Set-Invariance-based Interpretations for the L1 Performance of Nonlinear Systems

This paper is concerend with tackling the L 1 performance analysis problem of continuous and piecewise continuous nonlinear systems with non-unique solutions by using the involved arguments of set-invariance principles. More precisely, this paper derives a sufficient condition for the L 1 performance of continuous nonlinear systems in terms of the invariant set. However, because this sufficient condition intrinsically involves analytical representations of solutions of the differential equations corresponding to the nonlinear systems, this paper also establishes another sufficient condition for the L 1 performance by introducing the so-called extended invariance domain, in which it is not required to directly solving the nonlinear differential equations. These arguments associated with the L 1 performance analysis is further extended to the case of piecewise continuous nonlinear systems, and we obtain parallel results based on the set-invariance principles used for the continuous nonolinear systems. Finally, numerical examples are provided to demonstrate the effectiveness as well as the applicability of the overall results derived in this paper.

A resilient control strategy for networked multi-agent systems subject to covert attacks

In this paper, a resilient distributed control scheme against covert attacks for multi-agent networked systems subject to input and state constraints is developed. The idea consists in a clever deployment of predictive arguments with a twofold aim: detection of malicious agent behaviors affecting the normal system operations and consequent specific control actions implementation to mitigate as much as possible undesirable knock-on effects resulting from adversary actions. Specifically, the multi-agent system is organized in terms of a grid topology and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to recognize the attacked agent. In essence, the resulting solution relies on the combined use of predictive control and set-invariance ideas that are exploited to generate redundant control sequences randomly selected on the actuator side such that the malicious agent is never aware about the effective control action indeed exploited. As a consequence, countermeasures on the sensor-to-controller channel could lead to significantly erroneous data not complying with the expected evolution of the system modeling. Finally, numerical simulations are carried out to show benefits and effectiveness of the proposed approach.