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Lukas Kölsch

Publications and source records attributed to Lukas Kölsch.

24 records · Page 2Linked to original sources

On the inverses of Kasami and Bracken-Leander exponents

We explicitly determine the binary representation of the inverse of all Kasami exponents $K_r=2^{2r}-2^r+1$ modulo $2^n-1$ for all possible values of $n$ and $r$. This includes as an important special case the APN Kasami exponents with $\gcd(r,n)=1$. As a corollary, we determine the algebraic degree of the inverses of the Kasami functions. In particular, we show that the inverse of an APN Kasami function on $\mathbb{F}_{2^n}$ always has algebraic degree $\frac{n+1}{2}$ if $n\equiv 0 \pmod 3$. For $n\not\equiv 0 \pmod 3$ we prove that the algebraic degree is bounded from below by $\frac{n}{3}$. We consider Kasami exponents whose inverses are quadratic exponents or Kasami exponents. We also determine the binary representation of the inverse of the Bracken-Leander exponent $BL_r=2^{2r}+2^r+1$ modulo $2^n-1$ where $n=4r$ and $r$ odd. We show that the algebraic degree of the inverse of the Bracken-Leander function is $\frac{n+2}{2}$.

math.CO↗

Optimal Control of Port-Hamiltonian Systems: A Time-Continuous Learning Approach

Feedback controllers for port-Hamiltonian systems reveal an intrinsic inverse optimality property since each passivating state feedback controller is optimal with respect to some specific performance index. Due to the nonlinear port-Hamiltonian system structure, however, explicit (forward) methods for optimal control of port-Hamiltonian systems require the generally intractable analytical solution of the Hamilton-Jacobi-Bellman equation. Adaptive dynamic programming methods provide a means to circumvent this issue. However, the few existing approaches for port-Hamiltonian systems hinge on very specific sub-classes of either performance indices or system dynamics or require the intransparent guessing of stabilizing initial weights. In this paper, we contribute towards closing this largely unexplored research area by proposing a time-continuous adaptive feedback controller for the optimal control of general time-continuous input-state-output port-Hamiltonian systems with respect to general Lagrangian performance indices. Its control law implements an online learning procedure which uses the Hamiltonian of the system as an initial value function candidate. The time-continuous learning of the value function is achieved by means of a certain Lagrange multiplier that allows to evaluate the optimality of the current solution. In particular, constructive conditions for stabilizing initial weights are stated and asymptotic stability of the closed-loop equilibrium is proven. Our work is concluded by simulations for exemplary linear and nonlinear optimization problems which demonstrate asymptotic convergence of the controllers resulting from the proposed online adaptation procedure.

math.OC↗

Distributed Frequency and Voltage Control for AC Microgrids based on Primal-Dual Gradient Dynamics

With the gradual transformation of power generation towards renewables, distributed energy resources are becoming more and more relevant for grid stabilization. In order to involve all participants in the joint solution of this challenging task, we propose a distributed, model-based and unifying controller for frequency and voltage regulation in AC microgrids, based on steady-state optimal control. It not only unifies frequency and voltage control, but also incorporates the classic hierarchy of primary, secondary and tertiary control layers with each closed-loop equilibrium being a minimizer of a user-defined cost function. By considering the individual voltage limits as additional constraints in the corresponding optimization problem, no superordinate specification of voltage setpoints is required. Since the dynamic model of the microgrid has a port-Hamiltonian structure, stability of the overall system can be assessed using shifted passivity properties. Furthermore, we demonstrate the effectiveness of the controller and its robustness against fluctuations in active and reactive power demand by means of numerical examples.

math.OC↗

Distributed Frequency Regulation for Heterogeneous Microgrids via Steady State Optimal Control

In this paper, we present a model-based frequency controller for microgrids with nonzero line resistances based on a port-Hamiltonian formulation of the microgrid model and real-time dynamic pricing. The controller is applicable for conventional generation with synchronous machines as well as for power electronics interfaced sources and it is robust against power fluctuations from uncontrollable loads or volatile regenerative sources. The price-based formulation allows additional requirements such as active power sharing to be met. The capability and effectiveness of our procedure is demonstrated by means of an 18-node exemplary grid.

eess.SY↗

Steady-State Optimal Frequency Control for Lossy Power Grids with Distributed Communication

We present a distributed and price-based control approach for frequency regulation in power grids with nonzero line conductances. Both grid and controller are modeled as a port-Hamiltonian system, where the grid model consists of differential as well as algebraic equations. Simulations show that the resulting controller asymptotically stabilizes the frequency while maintaining minimum overall generation costs in steady state and being robust in terms of clock drifts and uncontrollable loads. Moreover, it is shown that active power sharing can be achieved by an appropriate choice of the cost function.

eess.SY↗

On the Differential-Linear Connectivity Table of Vectorial Boolean Functions

Vectorial Boolean functions are crucial building-blocks in symmetric ciphers. Different known attacks on block ciphers have resulted in diverse cryptographic criteria for vectorial Boolean functions, such as differential uniformity and nonlinearity. Very recently, Bar-On et al. introduced at Eurocrypt'19 a new tool, called the differential-linear connectivity table (DLCT), which allows for taking into account the dependency between the two subciphers $E_0$ and $E_1$ involved in differential-linear attacks. This new notion leads to significant improvements of differential-linear attacks on several ciphers. This paper presents a theoretical characterization of the DLCT of vectorial Boolean functions and also investigates this new criterion for some families of functions with specific forms. More precisely, we firstly reveal the connection between the DLCT and the autocorrelation of vectorial Boolean functions, we characterize properties of the DLCT by means of the Walsh transform of the function and of its differential distribution table, and we present generic bounds on the highest magnitude occurring in the DLCT of vectorial Boolean functions, which coincides (up to a factor~\(2\)) with the well-established notion of absolute indicator. Next, we investigate the invariance property of the DLCT of vectorial Boolean functions under the affine, extended-affine, and Carlet-Charpin-Zinoviev (CCZ) equivalence and exhaust the DLCT spectra of optimal $4$-bit S-boxes under affine equivalence. Furthermore, we study the DLCT of APN, plateaued and AB functions and establish its connection with other cryptographic criteria. Finally, we investigate the DLCT and the absolute indicator of some specific polynomials with optimal or low differential uniformity, including monomials, cubic functions, quadratic functions and inverses of quadratic permutations.

cs.IT↗