Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

Providing QoS for networked peers in distributed haptic virtual environments

Haptic information originates from a different human sense (touch), therefore the quality of service (QoS) required to supporthaptic traffic is significantly different from that used to support conventional real-time traffic such as voice or video. Each type ofnetwork impairment has different (and severe) impacts on the user’s haptic experience. There has been no specific provision of QoSparameters for haptic interaction. Previous research into distributed haptic virtual environments (DHVEs) have concentrated onsynchronization of positions (haptic device or virtual objects), and are based on client-server architectures.We present a new peerto-peer DHVE architecture that further extends this to enable force interactions between two users whereby force data are sent tothe remote peer in addition to positional information. The work presented involves both simulation and practical experimentationwhere multimodal data is transmitted over a QoS-enabled IP network. Both forms of experiment produce consistent results whichshow that the use of specific QoS classes for haptic traffic will reduce network delay and jitter, leading to improvements in users’haptic experiences with these types of applications.