Optimal Control Applications and Methods
Vol 37 (6 Issues in 2016)
Edited by: Mike J. Grimble
Print ISSN: 0143-2087 Online ISSN: 1099-1514
Impact Factor: 0.903
Papers must include an element of optimization or optimal control and estimation theory to be considered by the journal, and all papers will be expected to include significant novel material. The journal only considers papers that mainly use model based control design methods and hence papers featuring fuzzy control will not be included.
Optimal Control Applications and Methods provides a forum for papers on the full range of optimal control and related control design methods. The aim is to encourage new developments in optimal control theory and design methodologies that may lead to advances in real control applications. Papers must include an element of optimization for dynamic systems, or optimal control and estimation theory, and all papers will be expected to include significant novel material. The journal focuses on papers that use model-based control design methods.
Papers are encouraged on the development of computational algorithms for solving optimal control and dynamic optimization problems. The scope includes papers on optimal estimation and filtering methods that have control-related applications. The journal is also a venue for interesting optimal control applications and design studies. Papers on the theory of optimal systems with engineering applications potential will be particularly welcome including papers on areas such as nonlinear, safety-critical, fault-tolerant, and reliable control.
The journal particularly wishes to encourage papers on Predictive Control dealing with theory and also applications. Such papers should be optimization based, and for linear or nonlinear systems. Other design methods covered by the journal include H2 and H∞ design, linear-quadratic optimal control, nonlinear optimal control, stochastic optimal control, periodic optimal control, optimal filtering and fault estimation, optimal adaptive control, multi-criteria and multiple-model optimal control, singular perturbation methods, repetitive control and switching, optimal control of large-scale or distributed systems, time-delay systems, nonlinear programming and optimization methods, dynamic programming, and static and dynamic optimization techniques.
Optimization of dynamic systems, optimal estimation, optimal control, and optimization-based analysis of dynamic systems are within the scope of the journal. A typical paper would normally involve some form of optimization and some form of dynamic system. A paper that applies an optimization-based soft computing technique (e.g., dynamic neural network) could be appropriate if it includes a rigorous theory for the analysis or design of such systems, or is applied to a novel optimal estimation and control problem. However, soft computing papers that involve only minor changes to existing algorithms, or use only static optimization, are not suitable.
There is a strong interest in engineering applications including: automotive systems, aerospace and defence, energy systems (including wind turbines, wave, tidal, battery, fuel cell and solar), marine and, electro-mechanical systems, robotics, power generation and distribution systems, chemical and petrochemical processes, biological and biomedical systems, environmental control, water treatment and distribution, manufacturing and electrical and electronic systems and networks. Applications of interest also include a wide range of interdisciplinary and complex systems problems, where multi-agent solutions, intelligent sensors, and either static or dynamic optimization play a role.