This study introduces an innovative approach to enhance the energy efficiency and position control performance of electro-hydraulic systems, employing a comprehensive comparative analysis. It ...presents and evaluates three control techniques: Proportional-Integral-Derivative (PID) control, Model Predictive Control (MPC), and Neural Network Model Predictive Control (NN-MPC). These methods are systematically assessed across varying load conditions. Notably, our research unequivocally establishes the exceptional performance of the NN-MPC approach, even when confronted with load variations. Furthermore, the study conducts an exhaustive examination of energy consumption by comparing a conventional system, where a flow control valve is not utilized as a hydraulic cylinder bypass, with a proposed system that employs a fully open Flow Control Valve (FCV). The results underscore the remarkable energy savings achieved, reaching up to 9% at high load levels.
Path tracking is one of the most important aspects of autonomous vehicles. The current research focuses on designing path-tracking controllers taking into account the stability of the yaw and the ...nonholonomic constraints of the vehicle. In most cases, the lateral controller design relies on identifying a path reference point, the one with the shortest distance to the vehicle giving the current state of the vehicle. That restricts the controller’s ability to handle sudden changes of the trajectory heading angle. The present article proposes a new approach that imitates human behavior while driving. It is based on a discrete prediction model that anticipates the future states of the vehicle, allowing the use of the control algorithm in future predicted states augmented with the current controller output. The performance of the proposed approach is verified through several simulations on V-REP simulator with different types of maneuvers (double lane change, hook road, S road, and curved road) and a wide range of velocities. Predictive Stanley controller was used compared to the original Stanley controller. The obtained results of the proposed control approach show the advantage and the performance of the technique in terms of minimizing the lateral error and ensuring yaw stability by an average of 53% and 22%, respectively.
The large number of poststroke recovery patients poses a burden on rehabilitation centers, hospitals, and physiotherapists. The advent of rehabilitation robotics and automated assessment systems can ...ease this burden by assisting in the rehabilitation of patients with a high level of recovery. This assistance will enable medical professionals to either better provide for patients with severe injuries or treat more patients. It also translates into financial assistance as well in the long run. This paper demonstrated an automated assessment system for in-home rehabilitation utilizing a data glove, a mobile application, and machine learning algorithms. The system can be used by poststroke patients with a high level of recovery to assess their performance. Furthermore, this assessment can be sent to a medical professional for supervision. Additionally, a comparison between two machine learning classifiers was performed on their assessment of physical exercises. The proposed system has an accuracy of 85% (±5.1%) with careful feature and classifier selection.
The following research proposes a closed loop force control system, which is implemented on a soft robotic prosthetic hand. The proposed system uses a force sensing approach that does not require any ...sensing elements to be embedded in the prosthetic's fingers, therefore maintaining their monolithic structural integrity, and subsequently decreasing the cost and manufacturing complexity. This is achieved by embedding an aluminum test specimen with a full bridge strain gauge circuit directly inside the actuator's housing rather than in the finger. The location of the test specimen is precisely at the location of the critical section of the bending moment on the actuator housing due to the tension in the driving tendon. Therefore, the resulting loadcell can acquire a signal proportional to the prosthetic's grasping force. A PI controller is implemented and tested using this force sensing approach. The experiment design includes a flexible test object, which serves to visually demonstrate the force controller's performance through the deformation that the test object experiences. Setpoints corresponding to "light", "medium", and "hard" grasps were tested with pinch, tripod, and full grasps and the results of these tests are documented in this manuscript. The developed controller was found to have an accuracy of ±2%. Additionally, the deformation of the test object increased proportionally with the given grasp force setpoint, with almost no deformation during the light grasp test, slight deformation during the medium grasp test, and relatively large deformation of the test object during the hard grasp test.
Variable stiffness link (VSL) manipulators are robotic arms that can adjust their link stiffness in real time to improve their adaptability and precision. They are particularly useful in industrial ...environments where safe collaboration with human workers is required. However, modeling and controlling these non-linear systems is a major challenge due to their complexity. This research paper presents a mathematical model for a 3DOF VSL manipulator, which is the first step towards optimizing performance, improving safety, and reducing costs. The accuracy and reliability of the model are demonstrated through verification experiments that strengthen confidence in its validity for engineering and scientific research. This study contributes to the understanding of the dynamics of VSL manipulators and provides insights for future advances in the use of such robots. By using the proposed model, the efficiency and precision of VSL manipulators can be improved while ensuring safe human–robot interaction in various industrial applications.
The importance of vehicle security has increased in recent years in the automotive field, drawing the attention of both the industry and academia. This is due to the rise in cybersecurity threats ...caused by (1) the increase in vehicle connectivity schemes, such as the Internet of Things, vehicle-to-x communication, and over-the-air updates, and (2) the increased impact of such threats because of the added functionalities that are controlled by vehicle software. These causes and threats are further amplified in autonomous vehicles, which are generally equipped with more electronic control units (ECUs) that are connected through controller area networks (CANs). Due to the holistic nature of CANs, attacks on the networks can affect the functionality of all vehicle ECUs and the whole system. This can lead to a breach of privacy, denial of services, alteration of vehicle performance, and exposure to safety threats. Although cryptographic encryption and authentication algorithms and intrusion detection systems (IDS) are currently being used to detect and prevent CAN bus attacks, they have certain limitations. Therefore, this study proposed a mitigation scheme that can detect and prevent such attacks at the ECU level, which could address the limitations of existing algorithms. This study proposed the usage of a secure boot scheme to detect and prevent the execution of malicious codes, as the presence of one or more ECUs with a malicious code is the root cause of most CAN bus attacks. Secure boot schemes apply cryptographic data integrity algorithms to ensure that only authentic and untampered software can run on the vehicle’s ECUs. The selection of an appropriate cryptographic algorithm is important because it affects the secure boot schemes’ security level and performance. Therefore, this study also tested and compared the performance of the proposed secure boot scheme with five different data security algorithms implemented using the hardware security module (HSM) of the TC399 32-bit AURIX™ TriCore™ microcontroller through an electric autonomous vehicle’s control unit. The tests showed that the two most favorable schemes with the selected hardware are the secure boot scheme with the cipher-based message authentication code (CMAC), because it possesses the highest performance with an execution rate of 26.07 (ms/MB), and the secure boot scheme with the elliptic curve digital signature algorithm (ECDSA), because it provides a higher security level with an acceptable compromise in speed. This study also introduced and tested a novel variation of the ECDSA algorithm based on the CMAC algorithm, which was found to have a 19% performance gain over the standard ECDSA-based secure boot scheme.
Cynara scolymus L. (Family: Compositae) or artichoke is a nutritious edible plant widely used for its hepatoprotective effect. Crude extracts of flower, bract, and stem were prepared and evaluated ...for their in vitro antioxidant activity and phenolic content. The flower crude extract exhibited the highest phenolic content (74.29 mg GAE/gm) as well as the best in vitro antioxidant activity using total antioxidant capacity (TAC), ferric reducing antioxidant power (FEAP), and 1,1-diphenyl-2-picrylhyazyl (DPPH) scavenging assays compared with ascorbic acid. Phenolic fractions of the crude extracts of different parts were separated and identified using high-performance liquid chromatography HPLC-DAD analysis. The silver nanoparticles of these phenolic fractions were established and tested for their cytotoxicity and apoptotic activity. Results showed that silver nanoparticles of a polyphenolic fraction of flower extract (Nano-TP/Flowers) exhibited potent cytotoxicity against prostate (PC-3) and lung (A549) cancer cell lines with IC50 values of 0.85 μg/mL and 0.94 μg/mL, respectively, compared with doxorubicin as a standard. For apoptosis-induction, Nano-TP/Flowers exhibited apoptosis in PC-3 with a higher ratio than in A549 cells. It induced total prostate apoptotic cell death by 227-fold change while it induced apoptosis in A549 cells by 15.6-fold change. Nano-TP/Flowers upregulated both pro-apoptotic markers and downregulated the antiapoptotic genes using RT-PCR. Hence, this extract may serve as a promising source for anti-prostate cancer candidates.
Study: Soft robots can achieve the desired range of motion for finger movement to match their axis of rotation with the axis of rotation of the human hand. The iterative design has been used to ...achieve data that makes the movement smooth and the range of movement wider, and the validity of the design has been confirmed through practical experiments. Limitation: The challenges facing this research are to reach the most significant inclined angle and increase the force generated by the actuator, which is the most complicated matter while maintaining the desired control accuracy. The motion capture system verifies the actual movement of the soft pneumatic actuator (SPA). A tracking system has been developed for SPA in action by having sensors to know the position and strength of the SPA. Results: The novelty of this research is that it gave better control of soft robots by selecting the proportional, integral, and derivative (PID) controller. The parameters were tuned using three different methods: ZN (Ziegler Nichols Method), GA (Genetic Algorism), and PSO (Particle Swarm Optimization). The optimization techniques were used in Methods 2 and 3 in order to reach the nominal error rate (0.6) and minimum overshoot (0.1%) in the shortest time (2.5 s). Impact: The effect of the proposed system in this study is to provide precise control of the actuator, which helps in medical and industrial applications, the most important of which are the transfer of things from one place to another and the process of medical rehabilitation for patients with muscular dystrophy. A doctor who treats finger muscle insufficiency can monitor a patient’s ability to reach a greater angle of flexion or increase strength by developing three treatment modalities to boost strength: Full Assisted Movement (FAM), Half Assisted Movement (HAM), and Resistance Movement (RM).
The challenge of trajectory tracking of autonomous vehicles (AVs) is a critical aspect that must be effectively addressed. Recent studies are concerned with maintaining the yaw stability to guarantee ...the customers’ comfort throughout the journey. Most of the geometrical controllers solve this task by dividing it into consecutive point stabilization problems, limiting the controllers’ ability to handle sudden trajectory changes. One research presented a predictive Stanley lateral controller that uses a discrete prediction model to mimic human behavior by anticipating the vehicle’s future states. That controller is limited in its use, as the parameters must be manually tuned for every change in the maneuver or vehicle velocity. This article presents a novel approach for trajectory tracking in autonomous vehicles, by introducing a fuzzy supervisory controller that automatically adapts to changes in the vehicle’s velocity and maneuver by estimating the prediction horizon’s length and providing different weights for each controller. The proposed method overcomes the limitations of traditional controllers that require manual tuning of parameters, making it ready for real-world experiments. This is the main contribution of the research in this paper. The suggested technique demonstrated an advantage over the Basic Stanley controller and the manually tuned predictive Stanley controller in terms of the total lateral error and the model predictive control (MPC) in terms of computational time. The performance is determined by performing various simulations on V-Rep and hardware-in-the-loop (HIL) experiments on an E-CAR golf bus. A broad selection of velocities is used to validate the behavior of the vehicle while working on different maneuvers (double lane change, hook road, S road, and curved road).
In this study, a state-of-the-art methodology for controlling an electro-hydraulic system is proposed. The aim is to achieve superior position tracking performance comparable to that of an ...electro-hydraulic servo valve system. To achieve this, a suite of linear and nonlinear control techniques—including PID, LQR, sliding mode, model predictive control (MPC), and neural network MPC controllers—are designed and tested based on system dynamics approximation. The controllers are optimized to effectively address the challenges posed by various loads, uncertainties, nonlinearities, internal leakage, chattering, and overshooting in the electro-hydraulic system. The proposed approach is both practical and effective, as demonstrated by simulation and experimental results. Comparative analysis reveals that the neural network MPC controller exhibits exceptional tracking performance and stability, with a smooth response and quick settling time.
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