Application of a New Model Reference Adaptive Control Based on PID Control in CNC Machine Tools

To improve the control performance of the CNC machine tool feed servo system with nonlinear disturbances, a model reference adaptive control (MRAC) based on PID control is proposed. The method is based on the traditional three-loop control, the output signal of the speed loop controller is used as the input signal of the model reference adaptive controller, and the adaptive law is derived on the basis of Lyapunov stability theory. To verify the effectiveness, this paper analyzed the method through simulation and experiment. Results showed that the following error caused by nonlinear friction was significantly reduced when the speed was reversed, and the influence of noise and mechanical resonance was effectively suppressed. The proposed control method in this paper improves the motion-control accuracy and anti-interference ability of the control system.

Comparison between Artificial Neural Network and Rigorous Mathematical Model in Simulation of Industrial Heavy Naphtha Reforming Process

In this study, an artificial neural network (ANN) model was developed and compared with a rigorous mathematical model (RMM) to estimate the performance of an industrial heavy naphtha reforming process. The ANN model, represented by a multilayer feed forward neural network (MFFNN), had (36-10-10-10-34) topology, while the RMM involved solving 34 ordinary differential equations (ODEs) (32 mass balance, 1 heat balance and 1 momentum balance) to predict compositions, temperature, and pressure distributions within the reforming process. All computations and predictions were performed using MATLAB® software version 2015a. The ANN topology had minimum MSE when the number of hidden layers, number of neurons in the hidden layer, and the number of training epochs were 3, 10, and 100,000, respectively. Extensive error analysis between the experimental data and the predicted values were conducted using the following error functions: coefficient of determination (R2), mean absolute error (MAE), mean relative error (MRE), and mean square error (MSE). The results revealed that the ANN (R2 = 0.9403, MAE = 0.0062) simulated the industrial heavy naphtha reforming process slightly better than the rigorous mathematical model (R2 = 0.9318, MAE = 0.007). Moreover, the computational time was obviously reduced from 120 s for the RMM to 18.3 s for the ANN. However, one disadvantage of the ANN model is that it cannot be used to predict the process performance in the internal points of reactors, while the RMM predicted the internal temperatures, pressures and weight fractions very well.

Features of Index-Ring Finger Pair’s Force Contribution in Multi-Finger Force-Following Tasks

New types of cylindrical handles such as pushrims with force signal sensors under four fingers (excluding the thumb) enable real-time gripping-status assessment. The mirrored change phenomenon of the index and ring fingers observed in linear grip tasks offers a new perspective on finger grouping. To evaluate the force contribution of index-ring finger pair in multi-finger force, 10 right-handed male participants with similar hand sizes were recruited to participate in sinusoidal function force-following tasks involving a cylindrical handle. The real-time signal of the grip force and individual finger force were recorded to analyze real-time changes in the finger force contribution (FC). Subsequently, the time-FC curves of individual and paired fingers were analyzed. Results show are as follows: (1) When the FC of the index-ring finger pair exceeded that of the middle-little finger pair, the gripping load was relatively low, and a smaller difference between the FCs of the index-ring finger pair and the middle-little finger pair indicated a smaller following error. (2) The FC of index-ring finger pair is a better (higher-linearity) parameter to assess gripping status. These findings show that the paired-finger FC is an adequate parameter for the gripping-status assessment.

Path following method for AUV based on Q-Learning and RBF neural network

In the underwater docking process, the oscillation on AUV velocity brings extra challenge on AUV path following. A Q-learning based Sliding Mode Control (SMC) method to increase the path following performances is proposed. Firstly, AUV guidance law is designed to reduce the path following error. Heading and depth sliding mode controllers are designed to track the guidance law. Then, according to AUV velocity, tracking error and the first derivative, the control parameters of SMC are optimized via Q-learning network. RBF neural network is built to accelerate the offline learning rate. Finally, numerical simulations are made to investigate the characteristics of the present method. Comparisons are made between the trained Q-learning based SMC and the traditional SMC. The results show the effectiveness of the present method.

The contributions of entorhinal cortex and hippocampus to error driven learning

Computational models proposed that the medial temporal lobe (MTL) contributes importantly to error-driven learning, though little direct in-vivo evidence for this hypothesis exists. To test this, we recorded in the entorhinal cortex (EC) and hippocampus (HPC) as macaques performed an associative learning task using an error-driven learning strategy, defined as better performance after error relative to correct trials. Error-detection signals were more prominent in the EC relative to HPC. Early in learning hippocampal but not EC neurons signaled error-driven learning by increasing their population stimulus-selectivity following error trials. This same pattern was not seen in another task where error-driven learning was not used. After learning, different populations of cells in both the EC and HPC signaled long-term memory of newly learned associations with enhanced stimulus-selective responses. These results suggest prominent but differential contributions of EC and HPC to learning from errors and a particularly important role of the EC in error-detection.

Research on Tool Presetting and Tool Deviation in CNC Lead Screw Grinding Process

In the process of tool presetting for an CNC lead screw grinding, when A-axis rotating and Z-axis shifting synchronously according to the screw pitch length, L, of the lead screw workpiece, the handwheel corresponding to X-axis and Z-axis, respectively, is operated to align the grinding wheel with the middle of the screw groove. Then, the coordinates of Z-axis, A-axis and X-axis of the current position are recorded, and the coordinates of the grinding start position and grinding end position of the lead screw workpiece are calculated accordingly.However, due to the mutual following error of Z-axis and A-axis in the synchronous movement process, tool deviation typically occurs when the grinding wheel moves from the grinding start position to the grinding end position to grind the lead screw workpiece. More specifically, the grinding wheel slightly deviates from the middle of the screw groove to the left or right of the screw groove.To offset this deviation, the root cause for creating the deviation is analyzed, and a method to correct the tool deviation is proposed: First, the CNC system sends out grinding instructions, according to the requirements of grinding process, to make the A-axis and the Z-axis move synchronously. In the meantime, the CNC system measures and records the current coordinates of A-axis and Z-axis, and calculates the tool deviation caused by the mutual following error between Z-axis and A-axis. As a result the grinding start position and the grinding end position are adjusted in light of the value of tool deviation in the subsequent grinding process, so as to address the tool deviation issue.

Constraint-oriented integrated longitudinal and lateral robust control for connected and automated vehicle platoons

The coupling, nonlinearity, and uncertainty characteristics of vehicle dynamics make the accurate longitudinal and lateral control of an automated and connected vehicle platoon a tough task. Little research has been conducted to fully address the characteristics. By using the ideology of constraint-following control this article proposes an integrated longitudinal and lateral adaptive robust control methodology for a vehicle platoon with a bidirectional communication topology. The platoon control objectives contain the path tracking stability, the platoon internal stability, and the string stability. First, we establish the nonlinear kinematics path tracking model and the coupled vehicle longitudinal and lateral dynamical model that contains time-varying uncertainties. Second, we design a series of nonlinear equality constraints that directly guarantee the control objectives based on the kinematic relations. On this basis, an adaptive robust constraint-following control is proposed. It is shown that the control guarantees the uniform boundedness and the uniform ultimate boundedness of the constraint-following error and the uncertainty estimation error. Finally, simulation results are provided to validate the effectiveness of the proposed methodology.

Isolating cultural contributions to metacognition

Some aspects of human metacognition, such as the ability to consciously evaluate our beliefs and decisions, are thought to be culturally acquired. However, direct evidence for this claim is lacking. As an initial step in answering this question, here we examine differences in metacognitive performance between populations matched for occupation (students), income, demographics and general intelligence, but drawn from two distinct cultural milieus (Beijing, China and London, UK). We show that Chinese participants have heightened metacognitive evaluation of perceptual decision-making task performance in comparison with UK participants. These differences manifested in boosts to post-decisional processing following error trials, despite an absence of differences in first-order performance. In a second experiment, we replicate these findings in a new task that replaced post-decision evidence with equivalent social advice. Together, our results are consistent with a proposal that metacognitive capacity is shaped via socio-cultural interactions.

Application research of master-slave cranio-maxillofacial surgical robot based on force feedback

Background: The complex anatomical structure, limited field of vision, and easily damaged nerves, blood vessels, and other anatomical structures are the main challenges of a cranio-maxillofacial (CMF) plastic surgical robot. Bearing these characteristics and challenges in mind, this paper presents the design of a master-slave surgical robot system with a force feedback function to improve the accuracy and safety of CMF surgery. Methods: A master-slave CMF surgical robot system based on force feedback is built with the master tactile robot and compact slave robot developed in the laboratory. Model-based master robot gravity compensation and force feedback mechanism is used for the surgical robot. Control strategies based on position increment control and ratio control are adopted. Aiming at the typical mandibular osteotomy in CMF surgery, a scheme suitable for robot-assisted mandibular osteotomy is proposed. The accuracy and force feedback function of the robot system under direct control and master-slave motion modes are verified by experiments. Results: The drilling experiment of the mandible model in direct control mode shows that the average entrance point error is 1.37 ± 0.30 mm, the average exit point error is 1.30 ± 0.25 mm, and the average posture error is 2.27° ± 0.69°. The trajectory tracking and in vitro experiment in the master-slave motion mode show that the average position following error is 0.68 mm, and the maximum force following error is 0.586 N, achieving a good tracking and force feedback function. Conclusion: The experimental results show that the designed master-slave CMF robot can assist the surgeon in completing accurate mandibular osteotomy surgery. Through force feedback mechanism, it can improve the interaction between the surgeon and the robot, and complete tactile trajectory movements.