Search Results (21)

This paper presents a high-order model-based robust control strategy for a dual-motor road wheel actuating system in a steer-by-wire (SbW) architecture. The system consists of a belt-driven and a pinion-driven motor collaboratively actuating the road wheels through mechanically coupled dynamics. To accurately capture the interaction between actuators, structural compliance, and road disturbances, a four-degree-of-freedom (4DOF) lumped-parameter model is developed. Leveraging this high-order dynamic model, a composite control framework is proposed, integrating feedforward model inversion, pole-zero feedback compensation, and a disturbance observer (DOB) to ensure precise trajectory tracking and disturbance rejection. High-fidelity co-simulations in MATLAB/Simulink and Siemens Amesim validate the effectiveness of the proposed control under various steering scenarios, including step and sine-sweep inputs. Compared to conventional low-order control methods, the proposed approach significantly reduces tracking error and demonstrates enhanced robustness and disturbance attenuation. These results highlight the critical role of high-order modeling in the precision control of dual-motor SbW systems and suggest its applicability in real-time, safety-critical vehicle steering applications. Full article

Aiming at the characteristic of a variable and optimized steering ratio of the Steer-by-Wire System (SBW), this paper studies the design method of the steering ratio starting from the influence of the steering ratio on the vehicle steering maneuverability and the driver’s steering burden. Through the analysis of the influencing factors of the steering ratio and the analysis of the driver’s steering characteristics, a yaw rate gain control model is established. Combined with the evaluation index of handling stability, the yaw rate gain is optimized, and the optimal yaw rate gain corresponding to different scenarios and different drivers’ steering characteristics is determined, so as to design the characteristics of the variable steering ratio that meet the preferences of different drivers. In order to verify the control effect of the variable gain steering ratio, a comprehensive feedback control strategy for the front wheel angle is established, and vehicles with a fixed steering ratio and a constant gain steering ratio are selected as references. Comparative tests under typical working conditions are carried out in the “driver-vehicle-road” closed-loop simulation system. The results show that the variable gain steering ratio considering the driver’s steering characteristics can not only improve the handling stability of the vehicle at medium and high speeds, but also enhance the driver’s steering comfort, enabling the SBW to achieve the goal of “the vehicle adapting to the person”. Full article

Addressing the shortcoming that steer-by-wire (SBW) system cannot directly transmit road feel, this study investigates a SBW system dynamics model, steering angle tracking control, and road feel simulation algorithm design. This study proposes a high-precision observer-based road feel simulation method that achieves road feel feedback torque design through the real-time estimation of system disturbance torque based on accurate front-wheel angle tracking. The methodology employs an improved nonlinear second-order sliding mode observer (INSOSMO) to estimate the system disturbance torque. This observer incorporates proportional–integral terms into the super-twisting algorithm to enhance dynamic response, replaces the sign function with a Sigmoid function to eliminate chattering, and utilizes the sparrow search algorithm (SSA) for global parameter optimization. Meanwhile, a two-stage filter combining a strong tracking Kalman filter (STKF) and first-order low-pass filtering processes the observer values to generate road feel feedback torque. Additionally, for the active return control of the steering wheel, a backstepping sliding mode control (BSSMC) integrated with an extended state observer (ESO) is employed, where the ESO enhances the robustness of BSSMC through real-time nonlinear disturbance estimation and compensation. MATLAB/Simulink-CarSim co-simulation demonstrates that, under sinusoidal testing, the INSOSMO reduces mean absolute error (MAE) by 34.7%, 62.5%, and 60.1% compared to the ESO, Kalman filter observer (KFO), and conventional sliding mode observer (SMO), respectively. The designed road feel feedback torque meets operational requirements. The active return controller maintains accurate steering wheel repositioning across various speed ranges. Full article

This paper proposes a novel steer-by-wire (SBW) system for marine vessels as a viable alternative to conventional hydraulic steering systems. By replacing mechanical linkages, the proposed SBW system enhances responsiveness, reduces complexity, and minimizes operator fatigue. Designed with a power transmission mechanism suited to maritime environments, it features a modular architecture that allows for seamless integration into existing vessels. Onboard experimental studies quantify the forces required for steering, establishing design criteria for the SBW system, while a disturbance observer (DOB)-based velocity controller improves tracking performance under unpredictable maritime conditions. Moreover, a sensorless admittance control strategy enables steering-feel rendering without the need for additional force sensors, thereby simplifying the overall design. Analyses of stiffness and damping characteristics further reveal that individual and combined tuning of these coefficients allows for customizable steering feel tailored to diverse operator requirements. Full article

Steer-by-wire (SbW) is the latest steering evolution, providing many benefits, such as reduced vehicle weight and enhanced steering capability. While reliability is one of the main concerns hindering its widespread application, the potential of this technology to revolutionize the automotive industry is huge. Control techniques play an important part in achieving the full potential of SbW by focusing on the development of its performance and safety aspects. This paper provides a review of the control techniques that are being used in SbW technology to achieve better performance and enhance safety. Various control techniques for SbW exist to serve different purposes when dealing with the non-linear nature of the SbW dynamics. Although there is no one-size-fits-all control technique for all the requirements of the SbW, this study highlights that the non-linear controllers based on the sliding mode control (SMC) are a popular option for enhancing the accuracy of SbW systems. However, these controllers often suffer from a downside known as chattering. In contrast, robust controllers like Model Predictive Controllers (MPCs) can effectively manage uncertain dynamics and eliminate chattering, although they pose challenges due to their high computational costs. Full article

The discharge of industrial effluents containing toxic heavy metals in water sources has serious consequences for human health and the environment, and biosorption appears to be an environmentally-friendly and cost-effective alternative that can be used for wastewater treatment. The use of different types of agricultural waste as biosorbents for the removal of toxic heavy metals, although an alternative, is quite difficult to apply in practice because these wastes have many other uses. Based on these considerations, in this study, soybean biomass (SB), soybean waste biomass obtained from oil extraction (SBW), and biochar obtained from soybean waste pyrolysis (BC-SBW) were tested as biosorbents for removing Pb(II) and Cd(II) ions, in batch systems. Under optimal conditions (pH = 5.4, 4.0 g biosorbent/L, room temperature (25 ± 1 °C), contact time = 180 min), the biosorption capacity increases in the order SB < SBW < BC-SBW for both metal ions (Pb(II) ions (69.43 mg/g < 99.81 mg/g < 116.83 mg/g) and Cd(II) ions (25.63 mg/g < 36.12 mg/g < 49.10 mg/g)), indicating that BC-SBW has the highest efficiency in removing toxic heavy metals. In addition, experiments on wastewater samples have shown that, in addition to significantly reducing the content of heavy metals, BC-SBW also significantly improved other quality indicators (such as pH, TSM (total suspended matter), COD (chemical oxygen demand), BOD5 (biochemical oxygen demand)), compared to the other biosorbents (SB and SBW). Quantitative evaluation of the biosorption performance of each biosorbent (SB, SBW, and BC-SBW) shows that BC-SBW has a real chance of being used on an industrial scale for wastewater treatment. All these aspects allowed the development of a circular approach for the use of soybean biomass in the removal processes of toxic heavy metals. This approach minimizes the shortcomings of using biomass as a biosorbent and increases the chance of using these materials in industrial practice. Full article

A crucial role is played by steering-angle prediction in the control of autonomous vehicles (AVs). It mainly includes the prediction and control of the steering angle. However, the prediction accuracy and calculation efficiency of traditional YOLOv5 are limited. For the control of the steering angle, angular velocity is difficult to measure, and the angle control effect is affected by external disturbances and unknown friction. This paper proposes a lightweight steering angle prediction network model called YOLOv5Ms, based on YOLOv5, aiming to achieve accurate prediction while enhancing computational efficiency. Additionally, an adaptive output feedback control scheme with output constraints based on neural networks is proposed to regulate the predicted steering angle using the YOLOv5Ms algorithm effectively. Firstly, given that most lane-line data sets consist of simulated images and lack diversity, a novel lane data set derived from real roads is manually created to train the proposed network model. To improve real-time accuracy in steering-angle prediction and enhance effectiveness in steering control, we update the bounding box regression loss function with the generalized intersection over union (GIoU) to Shape-IoU_Loss as a better-converging regression loss function for bounding-box improvement. The YOLOv5Ms model achieves a 30.34% reduction in weight storage space while simultaneously improving accuracy by 7.38% compared to the YOLOv5s model. Furthermore, an adaptive output feedback control scheme with output constraints based on neural networks is introduced to regulate the predicted steering angle via YOLOv5Ms effectively. Moreover, utilizing the backstepping control method and introducing the Lyapunov barrier function enables us to design an adaptive neural network output feedback controller with output constraints. Finally, a strict stability analysis based on Lyapunov stability theory ensures the boundedness of all signals within the closed-loop system. Numerical simulations and experiments have shown that the proposed method provides a 39.16% better root mean squared error (RMSE) score than traditional backstepping control, and it achieves good estimation performance for angles, angular velocity, and unknown disturbances. Full article

The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter variations, and exterior disturbance with input and output time delays as the generalized state, a scaling finite-time extended state observer (SFTESO) is constructed with a scaling gain for quickly estimating the unmeasured velocity and the generalized disturbances within a finite time. With the aid of the SFTESO, the robust FFTCC with the scaling gain is designed not only for ensuring finite-time convergence and strong robustness against time delays and disturbances but also for improving the speed of the convergence as a main novelty. Based on the Lyapunov theorem, the closed-loop stability of the overall SBW system is proven as a global uniform finite-time. Through examination across three specific scenarios, a comprehensive evaluation is aimed to assess the efficiency of the suggested controller strategy, compared with active disturbance rejection control (ADRC) and scaling ADRC (SADRC) methods across these three distinct driving scenarios. The simulated results have confirmed the merits of the proposed control in terms of a fast-tracking rate, small tracking error, and strong system robustness. Full article

In this paper, an adaptive active disturbance rejection control is newly designed for precise angular steering position tracking of the uncertain and nonlinear SBW system with time delay communications. The proposed adaptive active disturbance rejection control comprises the following two elements: (1) An adaptive extended state observer and (2) an adaptive state error feedback controller. The adaptive extended state observer with adaptive gains is employed for estimating the unmeasured velocity, acceleration, and compound disturbance which consists of system parameter uncertainties, nonlinearities, exterior disturbances, and time delay in which the observer gains are dynamically adjusted based on the estimation error to enhance estimation performances. Based on the accurate estimations of the adaptive extended state observer, the proposed adaptive full state error feedback controller is equipped with variable gains driven by the tracking error to develop control precision. The integration of the advantages of the adaptive extended state observer and the adaptive full state error feedback controller can improve the dynamic transient and static steady-state effectiveness, respectively. To assess the superior performance of the proposed adaptive active disturbance rejection control, a comparative analysis is conducted between the proposed control scheme and the classical active disturbance rejection control in two different cases. It is worth noting that the active disturbance rejection control serves as a benchmark for evaluating the performance of the proposed control approach. The results from the comparison studies executing two simulated cases validate the superiority of the suggested control, in which estimation, tracking response rate, and steering angle precision are greatly improved by the scheme proposed in this article. Full article

The steer-by-wire system severs the mechanical link between the steering wheel and the steering gear. This configuration enhances the angular transmission characteristics. Entering the nonlinear region of the tires could result in a reduction in the vehicle’s steering gain. In order to improve the comfort of vehicle steering operation, we have developed a variable transmission ratio controller for the steer-by-wire (SBW) system. This controller utilizes information on the vehicle speed and steering wheel angle to generate a variable transmission ratio coefficient, thereby adjusting the steering ratio. We introduce a multi-objective comprehensive evaluation index that takes into account vehicle lateral deviation, driver steering burden, vehicle stability, and safety. To harmonize the transmission ratio weights of constant steering gain, we employ the coefficient of variation method. Ultimately, a fuzzy neural network is employed to craft a nonlinear controller. We conducted steady-state circular motion tests, double lane-change tests, and step input tests to validate the performance of the variable transmission ratio control. The results suggest that, in comparison to conventional fixed transmission ratio systems, the variable transmission ratio control within the steer-by-wire system significantly alleviates the driver’s operational burden while enhancing the vehicle’s handling stability and safety. Full article

Tor is now using a centralized measurement system called Sbws to measure the bandwidth of relays to guide clients in selecting relays to balance traffic. Sbws has been proven to be vulnerable to multiple attacks because of the centralized structure and exposed measurements. We present SmartMeasurer, a secure and decentralized system for bandwidth measurement. Combining smart contract, Oracle Chainlink and ECC technology, we achieve decentralization while hiding the measurement circuits among the general circuits by exploiting the dual identity of randomly dynamic measurers and guards. We analyze the security of our system and demonstrate that it defends against three types of attacks. Our experiments on both private and public Tor networks show that our system is decentralized while keeping the error and the average of our measurements converges to a small interval of 0.30 Mbps. Compared to other existing methods, our system reduces trust assumptions and the costs of using smart contract, and enhances the practical feasibility of the solution. Full article

With the significant growth in modern computing systems, dynamic random access memory (DRAM) has become a power/performance/energy bottleneck in data-intensive applications. Both the power management mechanism and downscaling method face decreasing performance or difficulties in the smaller footprint of the DRAM capacitor. Since optimizing the circuit of sense amplifier (SA) is an efficient method to reduce energy consumption, we propose two single bitline load sense amplifier (SBLSA) circuits, i.e., a redundant voltage discharged SBLSA (RVD-SBLSA) circuit and a bit aware SBLSA (BA-SBLSA) circuit, to improve conventional and single bitline write (SBW) circuits. The RVD-SBLSA circuit utilizes a clamp diode to discharge redundant voltage over VDD/2 with an additional working stage. The BA-SBLSA circuit abandons the single bitline load (SBL) circuit during read and write ‘1’ operations. The RVD-SBLSA circuit can offer the lowest total energy consumption, and the BA-SBLSA circuit can make a better balance between energy consumption and latency. Through the simulation results, the proposed circuits can efficiently reduce energy consumption or balance energy consumption and latency and show huge potentials in very large-scale integrated circuits. Full article

Body weight and chemical composition are important aspects of beef cattle nutrition and management; however, existing equations estimating relationships among empty body and carcass chemical components were developed over 40 years ago using different cattle genetics and production systems. The objective of this analysis was to evaluate existing equations in predicting empty body and carcass chemical composition and determine the effect of sex, breed type, and publication year. A dataset was developed from published literature that contained 388 treatment means from 46 studies published between 1970 and 2020. Two equations relating shrunk body weight (SBW) to empty body weight (EBW), and 8 equations relating EBW and hot carcass weight (HCW) were found in the literature and evaluated using the developed dataset. Three sets of equations relating empty body chemical components, 4 sets of equations relating carcass chemical components, and 2 sets of equations relating carcass with empty body chemical components were found in the literature and evaluated using the dataset. Precision and accuracy of the equations were evaluated by simple linear regression of observed on predicted values, mean bias (MB), and concordance correlation coefficient (CCC). Additionally, the fixed effects of publication year, sex, and breed type on the deviation from observed values were evaluated using a general linear model. Both equations relating SBW to EBW and all equations relating EBW to HCW had high precision, but accuracy varied from −3.22 to −0.11% and −9.35 to −3.73% MB, respectively, and all the equations were affected by sex and breed type with 8 out of the 10 equations affected by publication year. For prediction of empty body chemical composition assuming empty body water is known, the 3 sets of equations varied in precision for protein (0.18 to 0.46), but not for fat (0.88 to 0.96) or ash (0.06 to 0.13) based on CCC, although the precision of prediction of protein and ash were poor. Accuracy of the 3 sets of equations varied for predicting empty body fat, protein, and ash with MB of −19.73 to −3.81, 1.67 to 15.91, and −0.16 to 15.75%, respectively. All 3 sets of equations were affected by publication year and breed type for predicting empty body fat, protein, and ash, and by sex for ash. For prediction of carcass chemical components assuming carcass water is known, the precision was similar among the 4 sets of equations for predicting fat (0.92 to 0.95), protein (0.34 to 0.40), and ash (−0.02 to −0.01) based on CCC, although precision was poor for protein and ash, but accuracy varied for prediction of carcass fat, protein and ash with MB of −11.20 to −2.52, 2.72 to 8.92, and −4.66 to 20.12%, respectively. Publication year and breed type affected the prediction of carcass fat and protein, and publication year, sex, and breed type affected the prediction of carcass ash for all 4 sets of equations. The precision of predicting empty body chemical components assuming carcass chemical components are known was high for water (0.96 and 0.98), fat (0.97 and 0.98), protein (0.97 and 0.97), and ash (0.98 and 0.96) and similar between the 2 sets of equations based on CCC. The accuracy of predicting empty body water (−1.68 and −0.33%), fat (6.38 and 2.70%), protein (0.85 and −0.54%), and ash (−0.65 and −4.54%) was moderate to high, but differed between sets of equations for fat and ash. Publication year influenced the prediction of empty body water for both sets of equations and ash for one of the equations, whereas, breed type influenced the prediction of water, protein, and ash, but not fat for both equations. Overall, existing equations may have major limitations to predicting empty body protein and ash unless carcass protein and ash are known. Additionally, all the equations were affected by some combination of publication year, sex, and breed type for one or more chemical components. Thus, a more robust set of equations should be developed to account for sex, breed type, and more recent cattle genetics and management systems. Full article

This paper presents the integrated motion control method for an electric vehicle (EV) equipped with a front/rear steer-by-wire (SbW) system and four in-wheel motor (IWM). The proposed integrated motion control method aims to maintain stable cornering. To maintain vehicle agility and stability, the lateral force and yaw rate commands of the vehicle are generated by referring to the neutral steering characteristics. The driver’s driving force command, the lateral force command based on the bicycle model, and the yaw moment generated by the high-level controller are distributed into the driving force of each wheel and the lateral force of the front and rear wheels by the yaw moment distribution. Finally, the distributed forces are directly controlled by a low-level controller. To directly control the forces, a driving force observer and a lateral force observer were introduced via driving force estimation in the IWMs and rack force estimation in the SbW system. The control performance is verified through computer simulations. Full article

It is difficult to model and determine the parameters of the steer-by-wire (SBW) system accurately, and the perturbation is variable with complex and changeable tire–road conditions. In order to improve the control performance of the vehicle SBW system, an adaptive fast super-twisting sliding mode control (AFST-SMC) scheme with time-delay estimation (TDE) is proposed. The proposed scheme uses TDE to acquire the lumped dynamics in a simple way and establishes a practical model-free structure. Then, a fractional order (FO) sliding mode surface and a fast super-twisting sliding mode control structure were designed on the basic super-twisting sliding mode to ensure fast convergence and high control accuracy. Since the uncertain boundary information of the actual system is unknown, a novel adaptive algorithm is proposed to regulate the control gain based on the control errors. Theoretical analysis concerning system stability is given based on the Lyapunov theory. Finally, the effectiveness of the method is verified through comparative experiments. The results show that the proposed TDE-AFST-FOSMC control scheme has the advantages of model-free, fast response and high accuracy. Full article