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TD-CD-MPPI: Temporal-Difference Constraint-Discounted Model Predictive Path Integral Control
No full textInternational audiencePath Integral methods have demonstrated remarkable capabilities for solving non-linear stochastic optimal control problems through sampling-based optimization. However, their computational complexity grows linearly with the prediction horizon, limiting long-term reasoning, while constraints are merely enforced through handcrafted penalties.In this work, we propose a unified and efficient framework for enabling long-horizon reasoning and constraint enforcement within Model Predictive Path Integral (MPPI) control. First, we introduce a practical method to incorporate a terminal value function, learned offline via temporal-difference learning, to approximate the long-term cost-to-go. This allows for significantly shorter roll-outs while enabling infinite-horizon reasoning, thereby improving computational efficiency and motion performance. Second, we propose a discount modulation strategy that adjusts the return of sampled trajectories based on constraint violations. This provides a more interpretable and effective mechanism for enforcing constraints compared to traditional cost shaping. Our formulation retains the flexibility and sampling efficiency of MPPI while supporting structured integration of long-term objectives and constraint handling. We validate our approach on both simulated and real-world robotic locomotion tasks, demonstrating improved performance, constraint-awareness, and generalization under reduced computational budgets
Challenges of operating multiple distributed generators with different primary control strategies in microgrids: Interactions and performance assessment
No full textInternational audienceThis study investigates the effectiveness of hybrid power-sharing control strategies in microgrid systems. It integrates various droop controllers, including conventional droop, universal droop, dVOC, and VSG. The contribution of each controller is evaluated in terms of system stability, efficiency, and adaptability. These assessments consider how different test conditions influence overall system performance. The performance analysis focuses on power sharing during both transient and steady-state conditions. It accounts for DERs connected through complex transmission line impedances and subjected to variable local loads. The study concludes with extensive real-time simulations using the Typhoon HIL 604 platform. These scenarios test different operating conditions to identify the most stable microgrid configuration
Existence of monostable fronts for a KPP infinite-difference numerical scheme
No full textInternational audienceWe study the existence of traveling wave solutions for a numerical counterpart of the KPP equation. We obtain the existence of monostable fronts for all super-critical speeds in the regime where the spatial step size is small. The key strategy is to transfer the invertibility of certain linear operators related to the front solutions from the continuous setting to the discrete case we are interested in. We rely on resolvent bounds which are uniform with respect to the step size, a procedure which is also known as spectral convergence. The approach is also able to handle infinite range discretizations with geometrically decaying coefficients that are allowed to have both signs, which prevents the use of the comparison principle
Aerobic autotrophic isopropanol production under low H2 atmosphere in Hollow Fiber Membrane Bioreactor
No full textInternational audienceOne of the challenges of aerobic gas fermentation for the production of biomolecules is to control the gas environment in order to operate outside the explosive zone, i.e., with low O-2 (< 6%) and/or H-2 (< 4%) contents. In this study, a bioreactor was to a hollow fiber membrane contactor to supply hydrogen to the microbial suspension. This technology allows the transfer of H-2 directly in soluble form into the culture medium without generating bubbles, responsible for the enrichment of the gas mixture with hydrogen by bursting in the gas headspace. Coupling a Hollow Fiber Membrane Contactor to the gas bioreactor in C. necator cultures resulted in either 10 g/L of biomass or 1.3 g/L of isopropanol, while minimizing the H-2 content in the gas headspace to a level very close to, or even below, the safety threshold of 4 mol% H-2. Isopropanol production performance was compared with that obtained in a gas reactor without HFMC (6.8 g/L of isopropanol). Although the production performance was lower, the coupling still achieved it under low H-2 atmosphere, providing proof of concept that it is possible to perform aerobic autotrophic process under low hydrogen atmosphere, thus allowing the exit from the explosive zone regardless of the oxygen content of the reactor. This advancement should help make aerobic gas fermentation much safer and extend these processes on a larger scale
Carleman-Based Reconstruction Algorithm on a wave Network
No full textInternational audienceIn the context of a network of vibrating strings, modelled by interconnected linear partial differential equations, we are interested in the reconstruction of a zeroth order term of each one-dimensional wave equation involved, using some appropriate external boundary measurements. More precisely, we are interested in an inverse problem set on a tree shaped network where each edge behaves according to the wave equation with potential, external nodes have Dirichlet boundary conditions and internal nodes follow the Kirchoff law. The main goal is the reconstruction of the potential everywhere on the network, from the Neumann boundary measurements at all but one external vertices. Leveraging from the Lipschitz stability of this inverse problem, we aim at providing an efficient reconstruction algorithm based on the use of a specific global Carleman estimate. The proof of the main tool and of the convergence of the algorithm are provided; along with a detailed description of the numerical illustrations given at the end of the article
On the stationary distribution of reflected Brownian motion in a wedge: differential properties
No full textInternational audienceWe consider the classical problem of determining the stationary distribution of the semimartingale reflected Brownian motion (SRBM) in a two-dimensional wedge. Under standard assumptions on the parameters of the model (opening of the wedge, angles of the reflections, drift), we study the algebraic and differential nature of the Laplace transform of this stationary distribution.We derive necessary and sufficient conditions for this Laplace transform to be rational, algebraic, differentially finite or more generally differentially algebraic. These conditions are explicit linear dependencies between the angles of the model. A complicated integral expression for this Laplace transform has recently been obtained by two authors of this paper. In the differentially algebraic case, we provide a simple, explicit integral-free expression in terms of a hypergeometric function. It specializes to earlier expressions in several classical cases: the skew-symmetric case, the orthogonal reflections case and the sum-of-exponential densities case (corresponding to the so-called Dieker-Moriarty conditions on the parameters). This paper thus closes, in a sense, the quest of all ``simple'' cases. To prove these results, we start from a functional equation that the Laplace transform satisfies, to which we apply tools from diverse horizons. To establish differential algebraicity, a key ingredient is Tutte's invariant approach, which originates in enumerative combinatorics. It allows us to express the Laplace transform (or its square) as a rational function of a certain canonical invariant, a hypergeometric function in our context. To establish differential transcendence, we turn the functional equation into a difference equation and apply Galoisian results on the nature of the solutions to such equations
Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water–methane dimer
No full textInternational audienceFixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely-trusted many-body method for solving the Schr\"{o}dinger equation, known for its reliable predictions of material and molecular properties. Furthermore, its excellent scalability with system complexity and near-perfect utilization of computational power makes FN-DMC ideally positioned to leverage new advances in computing to address increasingly complex scientific problems. Even though the method is widely used as a computational gold standard, reproducibility across the numerous FN-DMC code implementations has yet to be demonstrated. This difficulty stems from the diverse array of DMC algorithms and trial wave functions, compounded by the method's inherent stochastic nature. This study represents a community-wide effort to address the titular question, affirming that: Yes, FN-DMC is reproducible (when handled with care). Using the water-methane dimer as the canonical test case, we compare results from eleven different FN-DMC codes and show that the approximations to treat the non-locality of pseudopotentials are the primary source of the discrepancies between them. In particular, we demonstrate that, for the same choice of determinantal component in the trial wave function, reliable and reproducible predictions can be achieved by employing the T-move (TM), the determinant locality approximation (DLA), or the determinant T-move (DTM) schemes, while the older locality approximation (LA) leads to considerable variability in results. This work lays the foundation to establish accurate and reproducible FN-DMC estimates for all future studies across applications in materials science, physics, chemistry, and biology
A formal implementation of Behavior Trees to act in robotics
No full textInternational audienceBehavior Trees (BT) are becoming quite popular as an Acting component of autonomous robotic systems. We propose to define a formal semantics to BT by translating them to a formal language which enables us to perform verification of programs written with BT, as well as runtime verification while these BT execute. This allows us to formally verify BT correctness without requiring BT programmers to master formal languages and without compromising BT most valuable features: modularity, flexibility and reusability. We present the formal framework we use: Fiacre, its language and the produced TTS model; Tina, its model checking tools and Hippo, its runtime verification engine. We then show how the translation from BT to Fiacre is automatically done, the type of formal LTL and CTL properties we can check offline and how to execute the formal model online in place of a regular BT engine. We illustrate our approach on two robotics applications, and show how BT could benefit of other features available in the Fiacre formal framework (state variables, time, etc)
Impact of environmental factors on photovoltaic system performance degradation
No full textInternational audienceThe rapid expansion of photovoltaic (PV) systems underscores the need to understand environmental factors affecting their performance, degradation, and economic viability. This study comprehensively reviews 175 articles, classifying environmental factors such as atmospheric deposits (dust, sea salt, pollen), meteorological conditions (wind, temperature, humidity, rainfall, snowfall, hailstorms), shading, and solar irradiation variability. A novel multilevel classification of degradation modes is introduced, identifying failure mechanisms and their impacts. Key findings reveal performance losses of up to 60%-70% due to combined factors, while mitigation strategies, such as wind-induced cooling, can improve power output by 14.25%, and snow accumulation results in up to 12% annual energy losses. Performance metrics like Performance Loss Rate (PLR) and Degradation Rate (DR) are evaluated to quantify long-term impacts, with economic implications including potential revenue losses and maintenance costs. For instance, addressing dust accumulation in arid regions could save 20%-30% in annual cleaning costs while reducing energy inefficiencies. Recent advancements in AI-driven predictive maintenance are highlighted as pivotal for optimizing system performance and minimizing costs. This integrated analysis provides actionable insights for researchers, engineers, and policymakers, emphasizing the need for tailored strategies to enhance PV resilience and economic sustainability. By addressing the interaction of environmental factors and introducing standardized metrics, this study fills critical research gaps, offering a roadmap for improving PV system reliability, reducing operational costs, and supporting the transition to sustainable energy under diverse environmental conditions
40 ans de développements en lithographie électronique : mémoires d’un dinosaure
No full textInternational audiencePersonal experience presentation over 40 years on Electron Beam Lithography (EBL) through its development history which led to the purchase of a 100keV EBL system at CNRS-LAA