Design of Neural Network Quantizers for Networked Control Systems

Neural-Smith Predictor Method for Improvement of Networked Control Systems

Networked control systems (NCSs) are distributed control systems in which the nodes, including controllers, sensors, actuators, and plants are connected by a digital communication network such as the Internet. One of the most critical challenges in networked control systems is the stochastic time delay of arriving data packets in the communication network among the nodes. Using the Smith predic...

Decentralized H_infty Quantizers Design for Networked Complex Composite Systems

The objective of the paper is to propose an approach to decentralized networked quantized state feedback H∞ controller design for a class of complex symmetric composite continuous-time systems. The effect of data-packet dropouts and communication delays between the plant and the local controller as well as quantizers design are included in the design of asymptotically stabilizing controller and...

Min-Max Design of Feedback Quantizers for Netorwked Control Systems

In a networked control system, quantization is inevitable to transmit control and measurement signals. While uniform quantizers are often used in practical systems, the overloading, which is due to the limitation on the number of bits in the quantizer, may significantly degrade the control performance. In this paper, we design an overloading-free feedback quantizer based on a ∆Σ modulator, comp...

Network Protocols for Networked Control Systems

Optimal Controller Design for Networked Control Systems

This paper addresses the problem of optimal control system design for networked control systems. We focus on a situation where the plant is single-input single-output and the communication link between the controller and the plant is signal-to-noise ratio constrained. In this setting, we characterize the controllers that minimize the tracking error variance, while respecting the channel signal-...