In this paper we discuss the modelling and control of networked control systems (NCS) where sensors, actuators and controllers are distributed and interconnected by a common communication network. Multiple distributed communication delays as well as multiple inputs and multiple outputs (MIMO) are considered in the modelling algorithm. In addition, the asynchronous sampling mechanisms of distributed sensors are characterized to obtain the actual time delays between sensors and the controller. Due to the characteristics of a network architecture, piecewise constant plant inputs are assumed and discrete-time models of plant and controller dynamics are adopted to analyse the stability and performance of a closed-loop NCS. The analysis result is used to verify the stability and performance of an NCS without considering the impact of multiple time delays in the controller design. In addition, the proposed NCS model is used as a foundation for optimal controller design. The proposed control algorithm utilizes the information of delayed signals and improves the control performance of a control system encountering distributed communication delays. Several simulation studies are provided to verify the control performance of the proposed controller design.

This paper discusses the impact of network architecture on control performance in a class of distributed control systems called networked control systems (NCSs) and provides design considerations related to control quality of performance as well as network quality of service. The integrated network-control system changes the characteristics of time delays between application devices. This study first identifies several key components of the time delay through an analysis of network protocols and control dynamics. The analysis of network and control parameters is used to determine an acceptable working range of sampling periods in an NCS. A network-control simulator and an experimental networked machine tool have been developed to help validate and demonstrate the performance analysis results and identify the special performance characteristics in an NCS. These performance characteristics are useful guidelines for choosing the network and control parameters when designing an NCS.

Autonomous parking is one significant autonomous application and will be implemented in daily life in the near future. Due to encountered narrow environments, the issues related to autonomous parking, such as path quality requirements, strict collision avoidance, and motion direction changes, must be overcome properly. Moreover, to be applied in daily driving activities, real‐time planning and human preference should be fulfilled by the designed motion planners. Therefore, an efficient and human‐like motion planning method based on the revised Bidirectional Rapidly‐Exploring Random Tree* (Bi‐RRT*) with Reeds‐Shepp curve is presented. The proposed method results in human‐like paths which have high trajectory quality and consistency for parking scenarios due to the revised Bi‐RRT* framework. Strict collision checking model guarantees the resulting paths to be collision‐free and even leaves safe distance from obstacles and uncertainties. State space adjustment makes the path optimization more efficient and effective. On the other hand, the cost function revision makes the resulting paths meet human driving behavior, such as less backward driving and motion direction changes. In addition, rigorous simulations and analysis demonstrate the effectiveness of the cost function revision and the state space adjustment and illustrate good performance of the proposed approach in common and even complex parking scenarios.

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Autonomous parking techniques can be used to tackle the lacking problem of parking spaces. In this paper, a sampling-based motion planner consisting of optimizing bidirectional rapidly-exploring random trees* (Bi-RRT*) and parking-oriented model predictive control (MPC) is proposed to properly deal with various parking scenarios. The optimal Bi-RRT* approach aims to improve the common defects of traditional sampling-based motion planners, such as uncertainties of path quality and consistency, and exploring inefficiency in narrow spaces. For this reason, the proposed motion planner is able to overcome strict environments with obstacles and narrow spaces. The parking-oriented MPC is then designed for steering and speed controls simultaneously for accurately and smoothly tracking parking paths. Furthermore, the proposed controller is dedicated to work under the practical scenarios, such as vehicle considerations, realtime control, and signal delay. To verify the effects of the proposed autonomous parking system, extensive simulations and experiments are conducted in common and strict parking scenarios, such as perpendicular parking, parallel parking. The simulation results not only verify the effects of each technical element, but also show the capability to deal with the various parking scenarios. Furthermore, various on-car experiments sufficiently demonstrate that the proposed system can be actually implemented in everyday life. INDEX TERMS Autonomous parking system, sampling-based motion planning, parking-oriented vehicle control, bidirectional rapidly-exploring random trees* (Bi-RRT*), model predictive control (MPC), perpendicular parking, parallel parking.

In a video-based surveillance system, a mobile camera can provide dynamical and wider monitoring range and the video data transmitted from cooperative mobile cameras can be used to actively detect the objects of interest. However, it is a difficult task to accurately detect the moving objects from the image frames captured by the mobile cameras and the data flow of surveillance video from multiple cameras could be huge. The camera motion usually causes the shifting of static background as well as the moving objects in the captured image frames. In order to correctly estimate the motion of moving objects, a voting-based motion estimation algorithm is proposed to process the image frames captured by the mobile camera. Based on the estimation, a content-based video transmission mechanism is then implemented to further effectively decrease encoding cost and bandwidth utilization. The overall approach consists of voting-based motion estimation, moving object edges detection and content-based sampling coding at temporal and spatial scales. Without knowing the prior knowledge of camera motion, the motion estimation algorithm only utilizes the shifting information of edges of static background to estimate the camera movement. The shifting information is determined based on the voting decision of several representative regions of interest and the estimated motion is then used to compensate for the visual content obtained from the captured image frames. The proposed algorithms have been experimentally tested on several practical scenarios and it is demonstrated that, under limited network bandwidth, the transmitted image quality can be progressively achieved and the transmission bandwidth utilization can be effectively decreased.

Because of ihe advanced development in computer iechnoloD, home auiomation system could provide a variety of convenient and novel services to people. But only providing many kinds of services is not enough; instead, upgrading the quality of services is also a v e y important issue. One way to upgrade the service quality is to cusiomize the service according io the inhabitant 5 personal situaiion, and ihe user location is the key information for ihe home automaiion system to customize the services. Anoiher impaci of the advanced compuier technology is to make the personal digital device to commonly have the capability to communicate through ihe wireless networks, and the popularity of wireless networks in home has increased in receni years. As a resuli, home automation system can bring services io personal digital devices held by people through any wireless network, and customize the services according to the location of personal digiial device in home. In this paper: we preseni a location determination sysiem for the home automation system io provide locaiion aware services. This location determination system uses support vector machine to cIassi3 the location of a wireless clientfrom its signal strength measures, and we will describe iis architecture and discuss iis performance.

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