Zhenlin Jin

Active compliance control represents a pivotal technique for managing the interplay between forces and positions. This article proposes an adaptive approach based on an identified model for variable trajectory control. Addressing parameter redundancy in the dynamic model, we propose a simplified, friction-incorporated modeling method. Key parameters are identified through current and torque data, with three friction models designed to approximate real-world scenarios. A method for monitoring instability risks is presented, particularly effective when the mass difference between the manipulator and the mobile platform is relatively small. It monitors imprudent power output, reducing risks such as overturning. Finally, within system safety constraints, an impedance model is designed to manage the relationship between external forces and position in Cartesian space. This model extends the range of motion to counteract external force influence, utilizing a trajectory modulation technique. Additionally, a trajectory tracking controller based on super-twisting sliding mode control is designed, and the stability of the control system is analyzed. Experimental validation confirms the efficacy of the proposed methodology.

Increasing demand for mobile manipulators in fields requiring high-precision tasks has introduced new requirements regarding their kinematic accuracy. Pose measurement of the mobile manipulator is a crucial method to improve the absolute positioning accuracy of the robot. To solve the pose estimation of the mobile manipulator, we propose a space measurement method based on visual marks and an interactive filtering method to improve the stability of measurement results. Firstly, the kinematics and dynamics of the mobile manipulator are analyzed, and the mathematical expression of the model is obtained to obtain the theoretical trajectory. Secondly, a visual marker based on pyramid hierarchy is proposed, which can adapt to scenes with significant distance scale changes. A visual marker of a regular 12-face is designed, the marker of each face is uniquely coded to ensure that multiple markers can be captured at the same time under a single viewing angle, and geometric relations determine the distance and pose of the end. We propose a filtering method considering the correlation of historical data to improve the stability and accuracy of measurement data. The matching degree of the filter motion mode is improved through the Pearson coefficient relationship between the filtered data in the current period and the historical data. In this paper, several experiments verify the method’s effectiveness. The repeatability of the measurement can reach 0.75mm, and the mean error(MAV)is 0.009mm. The noise test proves the anti-interference ability of the filtering method. The new filtering method has excellent performance on various tracking tracks. All experiments show that the method proposed in this paper has a good measurement effect and is a low-cost, convenient, and efficient method to solve the pose estimation and precise trajectory error analysis of mobile manipulators.

The mobile manipulator is a floating base structure with wide space operability. An integrated mechanical device for mobile operation is formed through the organic combination of the mobile platform and multi-axis manipulator. This paper presents a general kinematic modeling method for mobile manipulators and gives the relevant derivation of the dynamic model. Secondly, the null-space composition of the mobile manipulator is analyzed, the task space is divided, and a variety of task-switching criteria are designed. Finally, a hybrid control model combining dynamic feedback and synovial control based on dynamic parameter identification is designed, and stability proof is given. The theoretical method is also verified by the experimental platform. The proposed method can effectively improve the control accuracy of the mobile manipulator, and the hybrid control method can effectively control the output torque to reach the ideal state.

In this paper, we study the finite-time formation control problem of uncertain nonholonomic mobile robots following a parameterized path. A path-guided formation control scheme based on an extended state observer is proposed. To compensate for unmeasured velocities and disturbances simultaneously, a third-order fast finite-time extended state observer (FFTESO) is proposed. Then, a distributed formation control solution is developed to achieve the kinematic and dynamic system coordination control of the nonholonomic mobile robots. For the kinematic system control, a path-parameter-updating law is developed for a virtual leader, and the desired linear velocity and heading angle are developed for the mobile robots. For the kinetic control, an anti-disturbance control protocol is designed based on the estimated signals. The salient features of the proposed algorithms lie in that the estimations of disturbances and unmeasured velocities are achieved against the system’s nonholonomic constraints, and the path following the control and cooperative control is synthesized together for path-guided formation, which reduces the complexity of the controller design. Finally, simulation studies are conducted to demonstrate the effectiveness of the proposed algorithm.

Deep learning has been widely used in different fields such as computer vision and speech processing. The performance of deep learning algorithms is greatly affected by their hyperparameters. For complex machine learning models such as deep neural networks, it is difficult to determine their hyperparameters. In addition, existing hyperparameter optimization algorithms easily converge to a local optimal solution. This paper proposes a method for hyperparameter optimization that combines the Sparrow Search Algorithm and Particle Swarm Optimization, called the Hybrid Sparrow Search Algorithm. This method takes advantages of avoiding the local optimal solution in the Sparrow Search Algorithm and the search efficiency of Particle Swarm Optimization to achieve global optimization. Experiments verified the proposed algorithm in simple and complex networks. The results show that the Hybrid Sparrow Search Algorithm has the strong global search capability to avoid local optimal solutions and satisfactory search efficiency in both low and high-dimensional spaces. The proposed method provides a new solution for hyperparameter optimization problems in deep learning models.

It is too difficult to directly obtain the correspondence features between the two-dimensional (2D) laser-range-finder (LRF) scan point and camera depth point cloud, which leads to a cumbersome calibration process and low calibration accuracy. To address the problem, we propose a calibration method to construct point-line constraint relations between 2D LRF and depth camera observational features by using a specific calibration board. Through the observation of two different poses, we construct the hyperstatic equations group based on point-line constraints and solve the coordinate transformation parameters of 2D LRF and depth camera by the least square (LSQ) method. According to the calibration error and threshold, the number of observation and the observation pose are adjusted adaptively. After experimental verification and comparison with existing methods, the method proposed in this paper easily and efficiently solves the problem of the joint calibration of the 2D LRF and depth camera, and well meets the application requirements of multi-sensor fusion for mobile robots.

The electrohydraulic servo variable speed volume pump control system (hereinafter referred to as ESPCS) is integrated with a permanent magnet synchronous motor (hereinafter referred to as servo motor), a fixed-displacement pump, and a hydraulic cylinder. By controlling the servo motor speed, the output flow of the system can be controlled, as can the displacement, force, and speed of the hydraulic cylinder. Compared with the traditional electro-hydraulic servo valve control system, the ESPCS has the advantages of high power-to-weight ratio, energy saving, and environmental friendliness. However, due to the extremely nonlinear flow output of the ESPCS, further improvement of system control performance is greatly hindered. This paper focuses on the nonlinear characteristics of servo motor, fixed-displacement pump, hydraulic cylinder, and other key components in the system. A compensation method based on nonlinear characteristic mapping is proposed. Compared with the traditional PID control method (pressure control accuracy ± 0.12 MPa), the pressure control accuracy of the system is greatly improved (pressure control accuracy ± 0.037 MPa), which opens up a new way to improve the pressure control accuracy of the ESPCS.

The electro-hydraulic servo pump control system (EHSPCS) is a high-performance control unit that integrates a permanent magnet synchronous motor (PMSM) and a closed hydraulic system (CHS). The design features of high integration and a high power-weight ratio lead to the poor heat dissipation capacity and high thermal balance temperature of the system. Excessive temperature will seriously affect the system’s performance and service life. Therefore, the thermal balance analysis method of the EHSPCS under different loads and different wind speeds was proposed in this paper. Firstly, the PMSM and CHS were taken as research objects to analyze the heating source of the system. The thermal power model was established, and the calculation was performed. The variation rule of the thermal power generated by each component with the load torque under the typical rotating speed was obtained. Secondly, the system’s temperature field thermal balance solution model was established. ANSYS and AMESim software were used to calculate the thermal balance points of the PMSM and CHS under different working conditions. The change rule of the thermal balance temperature field of the EHSPCS under different loads was analyzed with the conditions of the natural cooling and forced wind cooling of the PMSM. Finally, an experimental platform was built for experimental research, and the experimental temperature of the system under different loads and different wind speeds was measured. Through comparison and analysis with the simulation results, the correctness and feasibility of the thermal balance theoretical analysis method were verified. The research results will lay the foundation for thermal balance research on the EHSPCS, and have guiding significance for system design, component selection, and load matching.

In steam turbine control and actuation, the steam control valve plays a key role in operability and reliability. The electrohydraulic regulating system for the steam control valve, usually called the servomotor, needs to be reliable and high performing under nonlinear excitation interference in actual conditions. Currently, electrohydraulic servo valve control technology is widely used in servomotors. Although this technology has good control performance, it still has some technical defects, such as poor antipollution ability, low energy efficiency, large volume size, and limited installation space. Aiming at the abovementioned technical shortcomings of electrohydraulic servo valve control technology, a servomotor-pump-hydraulic cylinder volume control scheme is proposed in this paper, forming a pump-controlled servomotor for the steam control valve. By analyzing the working principle of the pump-controlled servomotor position control in the steam control valve, the mathematical model of a pump-controlled servomotor for the steam control valve is established. The sliding mode variable structure control strategy is proposed, and the variable structure control law is solved by constructing a switching function. To verify the performance of the proposed control method, experimental research was conducted. The research results show that the proposed sliding mode variable structure control strategy has a good control effect, which lays the theoretical and technical foundation for the engineering application and promotion of pump-controlled servomotors for steam control valves and helps the technical upgrade and product optimization of steam turbines.