Model predictive control: theory and practice—a survey
Automatica (Journal of IFAC)
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Annals of Operations Research - Special issue on Tabu search
Design of a fuzzy-logic based diagnostic model for technical processes
Fuzzy Sets and Systems
Large-scale systems: modeling, control, and fuzzy logic
Large-scale systems: modeling, control, and fuzzy logic
An NN-based approach for tuning servocontrollers
Neural Networks
Lamarckian Evolution, The Baldwin Effect and Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
Empirical investigation of the benefits of partial lamarckianism
Evolutionary Computation
Constraint-based agents: an architecture for constraint-based modeling and local-search-based reasoning for planning and scheduling in open and dynamic worlds
A multi-objective genetic local search algorithm and itsapplication to flowshop scheduling
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A heuristic genetic algorithm for subcontractor selection in a global manufacturing environment
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Fusion of soft computing and hard computing in industrial applications: an overview
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
The hierarchical expert tuning of PID controllers using tools ofsoft computing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Theoretical proof of edge search strategy applied to power plantstart-up scheduling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An introduction to simulated evolutionary optimization
IEEE Transactions on Neural Networks
A novel approach for ANFIS modelling based on full factorial design
Applied Soft Computing
Soft computing in engineering design - A review
Advanced Engineering Informatics
Hi-index | 0.00 |
The design of control systems for large-scale and complex industrial plants involves numerous trade-off problems, such as costs, quality, environmental impact, safety, reliability, accuracy, and robustness. Some of these parameters are even conflicting. Thus, the use of a multidiscipline approach is suggested to satisfy these requirements in an acceptable and well-balanced manner, and a fusion of soft computing and hard computing appears to be a natural and practical choice. Although the state-of-the-art soft computing technology has distinguished features, the use of soft computing technology would be ineffective, and may be doomed to fail, if it is improperly fused with conventional hard computing technology and control processes. Proper fusion is key to success, and a general model of fusion is worth examining. In this paper, through a survey of published literature, a general model of fusion is shown at the system level as well as at the algorithm level. In the system level, soft computing is applied to the upper level in a hierarchical control system, performing human-like tasks, such as forecasting and scheduling, or applied to ill-defined process models for carrying out intelligent control. Hard computing is used at the middle or lower control level for well-defined process models, carrying out coordinate control tasks while maintaining a high level of accurate and safety control. In the case of fusion at the algorithm level, this paper will discuss several types of tasks, such as scheduling and control.