Advanced Motion Control and Planning Techniques of Complex Mechatronic Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 5046
Special Issue Editors
Interests: nonlinear control theory and applications; hydraulic systems; robotics; adaptive control; state and disturbance observer; nonlinear compensation control
Interests: hydraulic systems; nonlinear control; prescribed performance control
Special Issue Information
Dear colleagues,
With the development of modern industrial and military technology, the motion control of complex mechatronic systems in terms of accuracy, response, and robustness is requiring much higher performance. Over the past few decades, plenty of researchers have been committed to exploring advanced control methods for complex mechatronic systems and have laid a good foundation. Typical techniques include adaptive control, robust control, state and disturbance observation, model predictive control, intelligent control, and so on. In addition, motion planning techniques are widely employed in many practical complex mechatronic systems such as robots, autonomous vehicles, and unmanned aerial vehicles.
This Special Issue is committed to compiling recent research about advanced motion control and the planning of complex mechatronic systems. Manuscripts should contain both theoretical and simulation/experimental results and will be subject to Electronics' normal review procedures. The topics of interest within the scope of this Special Issue include (but are not limited to) the following:
- Nonlinear control methodologies for complex mechatronic systems including adaptive control, robust control, state and disturbance observer-based control, and other nonlinear control methods;
- Data-driven control;
- Reinforcement learning;
- Fault diagnosis and fault-tolerant control;
- Motion planning algorithms;
- Design and analysis of complex mechatronic systems;
- Modeling and system identification of complex mechatronic systems;
- Trajectory optimization.
Dr. Wenxiang Deng
Dr. Zhangbao Xu
Dr. Yaoyao Wang
Guest Editors
Manuscript Submission Information
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Keywords
- nonlinear control methodologies
- data-driven control
- reinforcement learning
- fault diagnosis and fault-tolerant control
- motion planning algorithms
- design and analysis of complex mechatronic systems
- modeling and system identification of complex mechatronic systems
- trajectory optimization
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