In view of the problem of disconnection between actual production scheduling and theoretical production scheduling due to frequent replacement of tools,fixtures,etc. in high-complexity intelligent manufacturing scenarios with multiple varieties and variable batches, it defines two coefficients,Machine Preparation Duration (MPD) and Machine Processing Coefficient (MPC), constructs an intelligent workshop scheduling mathematical model with multiple varieties and variable batches that introduces MPC parameters and takes minimizing maximum processing machine duration, the total machine load time and the total machine preparation time as the objective functions, designs a new solving algorithm Non-dominated Sorting Immune Genetic Algorithm-Ⅱ (NSIGA-Ⅱ) that combines Non-dominated Sorting Genetic Algorithm-Ⅱ (NGSA-Ⅱ) and Immune Genetic Algorithm (IGA). This algorithm uses a variety of methods for initialization,and proposes a scoring strategy that comprehensively considers non-dominated sorting and the size of the objective function value to select good individuals. At the same time,in order to improve the diversity of the population,it introduces the strategy of population stratification and adaptive cross-mutation. Finally,multiple sets of comparative experiments verify the effectiveness of this algorithm and its advantages of good stability and high solution quality when exploring optimal solutions.

To address the Flexible Job shop Batch Scheduling Problem with Variable Sublots (FJBSP-VS) aiming at minimizing the maximum completion time,an improved Sparrow Search Algorithm combined with Tabu Search (Tabu Search-Sparrow Search Algorithm,TS-SSA) was proposed for the integrated optimization of job batching,machine selection,and sublot sequencing.Firstly,a two-layer encoding method was designed to represent job batching,machine selection information,and sublot sequencing information,along with a decoding method that integrates no-delay scheduling to effectively improve the machine utilization. The Sparrow Search Algorithm (SSA) was discretized while retaining the producers-scroungers structure by introducing a crossover operator to solve discrete problems.Additionally,the choice of the target close to the scrounger was improved to enhance the global search ability of the algorithm.Furthermore,the combination of Tabu Search (TS) with the improved SSA enhances the local search ability of the algorithm.Finally,experiments were conducted using 27 existing public examples to verify the effectiveness and superiority of the TS-SSA algorithm.

Given the low capability-demand alignment,the difficulty of optimizing combinations under multiple constraints,and the low efficiency in optimization,a service combination optimization method based on the improved Dandelion Optimizer (DO) algorithm is proposed for cloud manufacturing. After analyzing the capabilities of cloud manufacturing service providers and the quality attributes of services,the Analytic Hierarchy Process (AHP) is utilized to normalize and aggregate various attribu-tes. Subsequently,an improved DO algorithm is employed to solve the service combination problem and obtain the optimal service combination solution.In terms of improving the DO algorithm,diversity of population particles is enhanced by introducing the Tent chaotic mapping. Additionally,the convergence speed of the algorithm is improved by incorporating reverse learning mechanisms,counters,and mutation concepts,thus preventing premature convergence. Finally,through simulation experiments and comparative analysis with classical dandelion optimizer algorithm and other improved algorithms such as particle swarm optimization,genetic algorithm,and polar bear optimization proposed in relevant literature on service combination,the effectiveness and stability of the proposed algorithm in cloud manufacturing service combination optimization are verified.

When valve core workpieces are stacked in disordered order,it is difficult for the robotic arm to automatically grasp the upper exposed valve cores.A point cloud segmentation algorithm based on surface curvature weighted fitting was proposed by processing the point cloud information collected by binocular camera. First,filter downsampling was performed and the redundant planar point cloud was removed using the Random Sample Consensus (RANSAC) algorithm,and the noise points were removed by clustering. Then,in order to solve the problem of sticking points at the edge of valve cores,the local plane was fitted using the least squares method and the dynamic curvature threshold was obtained based on the weighted average of surface curvature to remove the sticking points between the adjacent valve cores. Finally,the bottom area of the Oriented Bounding Box (OBB) of the valve core was calculated by the principal component analysis algorithm,and the interval test was performed to realize the iterative Euclidean distance threshold,so as to accurately segment the valve cores to be grasped by clustering. The experimental results show that the accuracy of valve core point cloud segmentation is over 95 %,the center of mass of the segmented valve core is obtained,and the grasping position is determined by combining with the linear fitting algorithm,and the Dobot robotic arm is able to accurately recognize and grasp the valve core through hand-eye calibration with the binocular camera.

With the development of intelligent manufacturing,intelligent warehousing,and other industries,unmanned forklifts have received more and more extensive attention,but the current research work on unmanned forklifts mainly focuses on positioning,sensing,planning,and other technologies,and the research on path tracking control is not mature enough. At present,there are two main problems in the path tracking control of unmanned forklifts. On the one hand,the existing control methods do not consider the system constraints such as steering wheel angle constraints and steering wheel angle speed constraints,and on the other hand,the existing research work usually does not use the midpoint of the front end of the forks as the control target. To solve these problems,first, a kinematic model of unmanned forklifts with the midpoint of the front end of the forks as the control point was established based on the principle of non-complete constraints,and then a path tracking control algorithm based on Nonlinear Model Predictive Control (NMPC) was designed,which was simulated and tested by MATLAB software and compared with Stanley control and other control methods. The proposed NMPC path tracking controller,which takes the midpoint of the front end of the forks as the control point,can realize high accuracy path tracking,and the maximum value of the lateral error amplitude was 0.054 9 m and the convergence value was not more than 0.014 7 m in the simulation results of different working conditions,which can reduce the maximum value of the lateral error amplitude by 75.88 % at least and convergence value by 88.34 % at least,compared with the NMPC path tracking controller with the midpoint of the front axle as the control point and the Stanley controller,etc. In addition,the real-time performance of the proposed controller can meet the requirements of low-speed control system,and the computation time in each control cycle was less than 20 ms,which was less than 40 % of the control cycle.

To address the issues of low production and debugging efficiency and the lack of effective monitoring methods for flapping-wing aircraft, a digital twin interaction system for flapping-wing aircraft was researched and designed. First, the five-dimensional model architecture of the digital twin interaction system was analyzed, based on which the virtual simulation system, monitoring system, and control system were designed. The virtual simulation system constructed a twin model of the physical entity on the Webots simulation platform and carried out simulation of flight attitudes and flight maneuvers, thereby improving on-site debugging efficiency. The monitoring and control systems enabled real-time bidirectional colsed-loop data interaction between the twin model and the physical entity through the upper computer control system, achieving visual monitoring of the flapping-wing aircraft during flight. Finally, the effectiveness and feasibility of the digital twin interaction system were verified through attitude visualization tests and flight tests. This digital twin interaction system provides a new approach to further enhancing the functions of digital twin systems for flapping-wing aircraft.

Aiming at the problem that it is difficult to accurately track and control the desired contact force in the dynamic environment of the grinding and polishing robot,a PD-fuzzy adaptive force tracking impedance control method was studied based on the adaptive impedance control model. Fuzzy control was used to dynamically adjust the update rate in the adaptive impedance control,and the time was adjusted by increasing PD control before the impedance control,in order to realise the accurate tracking and control of the desired contact force under the dynamic environment,and to ensure the quality of grinding and polishing processing. By setting up simulation with six environmental parameter variations,the investigated PD-fuzzy adaptive impedance controller was compared with the traditional impedance controller,adaptive impedance controller and fuzzy adaptive impedance controller,and the results show that the investigated PD-fuzzy adaptive impedance controller can maintain a shorter adjustment time and smaller overshooting in the collision contact phase while keeping a smaller steady-state error in the smooth contact phase,and it can achieve better contact force tracking compared to the other three kinds of controllers.

At present,the fully driven dexterous hand has many problems such as too many driving motors and insufficient grasping power.However,the highly underactuated dexterous hand has some problems,such as low independent control ability and insufficient dexterity. To solve the current problem,a four-finger dexterous hand based on cross-four linkage was designed,and the coupling motion between proximal and distal knuckle joints was realized by comparing the structure with the finger of an adult. Roll-pitch joint structure other than traditional yaw-pitch was put forward,applied which to 3 fingers except the thumb,enable the 3 fingers to flex and rotate,which can enrich dexterous hand grasping posture and enhance its dexterity; the thumb adopts a lateral swing structure in the metacarpophalangeal joint to achieve coordination with the other three fingers. The kinematics model of fingers were established in MATLAB software and the end working spaces of fingers were obtained. The dexterous hand was simulated by ADAMS software,and the rationality of the dexterous hand structure was verified by analyzing the movement characteristics of fingers. The experimental results showed that the four-finger dexterous hand had good grasping performance and high practical value.

Magnetically driven constitutes one of the significant drive modalities for small soft robots.Currently,the majority of magnetically driven soft robots employ external magnetic fields and exhibit weak crawling capabilities. To address this problem,a worm-like soft robot with built-in electromagnetically driven was proposed, which can crawl on sloping surfaces with multiple angles. Two models of soft-bodied robots,sized at 20 mm×6 mm×11 mm and 22 mm×6 mm×11 mm,were utilized in the experiments to verify the effect of the strength magnitude of the attracting and repelling magnets of the copper coils on the stability of crawling. It was concluded that the soft robot with a larger intermediate distance possesses stronger crawling stability and crawling ability,and it can crawl at a speed exceeding 1 mm/s on a maximum slope of 40°;the soft robots with small intermediate distances crawl faster,but have less crawling ability and stability. The influencing factors of the maximum slope and the motion action principle of the soft robot were presented, the thickness of the silicone,the selection of the drive device and the motion analysis of the electromagnetic contacts were discussed,and a variety of slope angle crawling experiments under the environment of no external magnetic field were carried out.

In order to improve the physical and mental health of the elderly and disabled people and reduce the burden of the family,it designs a two-phase travelling rehabilitation exoskeleton based on TRIZ,which is able to achieve the main functions of walking rehabilitation training and wheelchair travelling. The TRIZ innovation tool is used to solve the exoskeleton sit-to-stand conversion problem,and the exoskeleton prototype is statically analysed under load by ANSYS software. In order to explore the performance of the exoskeleton in the dynamic environment,kinematics and dynamics modelling of the exoskeleton is carried out,and a virtual prototype model is built and imported into ADAMS software for motion simulation,which verifies the feasibility of the design scheme through the analysis of the simulation data and provides a theoretical basis for the next step in the production of physical prototypes.

Path planning is a research hotspot of mobile robot,which is directly related to the efficiency and accuracy of mobile robot. Aiming at the problems that the existing research has not effectively solved the redundancy of turning points and the difficulty of obstacle avoidance in dynamic obstacle environment,a path planning algorithm of mobile robots based on B-spline improved RRT^* and Dynamic Window Approach (DWA) fusion was proposed. Firstly,the node pruning strategy was adopted to remove redundant nodes in the path. Then, B-spline curve was used to optimize the pruned path,shorten the path length,reduce the turning angle and make the path smoother. Finally,the improved DWA algorithm was integrated to ensure in real time avoidance of unknown obstacles under the condition of global optimization. Through MATLAB simulation and experiment based on ROS system,the results show that the proposed improved RRT^* and DWA fusion algorithm has the advantages of low cost,short running time,and can keeping a safe distance from obstacles,and planning the optimal path while avoiding dynamic obstacles.

Aiming at the problems of low precision of vehicle trajectory tracking and easy to be destabilized under the hazardous working conditions such as high speed driving,low adhesion road surface and large curvature conditions, taking the four-wheel independent drive intelligent vehicle as the research object,a trajectory tracking control strategy considering curvature adaptation and stability was proposed. Firstly,the vehicle traveling speed was calculated in real time according to the road curvature,and the model predictive control algorithm was used to solve the front wheel angle to track the desired path. Then,an additional transverse moment controller was designed based on integral sliding mode control,which used hyperbolic tangent function to reduce the system jitter and assigns moments according to the front and rear axle loads of the vehicle. The control objective was to track the desired trajectory more accurately and stably taking into account the control actuator constraints and vehicle stability constraints; finally, simulation experiments were conducted under double-shift line condition and large curvature condition,and the results show that the designed control strategy can effectively improve the trajectory tracking accuracy,reduce the peak center-of-mass lateral deflection angle and the peak swing angular velocity,and ensure the swing stability and ride comfort of the vehicle.

The Elasto-Hydrodynamic grease Lubrication (EHL) state of tapered roller bearings (FD-306/1025/YB) in wind turbine gearboxes was studied. The shear stress and viscosity of Mobil SHC 460 WT grease at different temperature were tested with the change of shear rate by a rotary rheometer. The corresponding rheological parameters were fitted with the Herschel-Bulkley model of non-Newtonian fluid. Based on the finite difference method,the linear contact elasto-hydrodynamic grease lubrication model of tapered roller bearing in high-power wind turbine gearboxes was established,and the oil film thickness and lubrication state were analyzed under different speed,load and temperature conditions. The results indicate that with the increase of shear rate and temperature,the viscosity of the grease decreased and had obvious shear thinning and viscosity-temperature character-istics. The increase of rotational speed,the decrease of bearing load and the decrease of temperature would increase the overall film thickness between the roller and raceway,increase the film thickness ratio and improve the lubrication state. Under high-speed conditions,the bearing film thickness ratio was more significantly affected by temperature,leading to more pronounced changes in the lubrication state.

To investigate the machinability of Inconel 718 alloy in dry end milling during laser cladding additive manufacturing,the laser cladding technique was used to coat Inconel 718 alloy on the surface of 27SiMn alloy steel. Orthogonal experimental design was employed to conduct dry end milling experiments and study the influence of milling process parameters on cutting forces and surface quality of the laser cladding layer. The research results indicate that milling depth has the most significant effect on cutting forces,and an increase in spindle speed,feed rate,and milling depth all lead to an increase in cutting forces. Among the milling process parameters,the feed rate has the most significant impact on surface roughness,followed by spindle speed,while the effect of milling depth is the smallest.The minimum surface roughness value was achieved when the spindle speed was set at 2 000 r/min,the feed rate was set at 150 mm/min,and the milling depth was set at 0.5 mm. Additionally,milling depth has the most significant influence on surface microhardness.These findings provide guidance and reference for process parameter selection in the mechanical machining process of laser cladded coatings.

Aiming at the problems of low efficiency and low precision of measuring sleeve size in traditional industrial inspection,a sleeve size measurement method based on machine vision was proposed. Firstly,the sleeve image was captured by the CMOS camera calibrated by Halcon software,and pre-processed by bilateral filtering and threshold segmentation. The improved Canny algorithm combined with the optimal segmentation threshold obtained by the Otsu method was used to obtain the pixel-level coordinates of the edges. The improved Zernike moments algorithm was used to locate the edges accurately. Finally,the inner and outer diameters of the sleeve were solved by fitting the inner and outer circles using the least squares method.The experimental results show that the average measurement accuracy of the method is less than 0.02 mm,and the measurement accuracy and efficiency meet the requirements of enterprises for rapid and accurate inspection.

To address challenges commonly encountered with optical projection-type length measuring machines during use,such as difficulty in reading, inaccurate readings, and accuracy degradation caused by optical system aging, a technical solution for upgrading the traditional human eye-based engraved line optical system to a grating-based digital display system was proposed. Based on grating length measurement technology,the solution included the design and installation of a marble guide and a grating measurement system to achieve high-precision digital length measurement. High-precision grating micrometer sensors were employed to ensure accurate probe zeroing and consistency in the contact force applied to the measured components during the measurement process. A specialized grating digital display unit,developed using Complex Programmable Logic Device (CPLD) technology,enabled high-speed real-time processing of signals from the grating scale and micrometer sensors.Additionally,software for the upper computer of the length measuring machine was developed,incorporating modules for error correction and compensation algorithms,data processing and display,database management,and auxiliary function control. Experimental results demonstrate that the upgraded length measuring machine achieves a resolution of 0.1 μm. Within a 2 m measurement range,the display error is ±(0.5+L/300) μm. Compared to the original optical projection-type length measuring machine,the upgraded system offers significantly improved accuracy,simplified readings,and enhanced stability of the display values. The system meets the requirements for metrological verification of measuring instruments.In conclusion,this method has high application value and strong potential for widespread adoption.

To address the issue of decreased accuracy in the block docking due to structural errors,the 4-PPPS parallel mechanism was focused.Initially,a closed-loop vector method was employed to establish a structural error model including 32 error terms.Subsequently,the influence of 16 measurable structural error parameters on the pose accuracy of the dynamic platform was specifically analyzed. It reveals that the length error of the moving pair along track direction has the greatest impact on the motion accuracy of the parallel mechanism,with a position error of 1.5 mm in the Z-axis direction when all four limbs exhibit such errors.Therefore,a compensation method based on the Whale Optimization Algorithm (WOA) optimized Radial Basis Function (RBF) neural network was proposed. By transforming pose errors into actuator length errors,it established a predictive model between theoretical pose of the dynamic platform and actuator length errors. After optimizing the network parameters,it yielded the actuator length compensation to correct the actual pose of the dynamic platform. Simulation results validate the effectiveness of this method in enhancing the motion accuracy of the parallel mechanism. Specifically,the mean errors in the X,Y,and Z directions are reduced from 0.169,0.188 and 0.159 mm to 0.002,0.001 and 0.003 mm,respectively. The maximum errors decrease from 0.208,0.231 and 0.195 mm to 0.012,0.001 and 0.019 mm,respectively. The average pose accuracy is improved by 85.07 %,demonstrating a significant compensation effect.

Aiming at the problem of poor robustness and anti-interference ability in Permanent Magnet Synchronous Motor (PMSM) speed control system, an Improved Fractional Order Active Disturbance Rejection Controller (IFOADRC) is proposed to replace the traditional active disturbance rejection controller. First, a new nonlinear function is designed and applied to the Nonlinear Fractional Order Extended State Observer (NFOESO). The Linear Fractional Order Extended State Observer (LFOESO) is used to make preliminary observations of the total disturbance, and then the designed weight function is used to introduce the estimated results into the nonlinear fractional extended state observer. Secondly, the Improved Fractional Order Active Disturbance Rejection Controller (IFOADRC) is established, and the convergence and interference suppression ability of the control strategy are analyzed theoretically. Finally, Simulink simulations and links-RT hardware-in-the-loop experiments are conducted to validate the proposed control strategy. Experimental results demonstrated that, compared to the traditional Nonlinear Active Disturbance Rejection Controller (NLADRC) and Cascaded Linear Active Disturbance Rejection Controller (CLADRC), the proposed control strategy achieved the following improvements: during speed step inputs, the settling time was reduced by 25.6 % and 17.6 % during acceleration, and by 10.7 % and 5.6 % during deceleration; during load disturbances, the settling time was reduced by 51.9 % and 24.2 % during sudden load addition, and by 41.5 % and 22.6 % during sudden load reduction. These results validate that the proposed control strategy effectively enhances the robustness and disturbance rejection capability of permanent magnet synchronous motors.