Road Disturbance Research Articles

Active disturbance rejection control for reducing vehicle body displacement based on an extended state observer and dynamic fuzzy techniques

This article presents a hybrid control method for an automotive suspension system to improve smoothness and comfort and eliminate the influence of sensor noise. The proposed algorithm is formed by combining an active disturbance rejection control technique and a dynamic fuzzy technique based on an extended state observer. The article’s novel contribution is to propose a solution for determining a reference signal and adjusting control parameters using soft computing techniques. Simulations are performed in three cases (corresponding to three types of road excitation signals) to validate the performance of the proposed algorithm. According to the calculation results, the displacement and acceleration of the vehicle body are significantly reduced when the proposed technique is applied to control the active suspension system. The error of the road disturbance observed by the extended state observer does not exceed 0.5 mm, while the error of the vehicle body displacement is less than 0.001 mm. In addition, the chattering phenomenon caused by sensor noise is completely eliminated once the proposed algorithm controls the active suspension system. In conclusion, the algorithm introduced in this work provides superior performance over traditional control methods, which is validated by simulation results.

Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique.

Road surface roughness is the cause of vehicle vibration, which is considered a system disturbance. Previous studies on suspension system control often ignore the influence of disturbances while designing the controller, leading to system performance degradation under severe vibration conditions. In this work, we propose a control method to improve active suspension performance that reduces vehicle vibration by eliminating the influence of road disturbances. The proposed method is formed based on the combination of an Active Disturbance Rejection Control (ADRC) technique with control coefficients tuned by a dynamic fuzzy technique formed based on special membership functions called Active Disturbance Rejection Control Based on Fuzzy (ADRCBF). An Extended State Observer (ESO) estimates state variables and disturbances. The performance of the proposed controller is evaluated through the numerical simulation process with three different cases. According to the calculation results, the acceleration and displacement of the sprung mass are significantly reduced when the suspension system is controlled by the proposed technique, compared with the passive suspension system and the active suspension system controlled by a Proportional-Integral-Derivative (PID) technique. In addition, the suspension travel follows the road disturbance with a small error. The error estimated by the ESO does not exceed 3.5% (for sinusoidal and random excitation). In general, system adaptation is ensured under many investigated conditions based on tuning the controller parameters by the soft computing method.

Lead compensator with proportional derivative control for lane keeping assistance system in presence of road disturbances

Advanced Driver Assistance Systems (ADASs) hold the potential to significantly reduce the number of road fatalities while enhancing vehicle safety and stability. A prominent feature of ADAS is the Lane Keep Assistance System (LKAS), designed to prevent unintended lane departures and ensure vehicles stay within their designated lanes, thereby safeguarding passengers. This research is centered on developing a lead/lag compensator for the robust design of a PID controller dedicated to lane keeping assistance control. The compensator-PD controller enhances lane tracking performance while ensuring vehicle stability is maintained. The gains of the PD controller are tuned using the Ziegler–Nichols method to achieve robustness in presence of road disturbances. The performance of the proposed controller was compared with that of a PID controller without any compensator and a fuzzy PID controller across variable speed conditions and the presence of sharp road curvature disturbances. Based on extensive simulation studies in MATLAB/SIMULINK environment the performance of all above controllers was evaluated. The proposed compensator based controller outperforms the existing designs by ensuring minimum tracking error.

Temporal effects of road disturbance on the spread of non‐native plants and arbuscular mycorrhizal fungi in subarctic mountain ecosystems

Roads in cold climate mountains are known to be important vectors in the introduction and spread of non‐native plant species. In the same context, mycorrhizal fungi communities are altered by roads, with a known positive effect on arbuscular mycorrhizal (AM) fungi diversity and abundance in disturbed roadsides. However, to what degree these two effects of roads are intertwined and how they are evolving over time is not well understood. In this study we conducted repeated surveys of non‐native plants and AM fungi between 2012 and 2022, in the northern Scandes mountains to investigate temporal changes and interactions between roads, mycorrhizal fungi and non‐native plants. We found that the upward spread of non‐native plants and lateral spread away from the roadside into the natural vegetation were so far extremely limited, with only two out of 23 non‐native species showing an increase in their upper elevational limit. However, non‐native plant species cover did increase over the ten year period, especially at lower elevations, and non‐native richness increased from 17 to 23 species. Likewise, we saw an increase in AM fungal abundance over the last four years along the roadsides at lower elevations. Furthermore, our results suggest that increases in non‐native species are unlikely to be the driving cause of the observed increase in AM fungal abundance, as AM fungi colonization varied independently of non‐native species cover dynamics.

On Adaptive Fractional Dynamic Sliding Mode Control of Suspension System

This paper introduces a novel adaptive control method for suspension vehicle systems in response to road disturbances. The considered model is based on an active symmetry quarter car (SQC) fractional order suspension system (FOSS). The word symmetry in SQC refers to the symmetry of the suspension system in the front tires or the rear tires of the car. The active suspension controller is generally driven by an external force like a hydraulic or pneumatic actuator. The external force of the actuator is determined using fractional dynamic sliding mode control (FDSMC) to counteract road disturbances and eliminate the chattering caused by sliding mode control (SMC). In FDSMC, a fractional integral acts as a low-pass filter before the system actuator to remove high-frequency chattering, necessitating an additional state for FDSMC implementation assuming all FOSS state variables are available but the parameters are unknown and uncertain. Hence, an adaptive procedure is proposed to estimate these parameters. To enhance closed-loop system performance, an adaptive proportional-integral (PI) procedure is also employed, resulting in the FDSMC-PI approach. A comparison is made between two SQC suspension system models, the fractional order suspension system (FOSS) and the integer order suspension system (IOSS). The IOSS controller is based on dynamic sliding mode control (DSMC) and a PI procedure (DSMC-PI). The results show that FDSMC outperforms DSMC.

Integral sliding-mode based interval type-2 fuzzy control for efficient networked nonlinear active suspension systems with input uncertainty

An event-triggered integral sliding mode control (ETISMC) approach for the networked nonlinear active suspension systems (ASSs) via interval type-2 (IT-2) T-S fuzzy logic is investigated in this paper. Firstly, in order to deal with the uncertainty in system masses, the nonlinearity of the suspension spring stiffness and damping coefficient, and the unknown actuator nonlinearity simultaneously, an ASSs model based on the IT-2 T-S fuzzy method is constructed. Secondly, a discrete event-triggered method is designed to process the sampled data and reduce the usage of vehicle CAN network communication resources. Thirdly, the H infinity robust method is used to handle the road disturbance and the sliding mode control (SMC) is adopted to deal with the actuator input uncertainty. To better integrate the SMC and event-triggered control (ETC), an ETISMC approach is explored for the ASSs. Finally, the numerical simulations and experiments are conducted to validate the effectiveness of the proposed strategy in this work.

Robust Static Output Feedback Control of a Semi-Active Vehicle Suspension Based on Magnetorheological Dampers

This paper proposes a novel design method for a magnetorheological (MR) damper-based semi-active suspension system. An improved MR damper model that accurately describes the hysteretic nature and effect of the applied current is presented. Given the unfeasibility of installing sensors for all vehicle states, an MR damper current controller that only considers the suspension deflection and deflection rate is proposed. A linear matrix inequality problem is formulated to design the current controller, with the objective of enhancing ride safety and comfort while guaranteeing vehicle stability and robustness against any road disturbance. A series of experiments demonstrates the enhanced performance of the proposed MR damper model, which exhibits greater accuracy than other state-of-the-art damper models, such as Bingham or bi-viscous. An evaluation of the vehicle behavior under two simulated road scenarios has been conducted to demonstrate the performance of the proposed output feedback MR damper-based semi-active suspension system.

Resistance of plant diversity to road disturbance: Evidence from the Tibetan Plateau

The expansion of road networks in recent decades has drawn considerable attention due to its impact on biodiversity in high-altitude ecosystems. Here, we conducted a comprehensive field survey to investigate the effects of road disturbance on plant diversity in alpine grasslands on the Tibetan Plateau. Our results indicate that road disturbance caused no significant changes in species richness, Shannon–Wiener’s diversity, or Simpson’s diversity, and the alteration in species composition was limited. These findings demonstrate the robust resistance of alpine grassland plant diversity to road disturbance. Plant diversity exhibited more resistance to road disturbance in regions with more hostile environments, such as plateau sub-frigid regions and alpine steppes. Our study suggests that road construction in the Tibetan Plateau poses limited risk to plant biodiversity.

Cargo E-Bike Robust Speed Control Using an MPC Battery Thermal Lumped Model Approach

Cargo e-bikes are expected to convey heavy loads in all aspects of daily life. Also, these vehicles are expected to maintain a consistent speed to meet mobility needs while optimizing the battery design. In this paper, a control model is developed to improve rotational speed motor control via the battery model predictive controller (MPC) thermal model designed based on experimental field test data. Experimental field tests are performed to provide the relation between battery surface and ambient temperatures in different road types and weight conditions. For this purpose, in different slope ranges, the pedal load/activity and voltage-current data are logged to use as experimental input in an MPC-integrated 1D model. To obtain the desired thermal conditions in the Li-Ion battery, the MPC battery thermal model is defined based on the thermal lumped model approach. In the next step, the generated MPC model is used as a function for longitudinal speed control in the MPC motor torque control model subjected to uncertain road disturbances. Then, the outputs of the control models are compared using the MPC parameters oc weight factors and prediction horizon. Thus, the speed control model for cargo e-bikes is presented with increased robustness using the MPC battery thermal lumped model approach considering energy and Li-Ion battery life-cycle efficiency methods regardless of driving performance needs.

H∞ Differential Game of Nonlinear Half-Car Active Suspension via Off-Policy Reinforcement Learning

This paper investigates a parameter-free H∞ differential game approach for nonlinear active vehicle suspensions. The study accounts for the geometric nonlinearity of the half-car active suspension and the cubic nonlinearity of the damping elements. The nonlinear H∞ control problem is reformulated as a zero-sum game between two players, leading to the establishment of the Hamilton–Jacobi–Isaacs (HJI) equation with a Nash equilibrium solution. To minimize reliance on model parameters during the solution process, an actor–critic framework employing neural networks is utilized to approximate the control policy and value function. An off-policy reinforcement learning method is implemented to iteratively solve the HJI equation. In this approach, the disturbance policy is derived directly from the value function, requiring only a limited amount of driving data to approximate the HJI equation’s solution. The primary innovation of this method lies in its capacity to effectively address system nonlinearities without the need for model parameters, making it particularly advantageous for practical engineering applications. Numerical simulations confirm the method’s effectiveness and applicable range. The off-policy reinforcement learning approach ensures the safety of the design process. For low-frequency road disturbances, the designed H∞ control policy enhances both ride comfort and stability.

Investigating the Influence of Anthropogenic Activities on Behavioral Changes of an Orb Web Spider (Neoscona vigilans).

Orb web spiders are common and highly diversified animals found in almost all habitats. They have remarkable plasticity against biotic and abiotic factors, making them excellent indicators of environmental health. The web creation behavior of spiders is influenced by disturbances in the environment. The aim of this research was to observe the alteration in the web-building behavior of Neoscona vigilans caused by human activities, specifically traffic disturbances. Spider webs were located and photographed at nighttime along the roadside, and their web characteristics were calculated. Spiders were captured from webs for their body measurements. Spider fourth leg length, carapace width, and body length had a significant association with web size and diameter, CTL, capture area, and mesh size. The quantity of trapped prey, the height of the plant, and the foliage radius increased with the distance from the road. Conversely, anchor points and web elevation from the ground dropped. The highest and lowest proportions of anomalies (modifications/defects) were recorded as holes (52.7%) in 105 webs (100%) and supernumerary (0.7%) in 55 webs (52.4%), respectively. Road disturbance had a negative influence on the spider's behavior as the webs formed in close proximity to the road had a higher frequency of anomalies, with a gradual decrease distantly. We can gain further insight into how different environmental changes, disruptions, and pollutants lead to this imperfection in the otherwise flawless perfect structure of spider webs.

Should I stay or move? Quantifying landscape of fear to enhance environmental management of road networks in a highly transformed landscape

The development and expansion of road networks pose considerable threats to natural habitats and wildlife, fostering a landscape of fear. In addition to direct mortality caused by road collisions, road construction and maintenance often result in habitat fragmentation and loss, impeding animal movement and gene flow between populations. Mountain ungulates are already confined to fragmented habitat patches and roads can cause substantial disturbances to their critical ecological processes, such as dispersal and migration. In this study, we employed two key mountain ungulates, the wild goat (Capra aegagrus) and mouflon (Ovis gmelini), as functional models to examine how road networks impact the quantity and connectivity of natural habitats in southwestern Iran, where extensive road construction has led to significant landscape changes. We used the MaxEnt method to predict species distribution, the circuit theory to evaluate habitat connectivity, and the Spatial Road Disturbance Index (SPROADI) to assess road impacts. During the modeling process, we selected eleven important variables and employed a model parametrization strategy to identify the optimal configuration for the MaxEnt model. For SPROADI index we used three sub-indices, including traffic intensity, vicinity impact, and fragmentation grade. We then integrated the results of these analyses to identify areas with the most significant environmental impacts of roads on the coherency of the natural habitats. The findings indicate that suitable habitats for wild goats are widely distributed across the study area, while suitable habitats for mouflon are primarily concentrated in the northeastern region. Conservation gap analysis revealed that only 8% of wild goat habitats and 7% of mouflon habitats are covered by protected areas (PAs). The SPROADI map highlighted that 23% of the study area is negatively influenced by road networks. Moreover, 30.4% of highest-probability corridors for mouflon, and 25.7% for wild goat, were highly vulnerable to the impacts of roads. Our combined approach enabled us to quantitatively assess species-specific vulnerability to the impacts of heavy road networks. This study emphasizes the urgent need to address the negative effects of road networks on wildlife habitats and connectivity corridors. Our approach effectively identifies sensitive areas, which can help inform mitigation strategies and support more effective conservation planning in significantly transformed landscapes.

Hybrid coati–grey wolf optimization with application to tuning linear quadratic regulator controller of active suspension systems

Vehicle suspension systems have become increasingly crucial for both driving safety and comfort. Active suspension systems can dynamically adjust suspension characteristics in real-time by introducing force into the system. Designing a controller for the real-time adjustment of the control force in active suspension systems is essential to meet challenging control objectives, including body acceleration, suspension deflection, and tire deflection. This article proposes a hybrid optimization approach named Coati–Grey Wolf Optimization (COAGWO), which combines the strengths of the coati optimization algorithm and grey wolf optimization to tune the gains of linear quadratic control applied to vehicle suspension systems. The COAGWO algorithm incorporates a unique strategy inspired by the Coati Optimization Algorithm, allowing wolves to climb trees. This enhancement significantly improves the wolves’ ability to explore the global search space and reduces the likelihood of being trapped in local optima. Initially, we conduct extensive experiments using a suite of challenging optimization problems from the CEC2019 benchmark to evaluate the effectiveness of the COAGWO algorithm. The effectiveness of COAGWO is compared against several state-of-the-art algorithms, including grey wolf, coati, aquila-grey wolf, whale, reptile search, tunicate swarm, and seagull optimization algorithms. The experimental results demonstrate that COAGWO consistently outperforms these algorithms in terms of solution quality and convergence speed. For the optimal weight selection problem of linear quadratic control applied to the control of vehicle suspension systems, the excellent performance of the proposed method is illustrated through comparative simulation studies under various road disturbance conditions. The results indicate that the COAGWO algorithm achieves a more efficient active suspension system compared to competitor algorithms by reducing the overall acceleration of the driver’s body, thereby enhancing ride comfort.

SIMULATION STUDY ON PARAMETRIC MODELLING OF MAGNETORHEOLOGICAL DAMPER SYSTEM

The Magnetorheological (MR) damper system serves as a semi-active suspension system designed to absorb road disturbances. This research aims to replicate the MR damper system through a parametric modeling approach, specifically employing the Simple Bouc-Wen Model, Spencer Model, and Hyperbolic-Tangent Model. The objective of this paper is to assess the effectiveness of these modeled MR damper systems with the utilization of a Fuzzy-PID controller. The simulation process is conducted within MATLAB Simulink, whereby a block diagram is devised based on equations related to the suspension system and the parametric models. The inputs for the system encompass sinusoidal and bump road profiles. The outcomes from the modeled MR damper systems reveal that the semi-active suspension system outperforms the passive suspension system. The primary simulation metrics under consideration include sprung displacement, sprung acceleration, and unsprung acceleration. Among the three MR damper models, the Hyperbolic-tangent model displays the most favorable performance, with a mean squared error of 51.44%, while the Bouc-Wen model exhibits the least favorable performance, registering a mean squared error of 25.96%. The integration of the Fuzzy-PID controller demonstrates an enhancement in the sprung suspension system, though the sprung acceleration remains relatively unchanged.

Unraveling community assembly in temperate desert ecosystems: Insights from multi‐seasonal surveys along the expressway

AbstractFor temperate desert ecosystems, understanding the maintenance mechanisms of biodiversity has become a central concern of policymakers, practitioners, and academicians, especially in the context of human disturbances. However, most of the past desert research is based on a single survey and single functional traits or phylogeny, and may lead to incomplete estimates of community assembly. To assess climate factors, soil factors, and human interference in the processes of dispersal assembly, filtering, and limiting similarity in community assembly, we selected 50 sites along the Beijing‐Xinjiang Expressway and conducted plant surveys at sites 0.5, 1.0, and 1.5 km away from the expressway twice, one in spring and one in autumn, and collected 31 functional traits and phylogenetic information of 74 species. We found that incomplete detection can lead to bias in biodiversity estimation due to seasonal surveys. Road disturbance at different distances had no significant effect on species composition and community assembly processes. The trade‐off between dispersal limitation and environmental filtering is the process of maintaining desert plant diversity. Precipitation directly determined the dispersal limitation and environmental filtering. Soil pH mediated the effect of temperature on biotic interaction in the dimension of phylogeny, while soil pH and organic carbon acted as intermediate factors affecting biotic interaction in functional traits. Our findings suggest that climate change, notably precipitation, has a more pronounced impact on desert plant communities than human disturbances. A multifaceted approach considering functional traits and phylogeny across seasons is essential for understanding species coexistence in desert ecosystems.

Optimization and comparative analysis of an AISD suspension system with inerter element for enhanced ride and handling

This paper presents a comprehensive study on the modeling and optimization of an advanced suspension system, known as the Air Springs Inerter-Spring-Damper (AISD) system, incorporating an inerter element. A linear quarter car model is utilized to analyze the vibrational behavior of the AISD system when subjected to harmonic road disturbances. The steady-state response of the system is investigated by deriving the root mean square (RMS) values of the absolute relative displacement and acceleration of the sprung mass. To optimize the quarter car model, a criterion based on minimizing the absolute acceleration RMS while considering the relative displacement RMS is employed to calculate the inerter coefficient. The performance of the AISD suspension system is compared to that of both conventional quarter car systems and traditional air quarter car systems, with a focus on ride comfort and handling. The results demonstrate that the proposed AISD system outperforms the other two suspension systems, exhibiting a significant improvement in ride quality. Specifically, the AISD system achieves a 45% enhancement over the air suspension and an 82% improvement over the classic suspension system.

Adaptive optimal control system design for semi-active suspension system by supposing variable parameters under exogenous road disturbance

Adaptive optimal control system design for semi-active suspension system by supposing variable parameters under exogenous road disturbance

Roadside disturbance promotes plant communities with arbuscular mycorrhizal associations in mountain regions worldwide

We assessed the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes. We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal–plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments. Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid‐mycorrhizal (ErM) associations. Furthermore, non‐native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations. These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM‐dominated systems, where AM‐fungi might aid AM‐associated plant species while potentially reducing the biotic resistance against invasive non‐native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make‐up of EcM‐ and ErM plant communities induced by roadside disturbance.

Reliable [formula omitted] fuzzy control for fault-tolerant actuator failures of active suspension system

A new methodology for fault tolerant control (FTC) is proposed to compensate actuator failures using Takagi–Sugeno systems. This makes possible to design the controller that represents actuator failures using a scaling factor by solving a family of linear matrix inequalities (LMIs). The resulting control system guarantees asymptotic stability, compensates the effect of actuator faults and ensures certain an H∞ performance level. This methodology is applied to the active suspension systems that motivated this research, where in the context of active suspension (AS) systems, the guaranteed performance correspond to ride comfort in the presence of road disturbances. Thus, a controller is developed for a quarter-car model with active suspension. The simulated results illustrate the effectiveness of the proposed approach.

Advanced active suspension control: A three-input fuzzy logic approach with jerk feedback for enhanced performance and robustness

Active suspension systems aim to increase ride comfort by reducing body acceleration due to road disturbances. This research proposes a new fuzzy logic controller (FLC) for such systems which includes acceleration error as third input. The objective of the proposed 3-inputs FLC is to improve vehicle comfort and ensure passenger safety. To assess the performances of the newly introduced controller, a theorical study is conducted on a quarter-car system with a four-wheel independent suspension design. Simulation results demonstrate high performances of the proposed 3-inputs FLC compared with conventional PID and 2-inputs FLC. The acceleration error as an additional FLC input was, to the best of our knowledge, not explored yet. Hence, this contribution offers a new method for the design of more effective active suspension systems.