This paper addresses the problem of hierarchical task control, where a robotic system must perform multiple subtasks with varying levels of priority. A commonly used approach for hierarchical control is the null-space projection technique, which ensures that higher-priority tasks are executed without interference from lower-priority ones. While effective, the state-of-the-art implementations of this method rely on low-level controllers, such as PID controllers, which can be prone to suboptimal solutions in complex tasks. This paper presents a novel framework for hierarchical task control, integrating the null-space projection technique with the path integral control method. Our approach leverages Monte Carlo simulations for real-time computation of optimal control inputs, allowing for the seamless integration of simpler PID-like controllers with a more sophisticated optimal control technique. Through simulation studies, we demonstrate the effectiveness of this combined approach, showing how it overcomes the limitations of traditional
Nicolae Marcoie, Șerban Chihaia, Tomi Alexăndrel Hrăniciuc
et al.
This work analyzed the nutrient dynamics (2011–2022) and discharge (2005–2022) for the Bahlui River at four distinctive locations: Parcovaci—a dam-protected area that has been untouched by agriculture or urbanization; Belcesti—a primarily agricultural area, also dam-protected; Podu Iloaiei—a region influenced by agriculture and urbanization; and Holboca—placed after a heavily urbanized area. The analysis focused on determining a series of statistical indicators using the Minitab 21.2 software. Two drought intervals and one flood interval were analyzed to highlight daily discharge evolution during the selected period, showing that the constructed reservoirs successfully control the streamflow. For the entire period, the evolution of mean and median values of the streamflow is consistent, considering the locations’ positions from the source to the river’s end. The total nitrogen and total phosphorus were selected as representative quality indicators. The study follows the influence of the analyzed areas’ characteristics and reservoirs’ presence on nutrient dynamics. The results showed that the most influential factor that impacts nutrient dynamics is the reservoirs’ presence, which controls the discharge, creates wetlands and swamps, and implicitly impacts nutrient concentration.
Nivedita Singh, Yejin Do, Yongsang Yu. Imane Fouad
et al.
Despite stringent data protection regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and other country-specific regulations, many websites continue to use cookies to track user activities. Recent studies have revealed several data protection violations, resulting in significant penalties, especially for multinational corporations. Motivated by the question of why these data protection violations continue to occur despite strong data protection regulations, we examined 360 popular e-commerce websites in multiple countries to analyze whether they comply with regulations to protect user privacy from a cookie perspective.
In this work, we propose a cascaded scheme of linear Model prediction Control (MPC) based on Control Barrier Functions (CBF) with Dynamic Feedback Linearization (DFL) for Vertical Take-off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs). CBF is a tool that allows enforcement of forward invariance of a set using Lyapunov-like functions to ensure safety. The First control synthesis that employed CBF was based on Quadratic Program (QP) that modifies the existing controller to satisfy the safety requirements. However, the CBF-QP-based controllers leading to longer detours and undesirable transient performance. Recent contributions utilize the framework of MPC benefiting from the prediction capabilities and constraints imposed on the state and control inputs. Due to the intrinsic nonlinearities of the dynamics of robotics systems, all the existing MPC-CBF solutions rely on nonlinear MPC formulations or operate on less accurate linear models. In contrast, our novel solution unlocks the benefits of linear MPC-CBF while considering the full underactuated dynamics without any linear approximations. The cascaded scheme converts the problem of safe VTOL-UAV navigation to a Quadratic Constraint Quadratic Programming (QCQP) problem solved efficiently by off-the-shelf solvers. The closed-loop stability and recursive feasibility is proved along with numerical simulations showing the effective and robust solutions. Keywords: Unmanned Aerial Vehicles, Vertical Take-off and Landing, Model Predictive Control, MPC, Nonlinearity, Dynamic Feedback Linearization, Optimal Control.
This paper presents an instability result of Hamiltonian systems associated with optimal swing-up control for a pendulum. The systems possess weak (higher-order) instability at the initial point of the swing-up control, the analysis for which requires techniques from celestial mechanics. The obtained result may have relationships with the previously obtained numerical studies for the existence of multiple locally optimal solutions and the non-existence conjecture of the optimal control.
The challenges of abiotic stress on plant growth and development are evident among the emerging ecological impacts of climate change (Bellard et al., 2012), and the constraints to crop production exacerbated with the increasing human population competing for environmental resources (Wallace et al., 2003). Climate change is predicted to affect agricultural production the most, primarily at low latitudes populated by developing countries, with adverse effects of increasing carbon dioxide and high temperature, challenging researchers toward devising adaptation strategies (Rosenzweig et al., 2014). These constraints to global food supply and a balanced environment encourage research and development of climate smart crops, resilient to climate change (Wheeler and Von Braun, 2013). The field of plant abiotic stress encompasses all studies on abiotic factors or stressors from the environment that can impose stress on a variety of species (Sulmon et al., 2015). These stressors include extreme levels of light (high and low), radiation (UV-B and UV-A), temperature [high and low (chilling, freezing)], water (drought, flooding, and submergence), chemical factors (heavy metals and pH), salinity due to excessive Na+, deficient or in excess of essential nutrients, gaseous pollutants (ozone, sulfur dioxide), mechanical factors, and other less frequently occurring stressors. Since combinations of these stresses such as heat and drought frequently occur under field conditions, and can cause unique effects that cannot be predicted from individual stressors (Suzuki et al., 2014), a multiplicity of physiological interactions can be expected, needing individual novel solutions. Plants are rooted in the environment they grow in, and have to adapt to the changing conditions brought about by the multitude of environmental factors, with extreme levels eliciting abiotic stress. A grand challenge in abiotic stress biology is to decipher how plants perceive the different stressors, how the early signals are transduced within the plant, what is the diversity of response pathways elicited by them, and how are they genetically determined (Yoshida et al., 2014). Beyond model plants and reference genotypes, the challenge is to identify how signaling pathways have evolved within a species to program a suite of responses differing in signals and regulatory networks, and constitute genotypes that are adapted to specific stressful environments. Many studies have begun to deal with the comparison of a few genotypes, such as tolerant and sensitive within a species, for the analysis of differential responses to a defined stress. Since these responses can be due to differences in sets of genes, an understanding of the diversity in signaling pathways can come only by making a systems level study of the differences between genotypes. Such comparative studies offer a challenge for the integration of diverse functional genomics datasets of gene expression, metabolomics, and stress physiological responses to make comparisons in the network of responses across genotypes. A compatible environment for one plant genotype may not be for another, and all external factors abiotic or biotic, can raise a challenge or stress to the plant depending on the plants genetic constitution and adaptive response. The specific genotype × environment interaction combinations offer multitude of effects in response to the environment (Des Marais et al., 2013). Molecular genetic analysis of specific genes conferring stress tolerance from tolerant crop accessions have resulted in the map-based isolation of genes for submergence tolerance (Xu et al., 2006) and salt tolerance (Ren et al., 2005) in rice, among many others. The challenge ahead is in the analysis of natural variation in populations using genome wide association studies (GWAS) to dissect quantitative traits from field screens of diverse genotypes and map specific naturally occurring “stress tolerant loci.” This has been successful for salt tolerance (Kumar et al., 2015) in rice, and also led to the identification from maize of the first drought tolerance gene (Mao et al., 2015). The variation within the maize drought tolerance gene is particularly interesting because the drought sensitive allele contains a transposon insert in the promoter that is involved in epigenetic regulation of the gene that differs in distribution between temperate and tropical maize. Transposons as agents of regulation of genes in abiotic stress are being identified in maize as “controlling elements” involved in the regulation of around 20% of the abiotic stress responsive genes (Makarevitch et al., 2015), indicating evolution and selection of novel stress protective alleles active in natural populations. Similarly in rice, insertions of the mPing transposon with insertion preference in the 5′ regions of genes were shown to up-regulate the downstream genes and render them stress responsive (Naito et al., 2009). The intriguing challenge ahead is to now see how far McClintock's controlling elements (McClintock, 1984), that are induced to move under stress can help plants survive abiotic stresses by creating and regulating networks of genes for stress protection. The new challenges will come from genome-wide analyses of stress tolerant genotypes from multiple plant species that will probably reveal novel tolerance and selective mechanisms in natural populations. The supporting technologies from next-generation sequencing to GWAS are available in many plant species, and much research is concentrated in this area for stress tolerance. This is therefore an area for future discoveries that will reveal the evolution of diverse mechanisms for stress tolerance that could be valuable for the design of crop improvement strategies including for climate change challenges. A fruitful strategy for the identification of stress tolerance genes has been by reverse genetics analyses of candidate genes identified through gene expression studies and other bioinformatics methods. The biological role of such candidate genes has been most often tested by the analysis of overexpression, knockout/knockdown genotypes in model, and crop plants (Todaka et al., 2015). Overexpression studies with transcription factors and other regulatory genes have been popular in transgenic crops, with the objective of improving their stress tolerance and productivity (Mickelbart et al., 2015), and often enabling applications across plant species. The potential redundancy of stress tolerance genes remains a challenge, since overexpression studies might not represent the natural function of genes in the plant. Nevertheless, all studies testing the potential phenotype of genes for alterations in stress response provide useful information on the gene function as well as the applications. Gene expression analysis of plants in response to abiotic stresses reveals a large fraction of the genome can be perturbed, reflecting the plasticity in stress response and protection. The complexity of a plants' response to abiotic stress factors, in interaction with its genetic constitution, provides a multitude of morpho-physiological, biochemical, gene expression, and other molecular responses that can best be described by networks of response pathways leading to expression of tolerance and adaptation to the environment. The role of genetics and evolution propounded by Darwinism seemed to prevail over the opposing views of Lamarckism, proposing life forms could acquire information from their environment and pass it on in their genes. Now, two centuries later the evidence from epigenetics is showing us in surprising detail, with the sophistication of genomics technologies, how the epigenome carries information that is not encoded in the DNA to offspring, and can even provide a mechanism for acclimation and adaptation to stress (Avramova, 2015). The role of the environment, and subsequently stresses that might permanently plague plants, probably have a significant epigenetic influence on the behavior of plants and their progeny, and provide new challenges to re-visit plant–environment interactions. Abiotic stresses will remain a challenge to the natural environment and agriculture. The early evolution of land plants took place under dry conditions with extremes of temperature and harsh sunlight, while crop domestication occurred later in more favorable environments. Subsequently, the selection of plants for productivity traits did not always result in crops that are productive under random stress factors, although the natural variation of crops are genetic reservoirs for abiotic stress adaptation. Presently, with the competing uses of land and the growing world population we are challenged to produce more in less area with dwindling resources of water, confronted with climate change increases in temperature and carbon dioxide, and the unpredictable local microclimate adversely affecting crop productivity. The challenges before us in plant biology and crop improvement are to integrate the systems level information on abiotic stress response pathways, identify stress protective networks, and engineer environmentally stable crops that yield more, with less water and dwindling natural resources, to feed the growing world population.
Doddi Yudianto, Finna Fitriana, Albert Wicaksono
et al.
ABSTRACTBogor City, renowned for its high rainfall value, has experienced rapid economic growth, leading to a substantial surge in population. This, in turn, has prompted extensive development, disrupting land use in the urban area. Consequently, effective area planning incorporating an adequate drainage system is imperative to mitigate flooding. The Cileuwibangke River, located south of Bogor City, traverses a residential area earmarked for conversion into commercial and industrial zones. Therefore, evaluating the floodwater level of the Cileuwibangke River is crucial, both in its existing state and post-construction. This study utilized daily data from the Gadog Rainfall Station and hourly data from the GPM satellite spanning from 2001 to 2020 for rainfall analysis. It revealed that several rain events exceeded the 2, 5, and 10-year return periods. Rainfall-runoff analysis showed that changes in land use resulted in a 35-36% increase in peak flood discharge and a 22-28% increase in runoff volume compared to the existing condition. The findings indicated that the normalization of the river section on the residential area side did not significantly lower the floodwater level, attributed to three broad-dimension culverts. Moreover, strengthening the river's bottom and banks is essential due to the observed hydraulic jump indication. Upstream riverbed protection can be achieved with a 35 m stretch of rock material. Keywords: Bogor City, Cileuwibangke River, HEC-HMS, HEC-RAS, and Urban Flood ABSTRAKKota Bogor, dikenal dengan curah hujannya yang tinggi, mengalami pertumbuhan ekonomi yang tinggi sehingga menyebabkan peningkatan jumlah penduduk yang cukup pesat. Hal ini memicu pembangunan besar-besaran yang mengubah fungsi lahan di kawasan perkotaan. Oleh karena itu, perencanaan kawasan dengan sistem drainase yang memadai diperlukan untuk mencegah terjadinya banjir. Sungai Cileuwibangke, yang terletak di selatan Kota Bogor, mengalir melalui kawasan pemukiman yang akan dikembangkan menjadi kawasan komersial dan industri. Sehingga, perlu dilakukan evaluasi tinggi muka air banjir Sungai Cileuwibangke baik pada kondisi eksisting maupun setelah konstruksi. Studi ini menggunakan data harian Pos Hujan Gadog dan data jam-jaman satelit GPM dari tahun 2001 hingga 2020 untuk melakukan analisis curah hujan. Ditemukan bahwa beberapa kejadian hujan memiliki nilai lebih besar dari hujan rencana periode ulang 2, 5, dan 10 tahun. Berdasarkan analisis curah hujan-limpasan yang dilakukan, diketahui bahwa alih fungsi lahan mengakibatkan peningkatan debit banjir puncak dan volume limpasan masing-masing sebesar 35-36% dan 22-28% dibandingkan dengan kondisi eksisting. Hasil penelitian menunjukkan bahwa normalisasi ruas sungai di sisi pemukiman tidak menurunkan debit banjir secara signifikan, dikarenakan adanya tiga gorong-gorong berdimensi lebar pada kawasan tersebut. Selain itu, perlu dilakukan perkuatan dasar sungai dan bantaran sungai dikarenakan adanya indikasi loncatan hidraulik. Perlindungan dasar sungai dapat dilakukan di hulu dengan menggunakan material batuan sepanjang 35 m.Keywords: Banjir Perkotaan, HEC-HMS, HEC-RAS, Kota Bogor, dan Sungai Cileuwibangke
Qiuhao Hu, Mohammad Reza Amini, Ashley Wiese
et al.
This paper explores the synergies between integrated power and thermal management (iPTM) and battery charging in an electric vehicle (EV). A multi-objective model predictive control (MPC) framework is developed to optimize the fast charging performance while enforcing the constraints in the power and thermal loops. The approach takes into account the coupling of the battery and cabin thermal management. The case study of a commercial EV demonstrates that the proposed method can effectively meet the requirements of fast charging and thermal management when accurate preview information is available. However, failure to predict the charging event can result in performance degradation with longer charging time. A time-varying weighting strategy is proposed to enhance charging performance in the presence of uncertainty. This strategy leverages the battery state-of-charge (SOC) and adjusts the priority of the multi-objective MPC at different phases during charging. Simulated results using a commercial EV use case show improved robustness in charging time using the proposed strategy.
Control barrier functions (CBFs) have become a popular tool to enforce safety of a control system. CBFs are commonly utilized in a quadratic program formulation (CBF-QP) as safety-critical constraints. A class $\mathcal{K}$ function in CBFs usually needs to be tuned manually in order to balance the trade-off between performance and safety for each environment. However, this process is often heuristic and can become intractable for high relative-degree systems. Moreover, it prevents the CBF-QP from generalizing to different environments in the real world. By embedding the optimization procedure of the exponential control barrier function based quadratic program (ECBF-QP) as a differentiable layer within a deep learning architecture, we propose a differentiable safety-critical control framework that enables generalization to new environments for high relative-degree systems with forward invariance guarantees. Finally, we validate the proposed control design with 2D double and quadruple integrator systems in various environments.
Predrag Popović, Olivier Devauchelle, Anaïs Abramian
et al.
Understanding how rivers adjust to the sediment load they carry is critical to predicting the evolution of landscapes. Presently, however, no physically based model reliably captures the dependence of basic river properties, such as its shape or slope, on the discharge of sediment, even in the simple case of laboratory rivers. Here, we show how the balance between fluid stress and gravity acting on the sediment grains, along with cross-stream diffusion of sediment, determines the shape and sediment flux profile of laminar laboratory rivers which carry sediment as bedload. Using this model, which reliably reproduces the experiments without any tuning, we confirm the hypothesis, originally proposed by Parker (1978), that rivers are restricted to exist close to the threshold of sediment motion (within about 20%). This limit is set by the fluid-sediment interaction and is independent of the water and sediment load carried by the river. Thus, as the total sediment discharge increases, the intensity of sediment flux (sediment discharge per unit width) in a river saturates, and the river can only transport more sediment by widening. In this large discharge regime, the cross-stream diffusion of momentum in the flow permits sediment transport. Conversely, in the weak transport regime, the transported sediment concentrates around the river center without significantly altering the river shape. If this theory holds for natural rivers, the aspect ratio of a river could become a proxy for sediment discharge - a quantity notoriously difficult to measure in the field.
In the recent years, the impacts of floods have gained importance because of the increasing number of people who are affected by its adverse effects, especially in Beaufort area, Sabah, Malaysia. Flood destroyed critical infrastructures that are needed as shelter and also emergency relief for victim. This paper presents the findings of flood modelling undertaken to establish baseline and post mining flooding conditions during upstream storm and combination of upstream and downstream storm, respectively. A hydrologic model was established and calibrated based on 2014 flood. A structural approach by changing the physical dimension through dredging or sand mining between 2m to 3m is used for hydrology modelling is added into the existing floodgates and bunds. The outcome from sustainable sand is prevailing when it is able to reduce flood level for normal flow, upstream case, and both upstream and downstream case. Other findings are changes in velocity, shear and the significantly reduced power generated by the river during flooding.
Abstract The central task of the Yellow River flood control works management is to maintain the integrity of the project and ensure the flood control ability of the project does not decrease. In order to achieve this goal, the Yellow River management departments at all levels need to use modern technology to supervise a set of modern project management system, so as to understand and grasp the project operation status in real time, so as to timely find and eliminate the project hidden dangers, and ensure the safety of the downstream embankment and flood control operation.
Janne Koivumäki, Jukka-Pekka Humaloja, Lassi Paunonen
et al.
This study proposes an adaptive subsystem-based control (SBC) for systematic and straightforward nonlinear~control of nth-order strict-feedback form (SFF) systems.~By decomposing the SFF system to subsystems, a generic~term (namely stability connector) can be created to address dynamic interactions between the subsystems. This 1) enables modular control design with global asymptotic stability, 2) such that both the control design and the stability analysis can be performed locally at a subsystem level, 3) while avoiding an excessive growth of the control design complexity when the system order n increases. The latter property makes the method suitable especially for high-dimensional systems. We also design a smooth projection function for addressing system parametric uncertainties. Numerical simulations demonstrate the efficiency of the method.
This paper is concerned with the Proportional Integral (PI) regulation control of the left Neu-mann trace of a one-dimensional semilinear wave equation. The control input is selected as the right Neumann trace. The control design goes as follows. First, a preliminary (classical) velocity feedback is applied in order to shift all but a finite number of the eivenvalues of the underlying unbounded operator into the open left half-plane. We then leverage on the projection of the system trajectories into an adequate Riesz basis to obtain a truncated model of the system capturing the remaining unstable modes. Local stability of the resulting closed-loop infinite-dimensional system composed of the semilinear wave equation, the preliminary velocity feedback, and the PI controller, is obtained through the study of an adequate Lyapunov function. Finally, an estimate assessing the set point tracking performance of the left Neumann trace is derived.
Abstract We present the results of flume experiments specifically designed to investigate the conditions required for successful bank protection using fascines, considered in the early and critical stage of their installation (no developed root system), in the alpine context. A total of 145 runs were performed with erodible banks, considering different combinations of protection design (no protection, rip-raps, twigs), bed mobility (with or without bedload), discharge (from low to exceptional floods), and bend curvature radius. None of the runs showed any direct fascine grabbing by the flow observed; all destruction was the consequence of bank scouring, erosion and collapse around the structure. In all cases, most destructive effects resulted from water recirculation inside the bank. Thus, we conclude that all measures aiming to reduce water circulations during the first stage of the fascine construction and development are recommended. This include large bend curvature radii (when possible), fining of the filling material, use of antiscouring twigs, optimisation of the programming of the works with consideration of the hydrology (shape of hydrographs) and regular survey of the structure. Our experiments show that anti-scouring twigs have a real protective effect by modifying the local hydraulics and promoting sediment deposition at the bank toe.
We consider a multi-agent noncooperative game with agents' objective functions being affected by uncertainty. Following a data driven paradigm, we represent uncertainty by means of scenarios and seek a robust Nash equilibrium solution. We treat the Nash equilibrium computation problem within the realm of probably approximately correct (PAC) learning. Building upon recent developments in scenario-based optimization, we accompany the computed Nash equilibrium with a priori and a posteriori probabilistic robustness certificates, providing confidence that the computed equilibrium remains unaffected (in probabilistic terms) when a new uncertainty realization is encountered. For a wide class of games, we also show that the computation of the so called compression set - a key concept in scenario-based optimization - can be directly obtained as a byproduct of the proposed solution methodology. Finally, we illustrate how to overcome differentiability issues, arising due to the introduction of scenarios, and compute a Nash equilibrium solution in a decentralized manner. We demonstrate the efficacy of the proposed approach on an electric vehicle charging control problem.