Indian Institute of Technology Jodhpur

In general, when a system is only right-invertible, it indicates that the number of inputs surpasses both the outputs and states of the system. Over-actuated systems fall into this category. This chapter presents a structured approach to designing a reduced-order Sliding Mode Control for a uncertain non-minimum phase over-actuated systems to track arbitrary reference signals. The method proposed involves a transformation that resolves input redundancy, thus representing the system as a normally-actuated with virtual control inputs. Additionally, unstable zero dynamics are virtually stabilized through another transformation, allowing for the exclusion of stable and virtually stable zero dynamic states from the super-twisting control design. Finally, the computed virtual control magnitude is distributed among all actuators through a redistributed pseudo-inverse type of control allocation, ensuring that the system operates within the limits of actuator saturation.

This chapter addresses the problem of achieving output tracking in non-minimum phase (NMP) systems using reduced order sliding mode control (SMC). Unstable zero dynamics hinders the design of reduced order tracking controllers. However, this problem can be solved through the virtual stabilization of zero dynamics, achieved by decomposing the system in a special coordinate basis (SCB). The design of reduced order control is possible because of the robustness property of SMC, which effectively eliminates the matched disturbance. This chapter details a methodology for designing a reduced order sliding surface with a reduced order state vector, aiming to ensure the asymptotic stability of the entire state vector during sliding motion. This approach eliminates the need for zero dynamics states in the surface and the control design.

In this chapter, the design of a reduced-order switching function for a discrete-time uncertain non-minimum phase system in a special coordinate basis form is discussed. The sliding mode control utilizing this approach ensures the asymptotic stability of all system states in the presence of matched disturbance. This approach is further extended to address the tracking problem of discrete-time uncertain non-minimum phase systems. The results of the simulation of the reduced-order sliding mode design are compared with that of the full-order sliding surface. Finally, the limitation of this approach in discrete-time domain is discussed.

In the realm of control theory for time-invariant systems, there exist numerous well-established design techniques aimed at stability of an equilibrium. However, in most cases, the zero dynamics of the system are disregarded as they do not determine the system’s stability. Nevertheless, the impact of zero dynamics becomes evident when the problem of tracking an arbitrary reference arises. In the case of a non-minimum phase (NMP) system, the impact of unstable zero dynamics becomes detrimental since they cannot be modified or altered. This chapter provides an overview of fundamental concepts concerning zero dynamics, including definitions, system properties related to zero dynamics, and the structural decomposition of the system that reveals the presence of zero dynamics.

This chapter presents the design of a reduced-order sliding mode controller for output tracking of an arbitrary signal. The controller aims to stabilize the difference between the system’s states and the reference states. A key challenge in reduced-order controller design is dealing with the zero dynamics states within the range space of the control input. To address this issue, a virtual zero placement using a specific transformation is discussed. By overcoming this obstacle, the reduced-order sliding mode controller can achieve stable output tracking despite the presence of unstable zero dynamics. Another challenge involves obtaining a bounded solution for the unstable zero dynamic state with respect to an arbitrary tracking input. Two methods are discussed to address this challenge: a non-causal system inverse and a causal reference tracking method, which involves a stable system center.

Designing reduced order control offers significant advantages by allowing the exclusion of stable and unstable zero dynamics states while keeping the robustness intact. This chapter presents the design of a reduced order sliding mode control applied to three distinct areas: controlling the pendulum angle of an inverted pendulum on a cart, managing the longitudinal dynamics of an aircraft through elevator deflection, and regulating the product concentration in a non-isothermal Van de Vusse reactor using the dilution rate as an input.

The integration of software-defined networking (SDN) and cloud radio access networks (CRANs) into vehicular ad hoc networks (VANETs) presents intricate challenges to achieving stringent service level objectives (SLOs). These objectives include optimizing data flow and resource management, achieving low latency and rapid response times, and ensuring network resilience under fluctuating conditions. Traditional load balancing and clustering approaches, designed for more static environments, fall short in the dynamic and variable context of VANETs. This necessitates a paradigm shift towards more adaptive and robust strategies to meet these advanced SLOs reliably. This paper proposes a software-defined vehicular fog computing (SDFC) framework that refines resource allocation in VANETs. Our SDFC framework utilizes an intelligent controller placement that strategically positions decision-making entities within the network to optimize data flow and resource distribution. This placement is governed by a dynamic clustering algorithm that responds to variable network conditions, an advancement over the static mappings used by traditional methods. By incorporating parallel processing principles, the framework ensures that computational tasks are distributed effectively across network nodes, reducing bottlenecks and enhancing overall network agility. Empirical evaluations (testbed) and simulation results of our framework indicate a substantial increase in network efficiency: a 28% improvement in average response time, a 23% decrease in network latency, and a 25% faster convergence to optimal resource distribution compared to state-of-the-art methods. These improvements testify to the framework's ability to support the escalating demands of intelligent transportation systems and underscore its potential to refine operational efficacy within VANETs.

A phosphine-based novel pincer chromium (II) catalyst CrCl2(PONNH) (Cr-1) is reported. The complex exhibited promising catalytic performance in C-C and C-N bond formation by borrowing hydrogen methodology. The Cr-1 catalyzed...

We have developed an efficient and sustainable approach for the synthesis of 4,4'‐bipyrazole derivatives from spirocyclopropanyl‐pyrazolone and hydrazine under mild conditions. This methodology is catalyst free, operating effectively in both batch and continuous flow processes. The flow synthesis allows the production of products up to 110 mg/h which provides industrial applicability and scalability. Additionally, 4,4’‐bipyraole has been transformed into a triphenyl‐substituted pyrazole derivative.

Essential plant nutrients encapsulated or combined with nano-dimensional adsorbents define nano fertilizers (NFs). Nanoformulation of non-essential elements enhancing plant growth and stress tolerance also comes under the umbrella of NFs. NFs have an edge over conventional chemical fertilizers, viz., higher plant biomass and yield using much lesser fertilization, thereby reducing environmental pollution. Foliar and root applications of NFs lead to their successful uptake by the plant, depending on the size, surface charge, and other physicochemical properties of NFs. Smaller NFs can pass through channels on the waxy cuticle depending on the hydrophobicity, while larger NFs pass through the stomatal conduits of leaves. Charge-based adsorption, followed by apoplastic movement and endocytosis, translocates NFs through the root, while the size of NFs influences passage into vascular tissues. Recent transcriptomic, proteomic, and metabolomic studies throw light on the molecular mechanisms of growth promotion by NFs. The expression levels of nutrient transporter genes are regulated by NFs, controlling uptake and minimizing excess nutrient toxicity. Accelerated growth by NFs is brought about by their extensive regulation of cell division, photosynthesis, carbohydrate, and nitrogen metabolism, as well as the phytohormone-dependent signaling pathways related to development, stress response, and plant defense. NFs mimic Ca,²⁺ eliciting second messengers and associated proteins in signaling cascades, reaching transcription factors and finally orchestrating gene expression to enhance growth and stress tolerance. Developing advanced nano fertilizers of the future must involve exploring molecular interactions with plants to reduce toxicity and improve effectiveness.

The magnetic properties and crystal chemistry of the novel Ba2CaCo2Si6O17 compound exhibiting one-dimensional zigzag chains of Co2+ ions (S = 3/2) are investigated using powder X-ray diffraction (PXRD), scanning lectron microscopy, energy dispersive-Xray spectroscopy, and temperature and field-dependent magnetic measurements. The refinement of PXRD data suggests a Cmcm space group in orthorhombic symmetry for Ba2CaCo2Si6O17 compound, consisting of a CoO4 tetrahedral network including 1-D zigzag Co2+ chains. Microstructural and elemental analysis substantiate the proper stoichiometry of the synthesized material. Magnetic measurements show paramagnetic characteristics at room temperature, followed by a transition from paramagnetic to antiferromagnetic (AFM) ordering near 17 K, superimposed with weak ferromagnetic ordering (WFM) characteristics. Magnetic hysteresis (M–H) at 5 K depicts a sigmoid curve with unsaturated magnetization even at high fields. The negative Weiss temperature value ≈−98 K substantiates the strong antiferromagnetic exchange interaction with a frustration index of ≈5.76. The effective paramagnetic moment is 3.34μB, close to the spin-only value 3.87μB of Co2+ (S = 3/2). The competing and short-range FM-AFM interaction is observed because of the zigzag Co2+ chain in the compound. The onset of WFM is attributed to the zigzag magnetic chain-induced lattice and spin distortion in Ba2CaCo2Si6O17 compound.

In this study, we propose the use of quantum information gain (QIG) and fidelity as quantum splitting criteria to construct an efficient and balanced quantum decision tree. QIG is a circuit-based criterion in which angle embedding is used to construct a quantum state, which utilizes quantum mutual information to compute the information between a feature and the class attribute. For the fidelity-based criterion, we construct a quantum state using the occurrence of random events in a feature and its corresponding class. We use the constructed state to further compute fidelity for determining the splitting attribute among all features. Using numerical analysis, our results clearly demonstrate that the fidelity-based criterion ensures the construction of a balanced tree. We further compare the efficiency of our quantum information gain and fidelity-based quantum splitting criteria with different classical splitting criteria on balanced and imbalanced datasets. Our analysis shows that the quantum splitting criteria lead to quantum advantage in comparison to classical splitting criteria for different evaluation metrics.

Cutting force is a vital indicator for assessing the performance of machining operations; therefore, developing a reliable predictive model is mandatory for process monitoring, optimization, and control. The mechanistic force model is preferred among approaches presented in the literature due to computational efficiency and effectiveness. The prediction abilities of the model largely depend on the empirical relationship between uncut chip geometry and lumped empirical constants determined using machining experiments involving cutting force measurements. The experimental data usually contains noise and outliers that must be removed before determining empirical constants. Data mining techniques are potential tools for removing noisy and outlier-ridden experimental data. This work develops a two-stage hybrid approach combining a clustering technique and machine learning model for data mining and determining precise empirical constants. The comparative evaluation of three unsupervised clustering techniques, namely hierarchical density-based spatial clustering of applications with noise (HDBSCAN), one-class support vector machine (SVM), and elliptic envelope, is performed in removing outliers. The machine learning-based ADAMW algorithm is implemented to fit the relationship and determine empirical constants from cleansed experimental data. It has been shown that HDBSCAN combined with the ADAMW algorithm can effectively remove outliers, enhance the goodness of fit, and achieve better performance. The prediction abilities of the proposed approach are corroborated by performing machining experiments over varying cutting conditions. It is concluded that the hybrid approach can address challenges associated with noisy and outlier-ridden experimental data, thereby enhancing the fidelity of the mechanistic force model.

Based on the perspectives of social competence and communicative skills, the study investigates media literacy and communicative abilities utilizing social media among adolescents in Klaten, Central Java, Indonesia. The methodology involved administering a questionnaire with quantitative descriptive analysis to 160 adolescents in Klaten. The findings of this study’s media literacy analysis indicate that adolescents’ media literacy is at a medium level, sufficient to demonstrate how proficiently adolescents are currently beginning to use social media. According to data on their platform usage, adolescents also utilize social media to access entertainment content. A small percentage of users visit it for educational purposes. Adolescents use social media to find enjoyment. Furthermore, adolescents’ communicative skills yield comparatively poor outcomes. It’s clear from this that adolescents’ use of social media is still limited to consuming material; only some generate content.

The beam spreading is essential for evaluating the higher-order Gaussian beam when it propagates through atmospheric turbulence. In this paper, we investigate the impact of individual atmospheric parameters such as jitter, turbulence, wind speed, and thermal blooming on beam spreading of Hermite Gaussian (HG), and Laguerre Gaussian (LG) beams. We also examine spot size variations due to beam quality on various HG and LG modes. It is seen that the impact of spreading caused by beam quality and turbulence is higher than that of jitter, wind speed, and thermal blooming. As the mode order increases, the effect of turbulence strength increases, leading to more spread for HG and LG beams. Spreading due to diffraction and beam quality on higher mode LG beam is higher than the HG beam in different modes. Beam spreading due to thermal blooming for the lower mode is higher compared to the higher mode for LG and HG beams. The sensitivity of higher mode LG beams to turbulence distortions is greater than HG beams as they experience more significant fractional increases in their spot size due to turbulence. The combined beam spread for the Laguerre Gaussian beam is larger than the Hermite Gaussian beam. This paper aims to understand better individual beam spreading in the atmosphere and its impact on the overall performance of higher-order laser propagation to develop optimized laser systems.

An economical sol–gel auto-combustion method aided by citric acid was used to synthesize nickel ferrite (${\text{NiFe}}_{2}{\text{O}}_{4}$) nanoparticles (nickel nitrate/ferric nitrate at 1:2 and metal nitrate with citric acid at 1:1, stirring condition: 600 rpm). The impurity phase present in as-synthesized nickel ferrite was removed by sintering at 950°C in a microwave furnace. Powder x-ray diffraction of the sintered sample confirmed the removal of impurity phase and showed the spinel cubic nature of the particles. The crystallite sizes of both as-synthesized and sintered particles were calculated using the Scherrer and Williamson–Hall formulas, which confirmed the formation of nanoparticles. Further, the particle size distribution and morphology of both samples were calculated using scanning electron microscopy with the help of ImageJ software. The UV–Vis spectroscopy of the particles showed strong absorption between 200 nm and 600 nm. The room-temperature magnetic hysteresis analysis revealed that both the as-synthesized (NFO-As) and sintered (NFO-950) materials exhibited a ferromagnetic nature, with maximum saturation magnetization of 50.84 emu/g for NFO-950 and higher coercivity of 179.76 Oe for NFO-As. Specific absorption rate (SAR) values of 7.976 W/g and 11.54 W/g were determined for NFO-As and NFO-950, respectively, from induction tests, which suggests the material is a suitable candidate for hyperthermia treatment. Additionally, investigation of the particles’ third-order nonlinear characteristics using a Ti-sapphire femtosecond laser showed reverse saturation absorption for NFO-950. The average nonlinear absorption coefficient of NFO-950 was found to be 1.44 times that of copper ferrite nanoparticles, rendering it a suitable candidate for optical limiting applications.

Methods enabling direct C−H alkylation of heterocycles are of fundamental importance in the late‐stage modification of natural products, bioactive molecules, and medicinally relevant compounds. However, there is a scarcity of a general strategy for the direct C−H alkylation of a variety of heterocycles using commercially available alkyl surrogates. We report an operationally simple palladium‐catalyzed direct C−H alkylation of heterocycles using alkyl halides under the visible light irradiation with good scalability and functional group tolerance. Our studies suggest that the photoinduced alkylation proceeds through a cascade of events comprising, site‐selective alkyl radical addition, base‐assisted deprotonation, and oxidation. A combination of experiments and computations was employed for the generalization of this strategy, which was successfully translated towards the modification of natural products and pharmaceuticals.