Advanced Control Systems and Optimization Techniques

Dear Colleagues,

The last decade has seen a serious step forward regarding the complexity of various technical and non-technical processes and in high demand dynamic and steady-state performance, including the robustness of control systems. Advanced control systems that include intelligent control, adaptive control, data-driven and learning control, have been successfully applied to cope with the uncertainties and disturbances of many processes. The optimization algorithms play an important role in this context, as they give, in the case of correct formulations, solutions to rather complicated problems in order to systematically meet the performance specifications of control systems.

The dynamic environments are usually changing and control systems should adapt themselves accordingly. Therefore, by employing intelligent approaches (dealing, for example, with fuzzy systems, neural networks and nature-inspired optimization), advanced control systems have been developed. With this regard, more efforts should be focused on the methodology of the learning systems. However, the advantage of advanced analysis tools should be embedded to improve the control system performance.

Nowadays, process control applications are developed under the conditions of optimal performance requirements. However, there is generally no dynamical model available of the process, or the process model is too complex to be used in controller design. Since modeling and system identification tools can be expensive and time-consuming, and models may be time-varying, or nonlinear, or contain delays, data-driven control has been proposed, with the aim to avoid the use of process models in controller tuning and to efficiently use the information in large amounts of process input–output data to design predictors, controllers, and monitoring systems that guarantee the required control system performance.

The main objective of this Special Issue is to create a platform for scientists, engineers and practitioners, to share their latest theoretical and technological results and to discuss several issues for the research directions in the field of advanced control systems and optimization. The papers to be published in this Special Issue are expected to provide recent results in advanced modeling and controller design and tuning techniques especially for cross-fertilizations between the fields of advanced control systems and optimization. Papers containing experimental results regarding advanced control systems and optimization are especially welcome.

Prof. Dr. Radu-Emil Precup
Prof. Dr. Sašo Blažič
Guest Editors

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