Wireless Networked Control Systems (NCS) are increasingly deployed to monitor and control Cyber-Physical Systems (CPS). To achieve and maintain a desirable level of performance, NCS face significant challenges posed by the scarce wireless resource and network dynamics. In this paper, we consider NCS consisting of multiple physical plant and digital controller pairs communicating over a multi-hop wireless network. The control objective is that the plants follow the reference trajectories provided by the controllers. This paper presents a novel optimization formulation for minimizing the tracking error due to (1) discretization and (2) packet delay and loss. The optimization problem maximizes a utility function that characterizes the relationship between the sampling rate and the capability of disturbance rejection of the control system. The constraints come from the wireless network capacity and the delay requirement of the control system. The solution leads to a joint design of sampling rate adaptation and network scheduling, which can be naturally deployed over existing networking systems which have a layered architecture. Based on a passivity-based control framework, we show that the proposed cross-layer design can achieve both stability and performance optimality. Simulation studies conducted in an integrated simulation environment consisting of Matlab/Simulink and ns-2 demonstrate that our algorithm is able to provide agile and stable sampling rate adaptation and achieve optimal NCS performance.
The systematic design of automotive control applications is a challenging problem due to lack of understanding of the complex and tight interactions that often manifest during the integration of components from the control design phase with the components from software generation and deployment on actual platform/network. In order to address this challenge, we present a systematic methodology and a toolchain using well-defined models to integrate components from various design phases with specific emphasis on restricting the complex interactions that manifest during integration such as timing, deployment, and quantization. We present an experimental platform for the evaluation and testing of the design process. The approach is applied to the development of an adaptive cruise control, and we present experimental results that demonstrate the efficacy of the approach.
Designing cyber-physical systems (CPS) is challenging due to the tight interactions between software, network/platform, and physical components. A co-simulation method is valuable to enable early system evaluation. In this paper, a cosimulation framework that considers interacting CPS components for design of time-triggered (TT) CPS is proposed. Virtual prototyping of CPS is the core of the proposed framework. A network/platform model in SystemC forms the backbone of the virtual prototyping, which bridges control software and physical environment. The network/platform model consists of processing elements abstracted by realtime operating systems, communication systems, sensors, and actuators. The framework is also integrated with a model-based design tool to enable rapid prototyping. The framework is validated by comparing simulation results with the results from a hardware-in-the-loop automotive simulator.
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