Advances in the Control of Complex Dynamic Systems

Dear Colleagues,

This Special Issue addresses ongoing research and development in the field of control systems engineering, focusing on the modeling, identification, and control of systems with complex dynamics, distinct nonlinearities, and interacting components. Techniques used in this area include model-based control, adaptive control, optimal control, and robust control. The goal is to develop control systems that can effectively manage the complexity and uncertainty inherent in these systems, resulting in improved performance and stability.

A very important aspect is the modeling and identification of the complex processes involved. Significant nonlinearities can be observed in many real-world processes. For example, a well-established approach for dealing with nonlinearities is fuzzy logic. Fuzzy models represent efficient universal approximators of nonlinear dynamics since they can be used to approximate any continuous nonlinear function with arbitrary accuracy. Many processes exhibit both continuous and discrete dynamical properties. Such hybrid systems are dynamic systems that can contain both continuous and discrete states or inputs, and often, the continuous and discrete dynamics are inextricably intertwined. For the most complex processes, modern evolving approaches seem to give good results.

Model predictive control is a family of control methods in which a model of the system is used to predict the future behavior of the system given certain inputs. The optimal inputs that are finally applied to the real system are usually determined by various optimization techniques. Various intelligent methods and algorithms can be implemented to improve the stability and performance of the closed loop system.

Topics of interest include but are not limited to:

• Complex process modeling;
• Identification;
• Fuzzy systems;
• Hybrid systems;
• Evolving systems;
• Interval systems;
• Model predictive control;
• Robust control;
• Optimization algorithms;
• Intelligent methods.

Dr. Gorazd Karer
Guest Editor

Manuscript Submission Information

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