Controlled System Research Articles

Stabilization of impulsive hybrid stochastic differential equations with Lévy noise by feedback control based on discrete-time state observations

In this paper, we investigate the problem of the mean-square exponential stabilization for a class of unstable impulsive hybrid stochastic differential equations with Lévy noise (IHSDEs-LN) via feedback control based on discrete-time state observations. Our results show that if feedback control of continuous-time observations can stabilize the controlled system in the sense of mean-square exponential stability, then feedback control of discrete-time state observations can also stabilize the controlled system. And there exists an upper bound on the interval between adjacent observation moments that can be accurately computed. Based on this new theory, we first design continuous-time feedback control for unstable IHSDEs-LN to achieve the stabilization problem, and then improve the continuous-time feedback control to discrete-time state observations feedback control.

Supervisor synthesis for asynchronous diagnosability enforcement in labeled Petri nets

The asynchronous fault diagnosis problem involves detecting the occurred faults in a system in the scenario that one asynchronously initiates a diagnosis agent with the system. This research investigates the asynchronous fault diagnosis problem of a system represented by labeled Petri nets (LPNs). An important property named asynchronous diagnosability of an LPN plant is formulated and studied which indicates that the detection of a fault can be achieved within a finite number of observations in the context of asynchronous diagnosis. This paper first introduces a structure named an asynchronous basis diagnoser, based on which the asynchronous diagnosis problem of an LPN plant can be addressed. Moreover, an approach is presented which leverages the asynchronous basis diagnoser to identify the asynchronous diagnosability. If an LPN plant is not asynchronously diagnosable, a supervisor is then designed which constraints the plant's behavior such that the controlled system satisfies the requirement of asynchronous diagnosability.

Novel distributed event/self-triggered sliding-mode control: Application to practical fixed-time consensus of second-order multi-agent systems

This paper presents a novel terminal sliding-mode control (SMC) protocol to accomplish the practical fixed-time (PFXT) consensus of second-order multi-agent systems (MASs) through event-triggered scheme (ETS). The main challenge is the digitization of SMC which prevents the controlled system from reaching an ideal sliding phase and the singularity problem in terminal sliding-mode controllers. Firstly, a novel method of PFXT stability is proposed, which guarantees the non-singularity for the controller. Secondly, based on the proposed PFXT control method, a practical non-singular terminal SMC strategy is designed to accomplish the PFXT consensus of MASs through ETS. Besides, a strictly positive minimal triggering interval of each follower is given to exclude the Zeno phenomenon. Different with conventional terminal SMC, maintaining the sliding trajectory constrained on the sliding manifold is not a premise to guarantee the system stability. Then, to eliminate the requirement of continuous monitoring for ETS, the SMC strategy is generalized to the self-triggered approach. At last, a numerical example is presented to validate the developed methods.

Increase of secondary metabolites in sweet basil (Ocimum basilicum L.) leaves by exposure to N2O5 with plasma technology

Exposure to N2O5 generated by plasma technology activates immunity in Arabidopsis through tryptophan metabolites. However, little is known about the effects of N2O5 exposure on other plant species. Sweet basil synthesizes many valuable secondary metabolites in its leaves. Therefore, metabolomic analyses were performed at three different exposure levels [9.7 (Ex1), 19.4 (Ex2) and 29.1 (Ex3) μmol] to assess the effects of N2O5 on basil leaves. As a result, cinnamaldehyde and phenolic acids increased with increasing doses. Certain flavonoids, columbianetin, and caryophyllene oxide increased with lower Ex1 exposure, cineole and methyl eugenol increased with moderate Ex2 exposure and l-glutathione GSH also increased with higher Ex3 exposure. Furthermore, gene expression analysis by quantitative RT-PCR showed that certain genes involved in the syntheses of secondary metabolites and jasmonic acid were significantly up-regulated early after N2O5 exposure. These results suggest that N2O5 exposure increases several valuable secondary metabolites in sweet basil leaves via plant defense responses in a controllable system.

Stability equivalence between regime‐switching jump diffusion delayed systems and corresponding systems with piecewise continuous arguments and application to discrete‐time feedback control

AbstractIn this paper, we mainly study the equivalence of exponential stability for regime‐switching jump diffusion delayed systems (RSJDDSs) and RSJDDSs with piecewise continuous arguments (RSJDDSs‐PCA). Our results show that if one of the RSJDDS and the RSJDDS‐PCA is th moment exponentially stable, then another system is also th moment exponentially stable when time delay and segment step size have a common upper bound, while both equations are almost surely exponentially stable, and we also provided a method to calculate this upper bound. In addition, as an application of the stability equivalence theorem, we design discrete‐time state and mode observations feedback control to stabilize unstable RSJDDSs and investigate that controllers of the drift, diffusion, and jump terms are all able to play a stabilizing effect on the controlled system.

Fractional Proportional Linear Control Systems: A Geometric Perspective on Controllability and Observability

The paper presents a detailed analysis of control and observation of generalized Caputo proportional fractional time-invariant linear systems. The focus is on identifying controllable states and observable systems within the controllable subspace, null space, and unobservable subspace of the proposed system. The necessary conditions for the controllable subspace and the necessary and sufficient conditions for observability criteria are firmly established. The controllable subspace is treated geometrically as the set of controllable states, while the observable system is characterized by a zero unobservable subspace. The results are reinforced by examples and will immensely benefit future studies on fractional-order control systems.

NON-ANALYTICAL DESIGN OF THE PI CONTROLLER OPTIMAL PARAMETERS FOR A CONTINUOUS LINE

The multiple motor drives are complex and coupled MIMO nonlinear systems. Due to the complexity of their mathematical models the development of effective control systems is quite complicated task. This paper presents the design of optimal control based on the quadratic optimality criterion for the central section of the continuous production line using soft computer methods when fuzzy model of the controlled system has been used. In this case, the proposed method demonstrates non-analytical design of the optimal parameters of PI controller with emphasis on minimal knowledge on the controlled system. The realized experimental measurements on a continuous line laboratory model confirmed the effectiveness and the good dynamic properties of the optimal continuous line controller and also its applicability to others MIMO nonlinear dynamic systems.

Integrating Graphene Oxide-Hydrogels and Electrical Stimulation for Controlled Neurotrophic Factor Encapsulation: A Promising Approach for Efficient Nerve Tissue Regeneration.

Nerve growth factor (NGF) plays a crucial role in cellular growth and neurodifferentiation. To achieve significant neuronal regeneration and repair using in vitro NGF delivery, spatiotemporal control that follows the natural neuronal processes must be developed. Notably, a challenge hindering this is the uncontrolled burst release from the growth factor delivery systems. The rapid depletion of NGF reduces treatment efficacy, leading to poor cellular response. To address this, we developed a highly controllable system using graphene oxygen (GO) and GelMA hydrogels modulated by electrical stimulation. Our system showed superior control over the release kinetics, reducing the burst up 30-fold. We demonstrate that the system is also able to sequester and retain NGF up to 10-times more efficiently than GelMA hydrogels alone. Our controlled release system enabled neurodifferentiation, as revealed by gene expression and immunostaining analysis. The increased retention and reduced burst release from our system show a promising pathway for nerve tissue engineering research toward effective regeneration.

Swirling Capillary Instability of Rivlin–Ericksen Liquid with Heat Transfer and Axial Electric Field

The mutual influences of the electric field, rotation, and heat transmission find applications in controlled drug delivery systems, precise microfluidic manipulation, and advanced materials’ processing techniques due to their ability to tailor fluid behavior and surface morphology with enhanced precision and efficiency. Capillary instability has widespread relevance in various natural and industrial processes, ranging from the breakup of liquid jets and the formation of droplets in inkjet printing to the dynamics of thin liquid films and the behavior of liquid bridges in microgravity environments. This study examines the swirling impact on the instability arising from the capillary effects at the boundary of Rivlin–Ericksen and viscous liquids, influenced by an axial electric field, heat, and mass transmission. Capillary instability arises when the cohesive forces at the interface between two fluids are disrupted by perturbations, leading to the formation of characteristic patterns such as waves or droplets. The influence of gravity and fluid flow velocity is disregarded in the context of capillary instability analyses. The annular region is formed by two cylinders: one containing a viscous fluid and the other a Rivlin–Ericksen viscoelastic fluid. The Rivlin–Ericksen model is pivotal for comprehending the characteristics of viscoelastic fluids, widely utilized in industrial and biological contexts. It precisely characterizes their rheological complexities, encompassing elasticity and viscosity, critical for forecasting flow dynamics in polymer processing, food production, and drug delivery. Moreover, its applications extend to biomedical engineering, offering insights crucial for medical device design and understanding biological phenomena like blood flow. The inside cylinder remains stationary, and the outside cylinder rotates at a steady pace. A numerically analyzed quadratic growth rate is obtained from perturbed equations using potential flow theory and the Rivlin–Ericksen fluid model. The findings demonstrate enhanced stability due to the heat and mass transfer and increased stability from swirling. Notably, the heat transfer stabilizes the interface, while the density ratio and centrifuge number also impact stability. An axial electric field exhibits a dual effect, with certain permittivity and conductivity ratios causing perturbation growth decay or expansion.

Distributed adaptive finite-time output feedback containment control for nonstrict-feedback stochastic multi-agent systems via command filters

In this paper, distributed adaptive finite-time output feedback containment control based on command filters is proposed for nonstrict-feedback stochastic multi-agent systems (SMASs) with unmodeled dynamics, input quantization and prescribed performance. The unknown states are estimated using a high-gain observer, the unmodeled dynamics is handled by introducing a measurable dynamic signal, and the input signal is processed using an integrated quantizer that combines the advantages of uniform quantizer and hysteretic quantizer. The hyperbolic tangent function and time-varying function are applied to construct the performance function, and the constrained containment error is transformed into an unconstrained system through nonlinear mapping (NM). Unknown smooth functions are handled with the superb approximation capability of radial basis function neural networks (RBFNNs). Based on stochastic finite-time theory and dynamic surface control (DSC) method, nonlinear command filters are introduced to reduce the use of black-box functions and simplify the controller design. Finally, the theoretical analysis and two sets of experimental results demonstrate that all signals in the controlled system are semi-global finite-time stability in probability (SGFSP) and the designed controller works well.

Real time adaptive probabilistic recurrent Takagi-Sugeno-Kang fuzzy neural network proportional-integral-derivative controller for nonlinear systems

This paper presents an adaptive probabilistic recurrent Takagi-Sugeno-Kang fuzzy neural PID controller for handling the problems of uncertainties in nonlinear systems. The proposed controller combines probabilistic processing with a Takagi-Sugeno-Kang fuzzy neural system to proficiently address stochastic uncertainties in controlled systems. The stability of the controlled system is ensured through the utilization of Lyapunov function to adjust the controller parameters. By tuning the probability parameters of the controller design, an additional level of control is achieved, leading to enhance the controller performance. Furthermore, it can operate without relying on the system's mathematical model. The proposed control approach is employed in nonlinear dynamical plants and compared to other existing controllers to validate its applicability in engineering domains. Simulation and experimental investigations demonstrate that the proposed controller surpasses alternative controllers in effectively managing external disturbances, random noise, and a broad spectrum of system uncertainties.

A Cell-Type Selective Stimulation and Recording System for Retinal Ganglion Cells.

Future retinal implants will require a stimulation selectivity between different sub-types of Retinal Ganglion Cells (RGCs) to evoke natural perceptions rather than phosphenes in patients. To achieve this, a cell-type specific stimulation pipeline is required that identifies target RGC sub-types from recorded input images and extracts the specific stimulation parameters to activate this cell-type selectively. Promising biological experiments showed that ON-/OFF- sustained/transient RGCs could be selectively activated by modulating repetition rate and amplitude of an electrical stimulation current in the kilohertz range. This research presents a 42 channel current controlled stimulation and recording system on chip (SoC) with parameter input from a real time target RGC selection algorithm. The SoC is able to stimulate retinal tissue with sinusoidal frequencies higher than 1 kHz at amplitudes of up to 200 μA at a supply voltage of 1.8 V. It also includes tunable recording units with an integrated action potential detection pipeline that are able to amplify signals between 1 Hz and 50 kHz. The required area of one stimulator is 0.0071 mm2, while one recording unit consumes an area of 0.0092 mm2. The application of sinusoidal stimulation currents in the kilohertz range towards retinal tissue leads to a suppressive response of only certain RGC sub-types that has not been oberved before, using electrical stimulation. Because this response is very similar to the natural light response of RGCs, this stimulation approach can lead to a more genuine visual perception for patients using retinal implants.

Multiple photofluorochromic luminogens via catalyst-free alkene oxidative cleavage photoreaction for dynamic 4D codes encryption

Controllable photofluorochromic systems with high contrast and multicolor in both solutions and solid states are ideal candidates for the development of dynamic artificial intelligence. However, it is still challenging to realize multiple photochromism within one single molecule, not to mention good controllability. Herein, we report an aggregation-induced emission luminogen TPE-2MO2NT that undergoes oxidation cleavage upon light irradiation and is accompanied by tunable multicolor emission from orange to blue with time-dependence. The photocleavage mechanism revealed that the self-generation of reactive oxidants driving the catalyst-free oxidative cleavage process. A comprehensive analysis of TPE-2MO2NT and other comparative molecules demonstrates that the TPE-2MO2NT molecular scaffold can be easily modified and extended. Further, the multicolor microenvironmental controllability of TPE-2MO2NT photoreaction within polymer matrices enables the fabrication of dynamic fluorescence images and 4D information codes, providing strategies for advanced controllable information encryption.

Contact exposure of honey bees and social stingless bees to fungicide sprayed on cotton and soybean in a controlled field simulation system

AbstractBees can be exposed to pesticides when visiting crops or plants in adjacent areas affected by spray drift. Among pesticide categories, fungicides tend to be considered relatively safe, though they also can negatively affect pollinators. Most evidence of damage by fungicides to bees comes from laboratory tests; there is little information concerning contamination levels in the field. We examined exposure of honey bees (Apis mellifera L.) (Hymenoptera: Apidae) and a common Brazilian native species of social stingless bees (Scaptotrigona postica Latreille; Hymenoptera: Apidae), which is about a third the size of a honey bee, to a commercial fungicide (Fox Xpro), with three active ingredients (trifloxystrobin, bixafen, and prothioconazole), applied to crops they often visit according to label directions. A spraying apparatus mounted on tracks in a laboratory spray room was used to simulate field conditions. Soybean and cotton plants grown in pots were transferred to the spray room when the plants were in flower. Anaesthetized bees were attached with insect pins at the top and middle of the plants, on leaves and flowers. The fungicide was applied using fine or coarse droplets. The amounts of the individual active ingredients absorbed by bees were then quantified. Concentrations of trifloxystrobin were highest in both honey bees and stingless bees, followed by bixafen, and then prothioconazole, which was detected in the bees at much lower levels. Overall, bees at the top of the plants and those sprayed with fine droplets absorbed more pesticide. As a function of body mass, the stingless bees were more heavily contaminated than the larger honey bees. Tests using spraying systems that simulate field conditions can better estimate the actual doses that contaminate bees to help determine the impact of fungicides and other pesticides applied to crops.

KONTROL SLIDING MODE ADAPTIF DENGAN VAKSINASI DAN TREATMENT PADA MODEL PENYEBARAN TUBERKULOSIS

This research examines the design of adaptive sliding mode control in a tuberculosis (TB) disease spread model, considering uncertainties within the model. The TB model involves five state variables (susceptible individuals, vaccinated individuals, individuals with latent TB infection, individuals with active TB infection, and individuals under treatment) and three control input variables consisting of vaccination and treatment. The objective of this control design is to reduce the number of susceptible individuals, individuals with active TB infection, and the number of individuals under treatment by tracking the given reference functions. Stability and convergence of tracking errors of the controlled system are proved using the Lyapunov Stability Theorem. Numerical simulations are conducted to evaluate the performance of the designed control under various parameter uncertainty conditions. Based on the simulation results, it is shown that the adaptive sliding mode controllers guarantee the convergence of tracking errors is achieved despite the presence of uncertainty in the model.

Supervisory Controller Design to Enforce Desired Properties in Systems Modeled by Timed-arc Petri Nets

Discrete-event systems which are modelled by timed-arc Petri nets are considered. A supervisory controller design approach for such systems for enforcing some desired properties is proposed. For the representation of the state of the system, the proposed design approach uses stretching. The designed controller enforces Lˆ-boundedness (for any given bound vector Lˆ) and reversibility simultaneously, whenever it is possible to design such a controller. Furthermore, ∆-liveness is also enforced, where ∆ is the largest possible subset of the set of transitions for which it is possible to design such a controller. Furthermore, the designed controller is maximally permissive in the sense that no transitions are disabled unnecessarily and the reachability set of the controlled system is the largest possible set in which boundedness and reversibility can be enforced simultaneously. To demonstrate the proposed approach, an example controller design is also presented for an automated manufacturing system.

Controlling the interactions in a cold atom quantum impurity system

We implement an experimental architecture in which a single atom of K is trapped in an optical tweezer, and is immersed in a bath of Rb atoms at ultralow temperatures. In this regime, the motion of the single trapped atom is confined to the lowest quantum vibrational levels. This realizes an elementary and fully controllable quantum impurity system. For the trapping of the K atom, we use a species-selective dipole potential, that allows us to independently manipulate the quantum impurity and the bath. We concentrate on the characterization and control of the interactions between the two subsystems. To this end, we perform Feshbach spectroscopy, detecting several inter-dimensional confinement-induced Feshbach resonances for the KRb interspecies scattering length, that parametrizes the strength of the interactions. We compare our data to a theory for inter-dimensional scattering, finding good agreement. Notably, we also detect a series of p-wave resonances stemming from the underlying free-space s-wave interactions. We further determine how the resonances behave as the temperature of the bath and the dimensionality of the interactions change. Additionally, we are able to screen the quantum impurity from the bath by finely tuning the wavelength of the light that produces the optical tweezer, providing us with a new effective tool to control and minimize the interactions. Our results open a range of new possibilities in quantum simulations of quantum impurity models, quantum information, and quantum thermodynamics, where the interactions between a quantized system and the bath is a powerful yet largely underutilized resource.

Development and Evaluation of Mucoadhesive Buccal Patch of Losartan Potassium

The buccal mucosa is regarded as an ideal location for administering medications for both local and systemic absorption. Mucin and polymers interact chemically during the mucoadhesion process. Much emphasis has been paid to the use of mucoadhesive polymers in buccal medication delivery. There are now many mucoadhesive dosage forms available, including pills, patches, disks, wafers, ointments, and gels. Buccal patches stand out among them for their higher comfort and flexibility. With their effective carrier capacity, smart materials like stimuli-responsive hydrogels, liposome-based patches, polymeric micelles, etc. play a crucial role in the development of these drug delivery systems by extending the drug's residence time at the site of absorption, improving drug bioavailability, reducing the frequency of dosing, and increasing patient compliance. Different designs and production techniques, including as electrospinning, electrospraying, and 3D printing, are thought to be novel and effective ways to manufacture buccal patches with certain distinctive qualities in comparison to conventional procedures like solvent casting. Aiming to develop buccal mucoadhesive patches as a novel controlled drug delivery system, this review aims to examine and introduce the most promising smart polymeric materials, new designs, and production techniques.

Adaptive Iterative Learning Constrained Control for Linear Motor-Driven Gantry Stage with Fault-Tolerant Non-Repetitive Trajectory Tracking

This article introduces an adaptive fault-tolerant control method for non-repetitive trajectory tracking of linear motor-driven gantry platforms under state constraints. It provides a comprehensive solution to real-world issues involving state constraints and actuator failures in gantry platforms, alleviating the challenges associated with precise modeling. Through the integration of iterative learning and backstepping cooperative design, this method achieves system stability without requiring a priori knowledge of system dynamic models or parameters. Leveraging a barrier composite energy function, the proposed controller can effectively regulate the stability of the controlled system, even when operating under state constraints. Instability issues caused by actuator failures are properly addressed, thereby enhancing controller robustness. The design of a trajectory correction function further extends applicability. Experimental validation on a linear motor-driven gantry platform serves as empirical evidence of the effectiveness of the proposed method.

The effects of commercial 2,4-D herbicide on game fish species: Natural lake water vs. laboratory system water

Aquatic herbicides with active ingredient 2,4-dichlorophenoxyacteic acid (2,4-D) are commonly used to control and combat aquatic non-native species that cause detrimental impacts including habitat destruction, strained resources among biota, and biodiversity loss. While many (eco)toxicology studies are performed in the laboratory under highly controlled circumstances, these studies may disregard the nuances and disorder that come with the complexity of natural aquatic ecosystems. Therefore, we conducted a series of laboratory experiments using laboratory system water, different lake waters, and different water parameters to determine the effects of ecologically relevant concentrations of 2,4-D (0.00–4.00 ppm a.e.) on the development and survival of two freshwater game species (Sander vitreus and Esox lucius). For 2,4-D exposures using different water sources, there were significant main effects of 2,4-D concentration and water source on walleye embryo and larval survival, however, there was no significant interaction between 2,4-D exposure and water source. For 2,4-D exposures and pH (5–9 pH), there were significant main effects of 2,4-D concentration and pH on walleye and northern pike embryo survival and a significant interaction between 2,4-D exposure and pH. Our results indicate that 2,4-D exposures in controlled laboratory system water can predict similar outcomes as 2,4-D exposures in natural lake water. Moreover, individual water parameters, such as pH, play a significant role in the toxicity of 2,4-D. Taken together, these results suggest that highly controlled laboratory studies are a useful tool for predicting impacts on survival of non-target fish in natural waters, but it is crucial for management agencies to consider individual water sources and specific lake water parameters in herbicide risk assessments to minimize the impacts to non-target organism.