The NCS (networked control system) is different from the conventional control systems which is the integration of the automation and control over communication network. When an NCS operates over the communication network, one of the major challenges is the network-induced delay in data transfer among the controllers, actuators, and sensors. This delay degrades system performance and causes system unstablility. This paper proposes a GPC (generalized predictive control) with the Kalman state estimator to compensate for the network-induced delay and packet loss. The GPC is implemented in WiNCS (Wireless NCS) based on IEEE 802.11 standard. An analytical NCS model and NS2 (network simulator version 2) are developed to simulate and evaluate the performance under the effect of various delays and packet loss rates. The result shows that the proposed GPC is adaptive and robust to the uncertainties in a time-delay system. The WiNCS is evaluated with latency and throughput measurements in various environments. The experiment setup conforming to the IEEE 802.11 standard achieves an average latency of 1.3 ms and a data throughput of 3.000 kB/s up to a distance of 70 m. The results demonstrate the feasibility of real-time closed-loop control with the proposed concept.

No abstract

Over past few decades, the society has seen the stunning transformation of low birth rate and dual-earner households. As a result more and more robots are design for helping people at home. However, most of them are design for specific tasks. This paper proposed an intelligence service robot aim to cope with wide range application in home. To let the robot move freely in home environment and reach one desired target position, two fuzzy logic control systems are proposed as autonomous navigation and obstacle avoidance. The distance information is proved by sonar sensor as the input of our fuzzy systems and the local navigation uses fuzzy logic to control the robot's behavior. The results show the intelligence service robot is adaptive to different environment. The experimental results shows the system can effectively travelled under the effect of time delays over the network and sensor uncertainties

The autonomous navigation of the mobile robot in an unknown, unstructured and dynamic environment is one challenging problem. An intelligent behavior control system based on fuzzy logic algorithm is proposed for an autonomous mobile robot to traverse through various terrains as slope, maze, and dynamic obstacle and dock station. A hierarchical structure consists of the main high-level navigation controller and a remote low-level closed-loop system is developed. The uncertainties in robot system are evaluated and it confirms the mathematical model base control strategy may need huge computation to deal with this issue. The proposed system is robust to the uncertainties and only uses sensors on the robot. The experiment results show the mobile robot can effectively and efficiently complete the trajectory autonomously avoiding obstacles in motion or stationary. The robot generates smooth and collision free trajectory without prior knowledge of the environment. The result demonstrates the system is robust to the uncertainties in the sensory readings