Wheel Slip Research Articles

Adaptive robust control with slipping parameters estimation based on intelligent learning for wheeled mobile robot

The widespread use of wheeled mobile robots (WMRs) in many fields has created new challenges. A critical issue is wheel slip, which, if not accurately determined and controlled, causes instability and deviation from the robot’s path. In this paper, an intelligent approach for estimating the longitudinal and lateral slip of wheels is proposed that can effectively compensate for the negative effects of slippage. The proposed algorithm relies on three regression networks to estimate the longitudinal slip ratio of the right and left wheels and sideslip angle on terrains with different friction coefficients. The datasets collected during tests on different surfaces with various maneuvers are used to train the artificial neural networks (ANNs). A developed dynamic model of a WMR considering wheel slip and modified traction force is presented. The adaptive robust controller, based on sliding mode control (SMC), is introduced to deal with the problems related to slipping, unknown uncertainties, and disturbances. The simulation results demonstrate that the presented controller has better performance than SMC in handling external disturbances and uncertainties, which leads to reduction in tracking error and faster convergence to zero. The proposed controller with an intelligent slip estimator, has been applied to a four-wheel mobile robot to demonstrate its effectiveness and feasibility. The high accuracy of slip estimation in the mentioned intelligent algorithm has resulted in the presented method being on average 26% more effective in reducing the tracking error than the control method without slip compensation in each test for circular trajectory.

Modeling of slip rate-dependent traversability for path planning of wheeled mobile robot in sandy terrain

A planetary exploration rover has been employed for scientific endeavors or as a precursor for upcoming manned missions. Predicting rover traversability from its wheel slip ensures safe and efficient autonomous operations of rovers on deformable planetary surfaces; path planning algorithms that reduce slips by considering wheel-soil interaction or terrain data can minimize the risk of the rover becoming immobilized. Understanding wheel-soil interaction in transient states is vital for developing a more precise slip ratio prediction model, while path planning in the past assumes that slips generated at the path is a series of slip ratio in steady state. In this paper, we focus on the transient slip, or slip rate the time derivative of slip ratio, to explicitly address it into the cost function of path planning algorithm. We elaborated a regression model that takes slip rate and traction force as inputs and outputs slip ratio, which is employed in the cost function to minimize the rover slip in path planning phase. Experiments using a single wheel testbed revealed that even with the same wheel traction force, the slip ratio varies with different slip rates; we confirmed that the smaller the absolute value of the slip rate, the larger the slip ratio for the same traction force. The statistical analysis of the regression model confirms that the model can estimate the slip ratio within an accuracy of 85% in average. The path planning simulation with the regression model confirmed a reduction of 58% slip experienced by the rover when driving through rough terrain environments. The dynamics simulation results insisted that the proposed method can reduce the slip rate in rough terrain environments.

Research on Some Control Algorithms to Compensate for the Negative Effects of Model Uncertainty Parameters, External Interference, and Wheeled Slip for Mobile Robot

In this article, the research team systematically developed a method to model the kinematics and dynamics of a 3-wheeled robot subjected to external disturbances and sideways wheel sliding. These models will be used to design control laws that compensate for wheel slippage, model uncertainties, and external disturbances. These control algorithms were developed based on dynamic surface control (DSC). An adaptive trajectory tracking DSC algorithm using a fuzzy logic system (AFDSC) and a radial neural network (RBFNN) with a fuzzy logic system were used to overcome the disadvantages of DSC and expand the application domain for non-holonomic wheeled mobile robots with lateral slip (WMR). However, this adaptive fuzzy neural network dynamic surface control (AFNNDSC) adaptive controller ensures the closed system is stable, follows the preset trajectory in the presence of wheel slippage model uncertainty, and is affected by significant amplitude disturbances. The stability and convergence of the closed-loop system are guaranteed based on the Lyapunov analysis. The AFNNDSC adaptive controller is evaluated by simulation on the Matlab/simulink software R2022b and in a steady state. The maximum position error on the right wheel and left wheel is 0.000572 (m) and 0.000523 (m), and the angular velocity tracking error in the right and left wheels of the control method is 0.000394 (rad/s). The experimental results show the theoretical analysis’ correctness, the proposed controller’s effectiveness, and the possibility of practical applications. Orbits are set as two periodic functions of period T as follows.

A Novel Bilevel Electromechanical Compound Braking Coordinated Control Strategy for Electric Vehicles

Due to the difference of response time and braking type between the motor and the pneumatic braking system, it is still difficult to coordinate the motor braking and the pneumatic braking to ensure the vehicle stability and maximal energy regeneration. To address this challenge, a bilevel electromechanical compound braking coordinated control strategy for electric vehicles is proposed considering general and emergency braking state. First, in general braking state, considering the delay characteristics of the pneumatic braking system, a Lagrange quadratic interpolation prediction algorithm is designed to start the pneumatic braking system in advance. Second, in emergency braking state, a model predictive control method is proposed to optimize the braking torque distribution while controlling the wheel slip ratio in a stable range. In order to obtain the optimal control effect, a modified adaptive cuckoo search algorithm is put forward, in which three adaptive impact factors are added. Finally, the proposed control strategy is verified under three road conditions and compared with the conventional control strategy. The results demonstrate significant improvements under gravel road condition, including a 7% increase in energy recovery efficiency, a 92.1% enhancement in the following effect of pneumatic braking torque, and a 43.5% reduction in wheel fluctuation.

Rule-based torque vectoring distribution strategy combined with slip ratio control to improve the handling stability of distributed drive electric vehicles

This study presents a hierarchical control system of handling stability for distributed drive electric vehicles. The desired direct yaw moment (DYM), determined by the upper-level controller, regulates the sideslip angle and yaw rate according to the robust H∞ control strategy. Meanwhile, the lower-level controller proposed in this research consists of a rule-based torque vectoring distribution and wheel slip ratio control. The proposed rule-based torque vectoring distribution strategy (TVDS) permits drive pattern switching based on the wheel slip ratio and preferentially employs the balanced torque vectoring distribution strategy to achieve DYM, wherein the distributed braking torque is achieved by motor regenerative braking. Here, the wheel with serious slipping was managed in a four-wheel drive pattern by the slip ratio controller. Then, the distribution strategies used for differential braking and proposed rule-based torque vectoring with and without slip ratio control were compared and analyzed in vehicle states and actuator outputs, respectively, by setting CarSim/MATLAB cosimulation under two driving conditions. Results demonstrate that the proposed rule-based TVDS can improve handling stability, energy efficiency, and riding comfort. Wheel locking can be successfully avoided by actuating the wheel slip ratio control, subsequently reducing the road adhesion requirements and improving vehicle handling stability and trajectory tracking accuracy.

A backstepping controller based on RBFNN for mobile manipulator with unknown wheel slippage

A backstepping controller based on RBFNN for mobile manipulator with unknown wheel slippage

A backstepping controller based on RBFNN for mobile manipulator with unknown wheel slippage

A backstepping controller based on RBFNN for mobile manipulator with unknown wheel slippage

Slip ratio control based on adaptive fuzzy sliding mode for vehicle with an electromechanical brake system

The development of vehicle intelligence has driven the evolution of brake-by-wire systems, with electromechanical braking (EMB) emerging as a crucial development in intelligent vehicle braking. To enhance the braking safety of EMB-equipped vehicles, this paper proposes a slip ratio control method based on adaptive fuzzy sliding mode control (AFSMC) to more effectively achieve wheel slip ratio tracking during braking. The approach involves establishing the mathematical model of the planetary gear-type EMB system and the vehicle’s longitudinal dynamics model. Additionally, a hierarchical collaborative control strategy is introduced, where the bottom layer employs the EMB clamping force control algorithm based on cascaded proportional-integral (PI), and the top layer integrates AFSMC to regulate the slip ratio. The simulation results, validated using the joint simulation platform of Simulink and Carsim under various conditions, illustrate that the AFSMC, compared to the conventional sliding mode controller (SMC), attains more precise control of wheel slip ratio while mitigating the chattering phenomenon. These findings suggest the potential of AFSMC for practical engineering applications.

Sliding Mode Wheel Slip Control for Regenerative Braking of an All-Wheel-Drive Electric Vehicle

Abstract Regenerative braking is one of the main advantages of electric propulsion systems. In such systems, the vehicle brake controller has to prioritize safety while maximizing the recovered energy at all times. This paper proposes a two-step hierarchical brake controller for a dual-motor all-wheel-drive electric vehicle. In the first step, a novel sliding mode controller (SMC) generates the total braking torque on each axle to independently control the slip on the front and rear wheels. In the second step, the torque split controller assigns motor and friction brake torques to maximize the recovered energy. By incorporating the effects of changing vehicle speed, the proposed SMC controller accounts for the nonlinearities in vehicle dynamics and tire model and considers the weight transfer due to vehicle deceleration while being robust to disturbances. Using simulations, we show that while the traditional SMC formulation is not effective during emergency braking scenarios, the proposed formulation successfully generates control commands to bring the vehicle to a stop position at a minimum distance. Furthermore, our controller can maintain both wheels in the stable slip region, even when starting from a locked position. The performance of the proposed controller is evaluated for an emergency braking scenario and on an aggressive segment of the US06 cycle.

Research on Shovel-Force Prediction and Power-Matching Optimization of a Large-Tonnage Electric Wheel Loader

Nowadays, rapid development has been achieved with respect to the electric wheel loader (EWL). The operational efficiency of EWLs is affected by many factors; especially, shovel force is a very important factor. For large-tonnage EWLs, when employing empirical, formula-based methods to predict shovel force, the generated errors are significant, with errors frequently reaching levels of up to 30%. To solve this problem, a method, based on the discrete element method (DEM), to predict shovel force is put forward in this paper. The material parameters are calibrated by a backpropagation (BP) neural network learning algorithm (NNLA). The material model is inputted into multi-body-dynamics software. A simulation model to accurately predict the shovel force is created. The error between the test results and the simulation results is 7.8%, demonstrating a high level of consistency. To validate the reliability of this method, the 35-ton EWL is taken as an example for research, and the straight-line driving test and the power-matching test are conducted. While ensuring the operational efficiency of the EWLs, the power loss is also a crucial consideration. The drastic changes in shovel force often result in front-tire slippage of the EWLs. To minimize wheel slippage during the shoveling section, the matching of the electric motor was optimized. In summary, material parameters were calibrated using a combined method of BP NNLA to predicate shovel force of a large-tonnage EWL. Additionally, the power matching of the EWL has been optimized to accord with the shoveling section of the device.

Research on a Comprehensive Evaluation Method of Train Anti-Slip System Performance

The quality of a train’s braking anti-slip control system has a significant impact on train safety and braking performance. Currently, there is no established standard evaluation method for anti-slip control systems, making it an important area of research in the academic community. This article comprehensively considers four key indexes: adhesive coefficient utilization rate, air consumption increase ratio, wheel slip work, and anti-slip valve action frequency. The evaluation system takes into account the influence of load layer and braking level, and proposes a comprehensive evaluation method for train anti-slip control based on multi-factor hierarchical analysis. A series of experiments were conducted using a semi-physical simulation test bench for anti-slip evaluation, aimed at comprehensively evaluating two different anti-slip control strategies. By applying the method proposed in this article, the above four indexes and their corresponding weights of two anti-slip control strategies under different conditions were calculated. Finally, the comprehensive evaluation result R1 of anti-slip control strategy 1 was calculated as 0.8389, while the comprehensive evaluation result R2 of anti-slip control strategy 2 was calculated as 0.7912. Based on the comprehensive evaluation results, it is evident that the anti-slip comprehensive evaluation method established in this article is comprehensive and scientific, with concise and clear evaluation results. This method carries certain reference significance for the design of future anti-slip evaluation methods.

Finding a generic fixed brake force distribution through optimizing hydraulic brake system parameters to prevent wheel lock

Purpose The paper aims to identify a suitable generic brake force distribution ratio (β) corresponding to optimal brake design attributes in a diminutive driving range, where road conditions do not exhibit excessive variations. This will intend for an appropriate allocation of brake force distribution (BFD) to provide dynamic stability to the vehicle during braking. Design/methodology/approach Two techniques are presented (with and without wheel slip) to satisfy both brake stability and performance while accommodating variations in load sharing and road friction coefficient. Based on parametric optimization of the design variables of hydraulic brake using evolutionary algorithm, taking into account both the laden and unladen circumstances simultaneously, this research develops an improved model for computing and simulating the BFD applied to commercial and passenger vehicles. Findings The optimal parameter values defining the braking system have been identified, resulting in effective β = 0.695 which enhances the brake forces at respective axles. Nominal slip of 3.42% is achieved with maximum deceleration of 5.72 m/s2 maintaining directional stability during braking. The results obtained from both the methodologies are juxtaposed and assessed governing the vehicle stability in straight line motion to prevent wheel lock. Originality/value Optimization results establish the practicality, efficacy and applicability of the proposed approaches. The findings provide valuable insights for the design and optimization of hydraulic drum brake systems in modern automobiles, which can lead to safer and more efficient braking systems.

Tracking controller for uncertain wheel mobile robot: adaptive sliding mode control approach

This paper presents a technique for developing a sliding mode controller (SMC) using the state model of wheel mobile robot (WMR). The control scheme which consists of a controller and a disturbances observer can eliminate system uncertainties, disturbances, and unknown wheel slips. To successfully implement the sliding mode tracking controller algorithm, first, the transformation is utilized to convert the kinematic and dynamic models to an equation of state, and then create a controller based on Lyapunov function. Subsequently, a disturbance observer is formulated based on a stable sliding surface, followed by the development of an adaptive sliding mode control (ASMC) for the system. Moreover, to verify the efficacy of the given strategy, simulations have been performed under the aforementioned disturbance conditions. Finally, the simulation results show that chattering effect is eliminated, and the impact of disturbances is also diminished, thus proving the viability and correctness of the proposed control algorithm.

A robust super twisting fractional-order sliding mode-based control of vehicle longitudinal dynamic subjected to a constant actuator fault

This paper deals with the design and analysis of a super twisting fractional-order sliding mode controller (ST-FOSMC) to adjust the vehicle longitudinal dynamic when braking. While vehicle loading, road types, and modeling uncertainties are time-varying parameters, the control law must be robust against these disturbances. Also, the aging of the brake plate may introduce a difference between the control output and the actuator response that should be considered. The proposed control strategy has been used to enable the anti-lock braking system (ABS) to track the desired wheel slip value despite the presence of disturbances and constant actuator fault. The design of this controller is presented and the system stability is guaranteed by applying the Lyapunov theory. We carried out a simulation example that makes a comparison between our controller and the one based on the fractional-order sliding mode control to investigate which one of them outperforms the other. The results exhibit the superiority of the super twisting fractional order controller over the traditional fractional-order sliding mode controller during the braking phase.

Performance Evaluation of a Height Adjustable Mini Combine Harvester

Mini combine harvesters have been very popular among paddy farmers. The compact size of the machine, in addition to the axial flow threshing mechanism and the effect of low ground pressure on paddy soil, makes it a potential alternative for efficient paddy harvesting of a height-adjustable mini combine harvester used for harvesting paddy fields. This type of harvester was tested in typical paddy field conditions planted with MR297 variety at MARDI Seberang Perai. The performance tests included measuring theoretical and effective field capacity, field efficiency, soil bearing capacity before and after machine disturbance and machine slippage. The fuel consumption was also recorded. The combined harvesting losses were also measured during the experiment. Results showed that in wet and muddy conditions, the mini combine harvester obtained a theoretical field capacity (TFC) of 1.28 ha/hr, effective field capacity (EFC) of 0.94 ha/hr and a field efficiency (FE) of 73.4%. The average fuel consumption of the mini combine harvester was 25 L /ha. The wheel slippage in wet paddy fields was 2.18% and on farm roads was 1.55%. The mini combine harvester also contributed to producing less ground effects, combined with the use of low ground contact pressure tracks, that caused minimal soil disturbance that would affect the soil hardpan layer. This mini combine harvester produced an average harvesting loss of 2.3% with an average harvesting impurity of 10.65%. The mini combine harvester had enough power to move in typical paddy field conditions, with no soft soil problems. The mini combine harvester was able to turn 360 degrees within a small area, which made it suitable for harvesting in paddy fields. Thus, this mini combine harvester has the potential to be used for paddy harvesting with the ability to not only produce minimal harvesting loss, but also produce less ground contact pressure which can help to manage the soil hardpan layer from being easily damaged.

Field Testing and Evaluation of a Seven-Row Inclined Plate Planter for Mustard Cultivation

Mustard seed (Brassica nigra) is a crucial oilseed crop extensively cultivated in several countries, especially in South Asia. Enhancing seed planting techniques is essential to optimize crop output and overcome the challenges faced by farmers. Traditional manual planting methods are inefficient and time-consuming, creating obstacles to overall agricultural productivity. To address this issue, a field test and evaluation of a seven-row inclined plate planter for mustard cultivation were conducted. Precision planting, which involves accurate seed placement at desired intervals, is vital for maximizing crop productivity. The study encompassed a comprehensive analysis of soil parameters, including soil type, moisture content, bulk density, and cone index. Various operational parameters such as seed spacing, row spacing, and ground wheel slip were evaluated. The economic aspects, including cost analysis, breakeven point, payback period, and benefit-cost ratio, were considered to assess the financial feasibility of the tractor-operated planter.
 Calibration results revealed variations in seed rates among different rows and hopper capacities, impacting seed placement uniformity. Additionally, the study examined seed breakage under different operational parameters, emphasizing its influence on germination rates. Field performance data included soil moisture (12.61%), bulk density (1.45 g/cc), and field efficiency (82.30%), offering insights into real-world planter operation. The cost analysis determined a favorable economic outlook, with a benefit-cost ratio of 1.2, signifying the economic viability of machine harvesting compared to manual methods.

Control of constrained mobile manipulators with unknown wheel slippage, using neural network based backstepping control technique

Control of constrained mobile manipulators with unknown wheel slippage, using neural network based backstepping control technique

MEASUREMENT OF LINEAR VELOCITY USING A MOBILE ROBOTIC PLATFORM WITH COMPUTER VISION

This article presents an approach to integrating computer vision algorithms into the control system of traction electric drives in rail transport. It demonstrates the utilization of computer vision algorithms for calculating linear velocity as an alternative to conventional sensors like wheel odometers, GPS, DGPS and inertial sensors, which may prove ineffective on slippery surfaces and at low speeds. As a result, this article focuses on employing linear velocity as feedback within the control system to enhance power efficiency during starting and stopping and to prevent wheel slip. The electric drive control system has been successfully implemented and tested on a robotics platform designed for simulating dynamic behaviors in real rail transports scenarios. The article details the development process of this robotics platform, which is employed to mimic real-world dynamic conditions in rail transport. The proposed control algorithm for speed estimation is assessed using a specially designed test bench, revealing its capability to predict speed with a relatively high degree of accuracy. Additionally, an optical flow algorithm for velocity estimation is introduced and evaluated through a specially designed test rig, indicating a strong correlation between the predicted vehicle speed and the measurements from precision optical encoders. The study also determines the optimal feature window size for real-time optical flow rate estimation. In summary, this approach exhibits significant potential for accurate speed estimation. Ongoing experiments are being conducted under various real-world conditions, with future research aimed at developing a dependable autonomous system for speed measurement. The integration of modern digital computer vision technologies not only enhances the traction characteristics of electric drives but also extends the capabilities of traction electric drives to meet the rigorous demands of industrial equipment.

Desempenho energético de trator agrícola articulado: Modo manual versus automático

ABSTRACT Automatic production management (APM) is a tool that assists in the operations of agricultural tractors, increasing yield and energy efficiency. The objective of the experiment was to compare the energy and operational performance of a 373-kW articulated tractor equipped with APM and manual mode of engine transmission and rotation, across different real-world speeds. The experiment was conducted in a randomized block design with five replicates, using a split-plot arrangement with two system modes (manual and automatic) in the plots and four real-world speeds (4, 6, 8, and 10 km h-1) in the subplots, totaling 40 experimental units. The evaluated variables were: wheel slippage; engine rotation; hourly and specific fuel consumptions; drawbar force, power, and yield; operating speed; and engine thermal efficiency. The variance of the data was analyzed using Tukey’s test for the first factor, and regression analysis for the second factor and interactions. The automatic mode showed lower engine rotation and wheel slippage without compromising the other variables. The use of this mode showed energy advantages at 4 and 6 km h-1 by resulting in less fuel consumption per hour. In addition, the manual mode presented higher thermal efficiency at lower speeds than the automatic mode, which showed a linear increase.

Theoretical Systematisation of Wheel Slip Control Methods Based on Excessive Torque and Angular Momentum

Theoretical Systematisation of Wheel Slip Control Methods Based on Excessive Torque and Angular Momentum