Biblio
Cyber-Physical Systems (CPSs), a class of complex intelligent systems, are considered the backbone of Industry 4.0. They aim to achieve large-scale, networked control of dynamical systems and processes such as electricity and gas distribution networks and deliver pervasive information services by combining state-of-the-art computing, communication, and control technologies. However, CPSs are often highly nonlinear and uncertain, and their intrinsic reliance on open communication platforms increases their vulnerability to security threats, which entails additional challenges to conventional control design approaches. Indeed, sensor measurements and control command signals, whose integrity plays a critical role in correct controller design, may be interrupted or falsely modified when broadcasted on wireless communication channels due to cyber attacks. This can have a catastrophic impact on CPS performance. In this paper, we first conduct a thorough analysis of recently developed secure and resilient control approaches leveraging the solid foundations of adaptive control theory to achieve security and resilience in networked CPSs against sensor and actuator attacks. Then, we discuss the limitations of current adaptive control strategies and present several future research directions in this field.
Cyber-physical systems are vulnerable to attacks that can cause them to reach undesirable states. This paper provides a theoretical solution for increasing the resiliency of control systems through the use of a high-authority supervisor that monitors and regulates control signals sent to the actuator. The supervisor aims to determine the control signal limits that provide maximum freedom of operation while protecting the system. For this work, a cyber attack is assumed to overwrite the signal to the actuator with Gaussian noise. This assumption permits the propagation of a state covariance matrix through time. Projecting the state covariance matrix on the state space reveals a confidence ellipse that approximates the reachable set. The standard deviation is found so that the confidence ellipse is tangential to the danger area in the state space. The process is applied to ship dynamics where an ellipse in the state space is transformed to an arc in the plane of motion. The technique is validated through the simulation of a ship traveling through a narrow channel while under the influence of a cyber attack.