Optimal Attack against Cyber-Physical Control Systems with Reactive Attack Mitigation

This paper studies the performance and resilience of a cyber-physical control system (CPCS) with attack detection and reactive attack mitigation. It addresses the problem of deriving an optimal sequence of false data injection attacks that maximizes the state estimation error of the system. The results provide basic understanding about the limit of the attack impact. The design of the optimal attack is based on a Markov decision process (MDP) formulation, which is solved efficiently using the value iteration method. Using the proposed framework, we quantify the effect of false positives and mis-detections on the system performance, which can help the joint design of the attack detection and mitigation. To demonstrate the use of the proposed framework in a real-world CPCS, we consider the voltage control system of power grids, and run extensive simulations using PowerWorld, a high-fidelity power system simulator, to validate our analysis. The results show that by carefully designing the attack sequence using our proposed approach, the attacker can cause a large deviation of the bus voltages from the desired setpoint. Further, the results verify the optimality of the derived attack sequence and show that, to cause maximum impact, the attacker must carefully craft his attack to strike a balance between the attack magnitude and stealthiness, due to the simultaneous presence of attack detection and mitigation

Energy-aware MPC co-design for DC-DC converters

In this paper, we propose an integrated controller design methodology for the implementation of an energy-aware explicit model predictive control (MPC) algorithms, illustrat- ing the method on a DC-DC converter model. The power consumption of control algorithms is becoming increasingly important for low-power embedded systems, especially where complex digital control techniques, like MPC, are used. For DC-DC converters, digital control provides better regulation, but also higher energy consumption compared to standard analog methods. To overcome the limitation in energy efficiency, instead of addressing the problem by implementing sub-optimal MPC schemes, the closed-loop performance and the control algorithm power consumption are minimized in a joint cost function, allowing us to keep the controller power efficiency closer to an analog approach while maintaining closed-loop op- timality. A case study for an implementation in reconfigurable hardware shows how a designer can optimally trade closed-loop performance with hardware implementation performance

PVT-Robust CMOS Programmable Chaotic Oscillator: Synchronization of Two 7-Scroll Attractors

Designing chaotic oscillators using complementary metal-oxide-semiconductor (CMOS) integrated circuit technology for generating multi-scroll attractors has been a challenge. That way, we introduce a current-mode piecewise-linear (PWL) function based on CMOS cells that allow programmable generation of 2–7-scroll chaotic attractors. The mathematical model of the chaotic oscillator designed herein has four coefficients and a PWL function, which can be varied to provide a high value of the maximum Lyapunov exponent. The coefficients are implemented electronically by designing operational transconductance amplifiers that allow programmability of their transconductances. Design simulations of the chaotic oscillator are provided for the 0.35μ m CMOS technology. Post-layout and process–voltage–temperature (PVT) variation simulations demonstrate robustness of the multi-scroll chaotic attractors. Finally, we highlight the synchronization of two seven-scroll attractors in a master–slave topology by generalized Hamiltonian forms and observer approach. Simulation results show that the synchronized CMOS chaotic oscillators are robust to PVT variations and are suitable for chaotic secure communication applications.Universidad Autónoma de Tlaxcala CACyPI-UATx-2017Program to Strengthen Quality in Educational Institutions C/PFCE-2016-29MSU0013Y-07-23National Council for Science and Technology 237991 22284

Adaptive design of delta sigma modulators

In this thesis, a genetic algorithm based on differential evolution (DE) is used to generate delta sigma modulator (DSM) noise transfer functions (NTFs). These NTFs outperform those generated by an iterative approach described by Schreier and implemented in the delsig Matlab toolbox. Several lowpass and bandpass DSMs, as well as DSM\u27s designed specifically for and very low intermediate frequency (VLIF) receivers are designed using the algorithm developed in this thesis and compared to designs made using the delsig toolbox. The NTFs designed using the DE algorithm always have a higher dynamic range and signal to noise ratio than those designed using the delsig toolbox