DMFAILC for MHSTs with Fading Compensation10. Event-Triggered DMFAILC for MHSTs with Switching Topologies11. DMFAILC for MHSTs under Weighted Communication and Saturations12. DMFAILC for MHSTs Considering Quantizations and Measurement Bias

Professor Deqing Huang received the B.S. and Ph.D. degrees from Sichuan University, Chengdu, China, in 2002 and 2007, respectively, and the second Ph.D. degree with a major in control engineering from the Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore, in 2011. From January 2010 to February 2013, he was a Research Fellow with the Department of Electrical and Computer Engineering, NUS. From March 2013 to January 2016, he was a Research Associate with the Department of Aeronautics, Imperial College London, London, U.K. In January 2016, he joined the Department of Electronic and Information Engineering, Southwest Jiaotong University, Chengdu, China, as a Professor and the Department Head. His current research interests include modern control theory, artificial intelligence, and fault diagnosis as well as robotics Dr Wei Yu received the B.S. degree in rail transportation signal and control from Henan Polytechnic University, Jiaozuo, China, in 2018, the M.S. degree in control science and engineering from the School of Electric Engineering and Automation, Henan Polytechnic University, Jiaozuo, China, in 2021 and the Ph.D. degree in control science and engineering with Southwest Jiaotong University, Chengdu, China, in 2024. He is currently conducting Boya postdoctoral research at Peking University. His research interests include high-speed train control, data-driven control, iterative learning control and networked system control

• 1. Introduction2. Preliminaries3. Coordinated MFAC of MHSTs Under Faded Channels and DoS Attacks4. DD Consensus of MHSTs Via Random Topologies with Recovery Mechanism5. Weighted T2T Communication-Based DD Consensus of MHSTs Under DA6. Active Quantizer-Based DMFAC for MHSTs Against Sensor Bias7. HOIM Based Data-Driven ILC of HSTs Subject to Faded Channels8. Fading-Based Coordinated MFAILC of MHSTs Against DoS Attacks9. Attack Recovery-Based DMFAILC for MHSTs with Fading Compensation10. Event-Triggered DMFAILC for MHSTs with Switching Topologies11. DMFAILC for MHSTs under Weighted Communication and Saturations12. DMFAILC for MHSTs Considering Quantizations and Measurement Bias