Cyber-Physical-Human (CPH) Systems present a particular class of safety-critical applications, where the interaction between the dynamics of the system and the cyber elements of its operation can be influenced by the human operator and the interaction between these three elements needs to be regulated for various objectives. CPH systems consist of three main components: physical elements modeling the systems to be controlled, cyber elements representing the communication links and software, and human operators who partially monitor the operation of the system and can interfere on as needed basis. Our research in CPH systems aims at development of robust, fault-tolerant architectures that would ensure predictable operation of the system with the given hardware constraints, despite the uncertainties in physical processes,  and cyber and human faults.
 
1. Control and Scheduling Co-design
In networked control systems (NCSs), the feedback loops are closed by real-time communication networks.  On one hand, the introduction of networking can be advantageous in terms of lower system costs due to streamlined installation and maintenance costs.  On the other hand, however, networking can introduce significant challenges for control of these systems with desired specifications. Communication, especially wireless communication, takes place in a discrete-time manner.  Because of the limited channel capacity, the data transmission has to be scheduled in an appropriate manner for proper operation of the control system.  Otherwise, the quality of service cannot be guaranteed, which may degrade the system performance or even render the system unstable. Similar challenges appear in computer-controlled systems.  To address these issues, our research focuses on systematic co-design approaches of both feedback control and network/computation scheduling.Our preliminary results in this direction present scheduling algorithms for real-time implementation of L1 adaptive controller. Event-triggering schedules the data transmission dependent upon errors exceeding certain threshold. We show that with the proposed event-triggering schemes the states and the input in the networked system can be arbitrarily close to those of a stable reference system by increasing the sampling frequency and the transmission frequency. Stability conditions, in terms of event threshold and allowable transmission delays, are also derived, which serve as the guidance in real-time scheduling. The performance bounds are quantified in terms of hardware constraints.
 
2. Fault tolerance in CPH Systems
Faults in CPH systems could be due to violation of assumptions in the physical and cyber elements, as well as due to human errors. Physical faults refer to the unpredictable factors/accidents that have severe impact on the physical components in the system, thus violating the main assumptions used in the modeling and control analysis. Cyber faults mainly refer to all errors in the computer and/communication systems, such as CPU overflow, communication jam, software errors, and mistakes in decision-making algorithms. Human faults are the mistakes made by the human operator. These different types of faults can appear jointly, sequentially or separately, creating catastrophic or hazardous conditions for the operation of the system. We are particularly concerned with understanding of pilot models and design of architectures, which can provide accurate situation awareness on distributing the actions between the human operator and the automation.
 
References:

  1. Wang, X., Kharisov, E. and Hovakimyan, N., “Real-Time L1 Adaptive Control Algorithm in Uncertain Networked Control Systems,” submitted to IEEE Transactions on Automatic Control, 2011. [pdf]
  2. Wang, X., Sun, Y. and Hovakimyan, N., “Asynchronous Task Execution in Decentralized Event‐Triggered Networked Control Systems,” submitted to System & Control Letters. [pdf]
  3. Wang, X. and Hovakimyan, N., “A Decoupled Design in Distributed Control of Uncertain Networked Control Systems,” submitted to American Control Conference, 2012. [pdf]
  4. Wang, X., Sun, H., Hovakimyan, N. and Başar, T., “Bounds on Transmission Rates and Performance in Quantized Network Systems,” in IFAC World Congress, 2011. [pdf]
  5. Wang, X. and Hovakimyan, N., “L1 Adaptive Control of Event‐Triggered Networked Systems,” in American Control Conference, 2010. [pdf]

 
Contact:

Xiaofeng Wang
Naira Hovakimyan
wangx (at) illinois (dot) edu
nhovakim (at) illinois (dot) edu

To read more about the NSF and their funding of this project, click here.