Advanced Control Systems Laboratory
Research Field
Distinguished Professor and internationallyrecognized researcher in Electrical Engineering, specializing in Control Systems, Robotics, and AI. With 16+ years of experience, author of 380+ high-impact publications (10,800+ citations, H-index: 60) and holder of 2 patents. A proven leader in securing and executing over $900K in research funding across 10+ projects. Honored as a Highly-Cited Researcher (ESI) and within the Top 1% globally in Engineering. Included in Stanford University’s World’s Top 2% Scientists List for 6 consecutive years (2019-2024). Recipient of Taiwan's highest academic and national honors, including the Research Excellence Award (2023), Plum Blossom Recognition Award, Taiwan (2024) and Taiwanese Nationality (2025), for exceptional contributions to the field. IEEE Senior Member and dedicated mentor in pioneering robotics and control research.
The Laboratory for Advanced Control Systems and Intelligent Robotics (ACSLab), under the direction of Professor Saleh Mobayen, is a premier research center within YunTech's Graduate School of Intelligent Data Science. The lab serves as a dynamic hub for pioneering research at the intersection of control theory, robotics, artificial intelligence, and embedded systems. Established and led by Professor Mobayen—an internationally recognized researcher and recipient of Taiwan's highest academic honors—the lab is dedicated to developing innovative solutions for complex engineering challenges.
Research Mission
Our mission is to advance the frontiers of intelligent control and autonomous systems through theoretical innovation and practical application. We focus on creating robust, adaptive, and finite-time control strategies that ensure precision, stability, and resilience in real-world systems under uncertainty, disturbances, and cyber-physical threats.
Core Research Areas
- Intelligent Control Systems: Design and implementation of adaptive, robust, nonlinear, and finite-time control algorithms.
- Autonomous Robotics & UAVs: Development of advanced guidance, navigation, and control systems for quadrotors, manipulators, and autonomous vehicles.
- Cyber-Physical System Security: Researching resilient control strategies for smart grids, microgrids, and industrial systems against cyber-attacks and faults.
- AI-Driven Engineering Applications: Leveraging machine learning and AI for system identification, optimization, and control in fields such as biomedical engineering, renewable energy, and power electronics.
- Embedded Systems & Real-Time Implementation: Bridging theory and practice through hardware-in-the-loop simulation and embedded system design for smart agriculture, healthcare, and automation.
- Design Capability: Profound experience in configuring specialized laboratories for control engineering, robotics, and AI research.
Academic Leadership & Impact
Professor Mobayen founded and directs the ACSLab, which also encompasses the Control Engineering Section at YunTech. The lab fosters a high-impact research environment, evidenced by:
- Supervision of 16+ PhD and 53+ MSc students to successful completion.
- Execution of 10+ major research projects with funding exceeding $900K, including grants from Taiwan's National Science and Technology Council (NSTC).
- Production of 380+ high-impact publications (10,800+ citations, H-index: 60) and 4 registered patents.
- Active collaboration with international institutions and industry partners.
A Collaborative & Multicultural Environment
The lab prides itself on being a multicultural and collaborative research environment. We welcome talented graduate students (MSc/PhD), postdoctoral researchers, and visiting scholars who are passionate about contributing to next-generation control technologies and intelligent systems.
1. Advanced Control Theory & Nonlinear Systems
Focus: Development of sophisticated control methodologies for systems with nonlinear dynamics, uncertainties, and external disturbances.
Key Techniques: Sliding Mode Control (SMC), Finite-Time Control, Adaptive Control, Barrier Function-based Control, Terminal Sliding Mode, Backstepping Control, and Prescribed Performance Control.
Applications: Applied to robotic manipulators, aerospace systems, power electronics, and mechanical systems to ensure stability, robustness, and precise tracking under challenging conditions.
2. Intelligent Robotics & Autonomous Systems
Focus: Design and control of autonomous robotic platforms, with emphasis on Unmanned Aerial Vehicles (UAVs/Quadrotors), robotic manipulators, and autonomous ground/air systems.
Key Areas: Trajectory tracking, obstacle avoidance, fault-tolerant control, attitude stabilization, and formation control.
Applications: UAV navigation, space vehicle control, industrial automation, and intelligent transportation systems.
3. Cyber-Physical Systems & Resilient Control
Focus: Ensuring security, resilience, and reliability in integrated computational and physical systems, particularly under cyber-attacks, faults, and communication delays.
Key Areas: Event-triggered control, secure communication, resilient microgrid/smart grid control, detection and mitigation of cyber-threats in real-time systems.
Applications: Smart grids, industrial IoT, critical infrastructure protection, and secure networked control systems.
4. AI & Machine Learning in Control Engineering
Focus: Integration of artificial intelligence, machine learning, and data-driven methods with traditional control systems.
Key Techniques: Reinforcement learning, neural networks, fuzzy logic, T-S fuzzy modeling, AI-based optimization, and adaptive learning control.
Applications: Intelligent fault diagnosis, predictive control, system identification, energy management, biomedical systems (e.g., glucose monitoring), and chaotic system synchronization.
5. Power & Energy Systems Control
Focus: Control and optimization of modern electrical energy systems, including microgrids, renewable energy integration, and power electronic converters.
Key Areas: Frequency and voltage regulation, distributed control of DC/AC microgrids, adaptive energy management, and stabilization under fluctuating loads (e.g., constant power loads).
Applications: Grid-connected and isolated microgrids, wind turbines, photovoltaic systems, and more-electric aircraft power systems.
6. Biomedical & Healthcare Engineering
Focus: Application of control theory and AI to medical devices, health monitoring, and therapeutic systems.
Key Areas: Non-invasive glucose monitoring, ECG signal analysis, arrhythmia detection, rehabilitation robotics, and intelligent alarm systems for healthcare.
Applications: Wearable sensors, medical diagnostics, personalized healthcare systems, and bio-signal encryption.
7. Embedded Systems & Real-Time Implementation
Focus: Development of hardware and software platforms for real-time control, monitoring, and automation.
Key Tools: MATLAB/Simulink, LabVIEW, C/C++, Python, ARM, ATMEGA microcontrollers.
Applications: Smart agriculture, building automation, industrial control systems, embedded AI, and hardware-in-the-loop (HIL) simulations.
Plum Blossom Recognition Award– Taiwan (2024); Research Excellence Award – Taiwan (2023); World's Top 2% Scientist – Stanford University List (2019-2024); Highly-Cited Researcher – Clarivate ESI (2018-Present); Top 1% Global Researcher in Engineering – ESI/ISI (2019-Present); Top 25 Electronics & Electrical Engineering Scientist in Taiwan (2022-Present); Best Researcher Award – Zanjan Province (2019, 2020); IJCAS Contribution Award – ICROS (2019); IEEE Senior Member (2013-Present)
Ph.D. in Control Engineering (2008–2013)
Tarbiat Modares University (QS Rank: 301–350)
– Graduated with 2nd Rank Honors | GPA: 16.88/20
– Thesis: Sliding mode controller design using generalized nonlinear sliding surfaces vs. uncertainties and external disturbances
– Supervisor: Prof. Vahid Johari Majd
M.Sc. in Control Engineering (2006–2008)
University of Tabriz (Best Global Universities Rank: #625)
– Graduated with 1st Class Honors | GPA: 18.57/20
– Thesis: Identification and control of rotary inverted pendulum system using artificial intelligent methods
– Supervisor: Dr. Iraj Hassanzadeh
B.Sc. in Electrical Engineering (2002–2006)
University of Tabriz
– Graduated with 1st Class Honors | GPA: 15.7/20
– Thesis: Design of new ant algorithm for AI-based optimization of continuous variables functions using binary codes
– Supervisor: Dr. M.T. Vakil Baghmisheh