Simple frequency-dependent tools for control system analysis, structure selection and design: thr
Automatica (Journal of IFAC)
The role of the condition number and the relative gain array in robustness analysis
Automatica (Journal of IFAC)
Screening tools for robust control structure selection
Automatica (Journal of IFAC)
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Automatica (Journal of IFAC)
A priori hyperreduction method: an adaptive approach
Journal of Computational Physics
D-optimal design of a monitoring network for parameter estimation of distributed systems
Journal of Global Optimization
Optimal control of switched distributed parameter systems with spatially scheduled actuators
Automatica (Journal of IFAC)
Optimal Training Sequences for Locally Recurrent Neural Networks
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Configuring A Sensor Network for Fault Detection in Distributed Parameter Systems
International Journal of Applied Mathematics and Computer Science - Issues in Fault Diagnosis and Fault Tolerant Control
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Sensor network design for the estimation of spatially distributed processes
International Journal of Applied Mathematics and Computer Science
Sensor location and classification for disturbance rejection by measurement feedback
Automatica (Journal of IFAC)
A new actuator activation policy for performance enhancement of controlled diffusion processes
Automatica (Journal of IFAC)
Quantification of interaction in multiloop control systems using directed spectral decomposition
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Hi-index | 22.16 |
Control system design involves input/output (IO) selection, that is, decisions on the number, the place, and the type of actuators and sensors. The choice of inputs and outputs affects the performance, complexity, and costs of the control system. Due to the combinatorial nature of the selection problem, systematic methods are needed to complement one's intuition, experience, and physical insight. This paper reviews the currently known IO selection methods, which aids the control engineer in picking a suitable method for the problem at hand. The methods are grouped according to the control system property that is addressed and applications are grouped according to the considered control systems. A set of criteria is proposed that a good IO selection method should possess. It is used to assess and compare the methods and it could be used as a guideline for new methods. The state of the art in IO selection is sketched and directions for further research are mentioned.