Simple Dynamic Model Research Articles

An Anti-Interference Control Algorithm for Continuum Robot Arm

The large number of joints in a continuum manipulator complicates its dynamic modeling, making model simplification inevitable for practical motion control. However, due to external disturbances and internal noise, a controller based on the simplified dynamic model often struggles to meet the desired dynamic performance. To address this issue, this paper proposes an anti-interference control algorithm for continuum manipulators, designed to compensate for parameter uncertainties, external disturbances, and measurement noise. At the same time, the parameters of the algorithm are obtained in the form of solvability of linear matrix inequalities (LMIs). The simulation results show that the algorithm proposed in the paper provides better transient performance and is not affected by the entire disturbance. Experimental results further confirm the effectiveness and robustness of the algorithm.

How host-microbiome/holobiont evolution depends on whether the microbiome affects host lifespan or fecundity.

There is overwhelming evidence that the microbiome can be important to host physiology and fitness. As such, there is interest in and some theoretical work on understanding when hosts and microbiomes (co)evolve so that microbes benefit hosts and hosts favour beneficial microbes. However, the outcome of evolution likely depends on how microbes benefit hosts. Here, we use adaptive dynamics to investigate how host and symbiont evolution depend on whether symbionts increase host lifespan or host reproduction in a simple model of host and symbiont dynamics. In addition, we investigate 2 ways hosts release (and transmit) symbionts: by releasing symbionts steadily during their lifetime or by releasing them at reproduction, potentially increasing symbionts' chances of infecting the host's offspring. The former is strict horizontal transmission, whereas the latter is also a form of indirect or "pseudovertical" transmission. Our first key result is that the evolution of symbionts that benefit host fecundity requires pseudovertical transmission, while the evolution of symbionts that benefit host lifespan does not. Furthermore, our second key result is that when investing in host benefits is costly to the free-living symbiont stage, intermediate levels of pseudovertical transmission are needed for selection to favour beneficial symbionts. This is true regardless of fitness effects because release at reproduction increases the free-living symbiont population, which increases competition for hosts. Consequently, hosts could evolve away from traits that favour beneficial symbionts. Generally, our work emphasizes the importance of different forms of vertical transmission and fitness benefits in host, microbiome, and holobiont evolution as highlighted by our prediction that the evolution of fecundity-increasing symbionts requires parent-to-offspring transmission.

RBFNN based fixed time sliding mode control for PEMFC air supply system with input delay

Ensuring rapid regulation of the oxygen excess ratio (OER) in proton exchange membrane fuel cells (PEMFC) during load changes is an important challenge. In this paper, fixed time sliding mode control of a PEMFC with input delay has been investigated. First, a simplified fourth-order nonlinear dynamical model with input disturbance and input delay is considered and a cascade structure is selected for the control design. A radial basis function neural network (RBFNN) is designed to estimate the input disturbance. To achieve precise estimation, a Cuckoo Search Algorithm is utilized to calculate the parameters of the RBFNN. Then, a new sliding mode controller is proposed for trajectory tracking within a fixed time. To ensure the effectiveness of the proposed controller, the fixed time convergence of both sliding and reaching phases is investigated and proven. Finally, a robust prediction based sliding mode control is designed for the PEMFC system that by incorporating the disturbance estimation, can eliminate the effect of input delay. The effectiveness and robustness of the proposed controller are validated via comparative simulations. It is noteworthy that this is the first study to propose predictor based control for input delay PEMFCs.

Simplified dynamic modeling and Fuzzy gain scheduled PID control of woodward-governor controlled grid-interactive twin-shaft gas turbine plants

Biomass-integrated gas turbines for electricity generation are competitive with coal and nuclear energy production. Gas turbine-based power generation system looks to be an excellent solution amid the emerging environmental conditions and the increased energy crisis. This paper presents a simplified dynamic analysis model for biomass-based, Woodward governor-controlled, twin-shaft heavy-duty gas turbine (HDGT) plants, alongside an intelligent controller for stability enhancement. Grid-connected HDGTs can become unstable under load disturbances, potentially causing system shutdowns. A simplified model for twin-shaft gas turbines, rated from 18.2 MW to 106.7 MW, has been identified based on control characteristics during startup. The speed controller is dominant, while the acceleration controller is only active at startup, and the temperature controller's effect is minimal during normal operation. This model suits all dynamic studies of twin-shaft gas turbines, regardless of varying power ratings and rotor time constants. For improving the grid stability, a Takagi-Sugeno-Kang (TSK) fuzzy gain scheduling PID controller has been proposed in this work and its behavior is validated with 5001M, 7001Ea, and 9001Ea models. Step response of fuzzy PID controller under load disturbances and set-point variations are compared with fixed gain PID controllers tuned by Ziegler-Nichols (ZN) and performance index-based tuning using the typical gas turbine model. Further the controller behavior is validated with field test-based model parameters as derived from the real-world combustion turbines used in Alaskan Railbelt system. Extensive research simulation and validation results reveal that the fuzzy self-tuning PID controller showed superior adaptability for grid-interactive twin-shaft HDGTs under load variations and set-point variations. Time domain specifications and the performance indices confirms that the proposed fuzzy tuned PID controller ensure reliable and stable operation for the energy management in grid-operative mode. The proposed simplified model and intelligent control logic enable various dynamic studies in grid-connected environments for both simple cycle and combined cycle operations.

Scaling behaviour of rotating convection in a spherical shell with different Prandtl numbers

Rayleigh–Bénard convection in a rotating spherical shell provides a simplified model for convective dynamics of planetary and stellar interiors. Over the past decades, the problem has been studied extensively via numerical simulations, but most previous simulations set the Prandtl number $Pr$ to unity. In this study we build more than 200 numerical models of rotating convection in a spherical shell over a wide range of $Pr$ ( $10^{-2}\le Pr \le 10^2$ ). By increasing the Rayleigh number $Ra$ , we characterise four different flow regimes, starting from the linear onset to multiple modes, then transitioning to the geostrophic turbulence and eventually approaching the weakly rotating regime. In the multiple modes regime, we show evidence of triadic resonances in numerical models with different $Pr$ , which may provide a generic mechanism for the transition from laminar to turbulence in rotating convection. We analyse scaling behaviours of the heat transfer and convective flow speeds in numerical simulations, paying particular attention to the $Pr$ dependence. We find that the so-called diffusion-free scaling for the heat transfer cannot reconcile all numerical models with different $Pr$ in the geostrophic turbulence regime. However, the characteristic flow speeds at different $Pr$ roughly follow a unified scaling that can be described by visco-Archimedean–Coriolis force balances, though the scaling tends to approach the Coriolis-inertial-Archimedean force balance at low $Pr$ . We also show that transition behaviours from rotating to non-rotating convection depend on $Pr$ . The transition criteria based on heat transfer and flow morphology would be rather different when $Pr>1$ , but the two criteria are consistent for cases with $Pr\le 1$ . Both scaling behaviours and transition behaviours suggest that the heat transfer is controlled by the boundary layers while the convective flow speeds are mainly determined by the force balance in the bulk for cases with $Pr>1$ , which is in line with recent experimental results with moderate to high $Pr$ . For cases with $Pr \le 1$ , both the heat transfer and convective velocities are approaching the inviscid dynamics in the bulk. We also briefly analysed the magnitude and scaling of zonal flows at different $Pr$ , showing that the zonal flow amplitude rapidly increases as $Pr$ decreases.

A simple dynamic time constant model for both summer overheating and winter heating analysis

As new buildings have high levels of insulation it is important to ensure that solar and other internal gains do not make the interiors too hot in summer. This is well known. But assessing overheating at an early design stage is not so easy. The Thermal Mass Parameter (TMP) in the regulations is based on a 24 h cyclic assessment of the depth of heat storage in a material. This paper examines a simpler method using the whole thermal mass, simple steady state calculations and a time constant that can take into account the heat gains over a number of days, such as in a heat wave, not just over 24 h. This simple dynamic time constant model (SDTCM) would be a more realistic model to assess overheating and performance for Future Homes and Buildings Standards, now under consultation in the UK. The model can equally be applied to assess winter heating and for dynamic simulation to consider control strategies. Practical application This paper describes a simple model that can be used for determining heating sizing in winter and overheating in summer. It relates to assessing the thermal mass via the time constant relating to the dynamic response of the building. This will be useful in initial design and possibly regulation.

The formation and ventilation of an oxygen minimum zone in a simple model for latitudinally alternating zonal jets

Abstract. An advection–diffusion model coupled to a simple dynamical ocean model is used to illustrate the formation and ventilation of an oxygen minimum zone. The advection–diffusion model carries a passive tracer with a source at the western boundary and a Newtonian damping term to mimic oxygen consumption. The dynamical model is a non-linear one-and-a-half-layer reduced-gravity model. The latter is forced by an annually oscillating mass flux confined to the near-equatorial band that, in turn, leads to the generation of mesoscale eddies and latitudinally alternating zonal jets at higher latitudes. The model uses North Atlantic geometry and develops a tracer minimum zone remarkably similar in location to the observed oxygen minimum zone in the eastern tropical North Atlantic (ETNA). This is despite the absence of wind forcing for a subtropical gyre and the shadow zone predicted by the ventilated thermocline theory. Although the model is forced only at the annual period, the model nevertheless exhibits decadal and multidecadal variability in its spun-up state. The associated trends are comparable to observed trends in oxygen within the ETNA oxygen minimum zone. Notable exceptions are the multi-decadal decrease in oxygen in the lower-oxygen minimum zone and the sharp decrease in oxygen in the upper-oxygen minimum zone between 2006 and 2013.

System Dynamics Model of CO2 Pollution Stocks Changes Due to Emissions and Absorbent in Indonesia

Air pollution, including CO2 pollution, is a serious issue worldwide, including in Indonesia. This CO2 pollution can impact public health and the environment. In the context of economic development, activities in Indonesia are increasing, leading to higher CO2 emissions. The highest CO2 emissions come from deforestation, large-scale peatland fires, and, to a lesser extent, burning fossil fuels for energy. This research focuses on a simple System Dynamics model approach to understand the cause-and-effect relationship of changes in CO2 pollution stocks concerning emissions and absorption in Indonesia. The method used in this study is qualitative based on system dynamics. System dynamics is a method that can be used to create structures, predict behavior, and provide feedback. The System Dynamics model uses Powersim Studio 10 Express, covering the research period from 2020 to 2040. The results of the system dynamics model show two structures related to CO2 pollution stocks: a positive feedback (reinforcing loop) from CO2 emissions and a negative feedback (balancing loop) from CO2 absorbent. The behavior of the model is exponential growth, it’s also considered valid due to simulation results based on real data processing and statistical analysis, yielding an Average Means Error (AME) of 0.56%.

Dynamics System Modeling of Declining Agricultural Land Area Potentially Causing Jakarta Flood Disaster

The change or evolution of land use in the DKI Jakarta area has caused various environmental problems in the city that have an impact on disasters that occur from time to time. The conversion of agricultural land that has a relatively high ability to absorb water into built-up land has reduced the water absorption capacity because the built-up area is increasingly impermeable which is at risk of causing flood disasters. This research focuses on a simple dynamic system modeling approach to understand the cause-and-effect relationship of the decline in agricultural land area in the DKI Jakarta area. The method used in this research is a qualitative-based dynamic system, dynamic system is a method that can be used to form structures and predict behavior and feedback. Dynamic system modeling using Powersim Studi 10 Express software uses time specifications ranging from 2020 to 2070. The results of the dynamic system model of agricultural land decline can be said to be valid, where the dominant structure formed is Negative Feedback (Balancing Loop) with Exponential Decay behavior and Average Means Error (AME) test results obtained a value of 29.6%

Nonlinear model predictive control for maximum wind energy extraction of semi-submersible floating offshore wind turbine based on simplified dynamics model

The application of floating offshore wind turbines means better exploitation of offshore wind resources. However, the six-degree of freedom motion characteristics of floating platforms bring greater challenges to control system design. Based on the dynamic characteristics of semi-submersible floating offshore wind turbines, this paper establishes a simplified nonlinear dynamic model for control system design. On this basis, a complete framework for nonlinear model predictive control of maximum wind energy extraction for semi-submersible floating offshore wind turbines considering wind and wave disturbances is developed. Based on the previewed wind and wave, a dynamic optimization problem with both state and control constraints is constructed, considering maximum wind energy extraction and torque fluctuation. Then, an improved equilibrium optimizer is proposed to address the nonlinear non-convex dynamic optimization problems, which achieves a better trade-off between exploitation and exploration. Simulation results verify the superiority of the proposed nonlinear model predictive control framework via the improved equilibrium optimizer, and the influences of different control algorithms on the platform motion state, power coefficient, and equivalent wind speed are analyzed.

Longitudinal vibrations and their suppression of a tethered satellite system using friction self-excitation mechanism

This paper proposes a friction self-excitation mechanism to regulate the longitudinal vibrations of the tether during the state-keeping phase of a two-body tethered satellite system. A simplified dynamic model is established, consisting of two mass blocks, a constant-length tether, and a conveyor belt. The Stribeck friction model is utilized to describe the effects of friction on the stability of longitudinal vibration. Numerical simulations reveal the instability phenomenon induced by Hopf bifurcation and indicate the potential self-excited vibration under different parameters. Additionally, the paper explores the design approach for the tether by introducing the concept of segmented tethering and its dynamic behavior under different design scenarios. Varying the stiffness of the tether can change the vibration modes of the system. Finally, a ground experiment is carried out to evaluate the dynamic behaviors of the system and to demonstrate the effectiveness of the proposed vibration suppression mechanism.

A Simplified Dynamic Model of DFIG-based Wind Generation for Frequency Support Control Studies

In recent years, wind generation has been fast growing and become one of the major generation resources in power systems. Since the wind generation does not inherently equip with frequency support functions, the power system frequency response degrades as the wind penetration increases. Therefore, frequency support control of wind generation has gained increasing focus. However, the dynamic models of wind generation systems, which are required by the control design and analysis, are commonly very complicated and difficult to obtain, especially for the doubly-fed induction generator based wind turbine (DFIG-WT). In this paper, the authors propose a simplified dynamic model for the DFIG-WT. The proposed analytical model is derived from the detailed model by selectively neglecting very fast dynamics while keeping the critical ones. It is suitable for frequency control studies. The model accuracy is first validated against the detailed DFIG-WT model in Simulink. Then, the wind frequency control function is studied based on the proposed model.

Research on digital vibration model of typical components in pipe system

The spatial distribution of pipe system is complex, long span and multi-point elastic support, so vibration analysis of pipe system is required in the pipeline design. This paper takes the pipe system as a typical component, based on the Timoshenko beam model, establishes a dynamic procedure for straight pipe elements that considers the axial flow rate of fluid, the pressure on the pipe wall, the Poisson coupling effect of fluid and pipeline structure, and the axial, transverse and torsional vibration. Through Laplace transform, the frequency simplified dynamic model is established. And the frequency transfer matrix model of straight pipe elements and the boundary constraint matrix of common boundary (such as fixed support) is established. Finally, the frequency domain transfer matrix model of different pipeline elements are set to the overall transfer matrix of the flow pipe system, providing a convenient means for rapid optimization of pipe system vibration.

A thermal flexible rotor dynamic modelling for rapid prediction of thermo-elastic coupling vibration characteristics in non-uniform temperature fields

The flexible rotors within aero-engines operate in complex thermal environments, where temperature influences both the vibration frequency and amplitude. This study establishes a simple thermal flexible rotor dynamics model to rapidly and precisely predict thermo-elastic coupling vibration characteristics within a non-uniform temperature field. The thermal potential energy of the thermal rotor element is derived for any temperature field, and the motion equation is obtained using the Euler-Lagrange equation. Specifically, the generalized vector of an arbitrary point and cross-sectional non-uniform thermal stress of the thermal rotor element are considered in the thermal potential energy. The model's frequency error is less than 1% under identical boundary conditions. Numerical findings indicate that thermal stress, temperature-dependent material properties, and the coupling effect collectively reduce the natural frequency (NF), with thermal stress having a more pronounced impact under axial constraint. Additionally, thermal stress and material decrease the amplitude across a broad range of rotation speeds, contrasting with thermal bending. This model will play a key role in the iterative calculation of thermo-elastic coupling vibration control due to its accuracy and simplicity.

Emergent ecological patterns and modelling of gut microbiomes in health and in disease.

Recent advancements in next-generation sequencing have revolutionized our understanding of the human microbiome. Despite this progress, challenges persist in comprehending the microbiome's influence on disease, hindered by technical complexities in species classification, abundance estimation, and data compositionality. At the same time, the existence of macroecological laws describing the variation and diversity in microbial communities irrespective of their environment has been recently proposed using 16s data and explained by a simple phenomenological model of population dynamics. We here investigate the relationship between dysbiosis, i.e. in unhealthy individuals there are deviations from the "regular" composition of the gut microbial community, and the existence of macro-ecological emergent law in microbial communities. We first quantitatively reconstruct these patterns at the species level using shotgun data, and addressing the consequences of sampling effects and statistical errors on ecological patterns. We then ask if such patterns can discriminate between healthy and unhealthy cohorts. Concomitantly, we evaluate the efficacy of different statistical generative models, which incorporate sampling and population dynamics, to describe such patterns and distinguish which are expected by chance, versus those that are potentially informative about disease states or other biological drivers. A critical aspect of our analysis is understanding the relationship between model parameters, which have clear ecological interpretations, and the state of the gut microbiome, thereby enabling the generation of synthetic compositional data that distinctively represent healthy and unhealthy individuals. Our approach, grounded in theoretical ecology and statistical physics, allows for a robust comparison of these models with empirical data, enhancing our understanding of the strengths and limitations of simple microbial models of population dynamics.

Gasification of mixed plastic-biomass pellets in an updraft fixed bed reactor: A simplified dynamic model

In the context of materials recycling, updraft gasifiers are promising small and middle-scale reactors to obtain building blocks and/or energy from waste plastic and biomasses. To this aim, these kinds of materials can also be mixed and reduced into pellets, while the needed heat enters the process with a heated carrier gas. In order to preliminarily design a gasifier to check its feasibility with an available feedstock, currently available models are inadequate. Thermodynamic ones are useless for the purposes of sizing, while too detailed rate-based models (e.g. based on fluid-dynamic modelling) are too substrate specific, need detailed input data and are extremely time consuming. A dynamic model of a fixed-bed reactor for biomass gasification is presented here. The gasifier is loaded continuously from the top with solid pellets and fed with counter-current air flow. The model considers: i) a one-step gasification kinetics, yielding a product spectrum which matches experimental data from the literature; ii) dynamic gas and solid energy balances and iii) steady-state energy balance for the furnace. The model has been applied to describe a tubular furnace (Ø 40 cm) which gasifies 500–1000 kg day−1 of mixed wastes using air heated up to 1200 °C: on the basis of the produced chemicals, the energy consumption was estimated as ca. 2 MJ per kg of solid feedstock. This simplified approach proved robust in describing the overall yields and start-up dynamics, showing higher reliability than equilibrium models in addressing the temperature profiles, at the cost of a simplified reaction kinetic and pellet description with respect to more complex simulation models. The model validation was done by comparison between the calculations results and available pilot-plant data. An overall good fit of the data can be concluded. The solid-gas heat transfer and the bed packing are the main computational criticalities to achieve a reliable process description.

Balance Controller Design for Inverted Pendulum Considering Detail Reward Function and Two-Phase Learning Protocol

As a complex nonlinear system, the inverted pendulum (IP) system has the characteristics of asymmetry and instability. In this paper, the IP system is controlled by a learned deep neural network (DNN) that directly maps the system states to control commands in an end-to-end style. On the basis of deep reinforcement learning (DRL), the detail reward function (DRF) is designed to guide the DNN learning control strategy, which greatly enhances the pertinence and flexibility of the control. Moreover, a two-phase learning protocol (offline learning phase and online learning phase) is proposed to solve the “real gap” problem of the IP system. Firstly, the DNN learns the offline control strategy based on a simplified IP dynamic model and DRF. Then, a security controller is designed and used on the IP platform to optimize the DNN online. The experimental results demonstrate that the DNN has good robustness to model errors after secondary learning on the platform. When the length of the pendulum is reduced by 25% or increased by 25%, the steady-state error of the pendulum angle is less than 0.05 rad. The error is within the allowable range. The DNN is robust to changes in the length of the pendulum. The DRF and the two-phase learning protocol improve the adaptability of the controller to the complex and variable characteristics of the real platform and provide reference for other learning-based robot control problems.

Onset of Intragroup Conflict in a Generalized Model of Social Balance.

Dynamically changing interpersonal relationships lie at the core of the emergence of in-group structures, such as polarity or conflict. We explore these dynamics in a simple continuous dynamical model obtained by generalizing a previously proposed model based on Heider's balance theory from social psychology. Previous findings include a rigorous proof of the emergence of in-group harmony or bipolar conflict (global minima) and the identification of local minima called jammed states, along with their corresponding energy spectrum in terms of structural complexity. However, some unrealistic scenarios constrain our capacity to contextualize and directly apply these results to real-world social behaviors. To address these challenges, we first introduce a unified dynamical model and find that group size can be critical to the onset of in-group bipolar conflict. Using random matrix statistics, we then characterize the pathways leading to jammed states, which have previously been discussed only in stochastic models. Unexpectedly, we also show that perturbing our dynamical model can increase the chances of getting trapped in jammed states, giving rise to a novel notion called the noise-induced jammed state. We conclude this Letter by discussing possible real-world implications as well as potential contributions to the existing literature in relevant fields such as anthropology.

A Simplified 4-DOF Dynamic Model of a Series-Parallel Hybrid Electric Vehicle

To research the dynamic response of a new type of dedicated transmission for a hybrid electric vehicle, a detailed dynamics model should be built. However, a model with too many degrees of freedom has a negative effect on controller design, which means the detailed model should be simplified. In this paper, two dynamic models are established. One is an original and detailed powertrain dynamics model (ODPDM), which can capture the transient response, and it is validated that the ODPDM can be used to accurately describe the real vehicle in some specific operating conditions. The other is a simplified torsional vibration dynamics model to study the torsional vibration characteristics of the hybrid electric vehicle. Compared with the full-order model, which is based on the ODPDM, the simplified model has a very similar vibration in low frequency. This study provides a basis for further vibration control of the hybrid powertrain during the process of a driving-mode switch.

Virtual track irregularity establishment for load prediction of heterogeneous bogie frames for virtually coupled trainsets

In this paper, we establish the virtual track irregularity (VTI) considering suspension system dynamics for load prediction of heterogeneous bogie frames for virtual coupled train sets (VCTS). At first, the dynamic characteristics of axlebox spring set and primary suspension vertical damper of A/B-type high-speed trains are analyzed and compared for establishment of frequency-varying parameter simplified vehicle dynamic models (FVP-SVDMs). Then, a frequency-segmented time-domain inversion (FSTIM) of VTI suitable for FVP-SVDMs is conducted, and a quantitative evaluation method for VTI consistency is established. Finally, the consistency of VTIs based on measured loads of A/B-type high-speed train bogie frames is quantitatively assessed, and the agreement between the measured and predicted load spectra based on VTI is evaluated. Based on the FVP-SVDM and the corresponding VTI, the equivalent load amplitude error between the predicted and measured bouncing load is 7%. The VTI technology provides the possibility for VCTS to eliminate the need for conducting the main test before applying the new vehicles on the line. In addition, for the fleet is running on the same track through the VCTS communication, the VTI will provide the theoretical support for implementing active control across the entire fleet.