The Topology Optimization of Oil Cylinder Mounting

The method of the structural topology optimization is often used to design machine in the early stage of the mechanical design.And the mechanical structures use the topology design to produce a new still and lightweight part with the different loading.A new structure is created through overlapping these new optimized structure.

FUZZY COORDINATION AND FORCE/POSITION CONTROL OF ROBOTIC MANIPULATOR

It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.

Impedance force control for position controlled robotic manipulators under the constraint of unknown environments

A force control strategy for position controlled robotic manipulators is presented. On line force feedback data are employed to estimate the local shape of the unknown constraint. The estimated vectors are used to generate the virtual reference trajectory for the target impedance model that is driven by the force error to produce command position. By following the command position trajectory the robotic manipulator can follow the unknown constraint surface while keeping an acceptable force error in a manner depicted by the target impedance model. Computer simulation on a 3 linked planar manipulator and experimental studies on an Adept 3, an SCARA type robotic manipulator, are conducted to verify the force tracking capability of the proposed control strategy.

Decentralized adaptive neural network sliding mode position/force control of constrained reconfigurable manipulators

A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.

Robust scheme of global parallel force/position regulators for robot manipulators under environment uncertainty

A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment： i） uncertainties in environment that are usually not available or difficult to be determined in most practical situations; ii） stability problem or/and integrator windup due to the integration of force error in the force dominance rule in parallel force/position control. It shows that this robust scheme is a good alternative for anti-windup. In the presence of environment uncertainties, global asymptotic stability of the resulting closed-loop system is guaranteed; it environment with complex characteristics. Finally, numerical robot manipulator. also shows robustness of the proposed controller to uncertain simulation verifies results via contact task of a two rigid-links

Application of Artificial Neural Network in Robotic Hybrid Position/Force Control

A hybrid position/force controller is designed for the joint 2 and the joint 3 of thePUMA 560 robot.The hybrid controller includes a multilayered neural network,which canidentify the dynamics of the contacted environment and can optimize the parameters of PIDcontroller.The experimental results show that after having been trained,the robot has sta-ble response to the training patterns and strong adaptive ability to the situation between thepatterns.

Collision avoidance for a mobile robot based on radial basis function hybrid force control technique

Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.

Hybrid H_2/H_∞ force/position control based on neural networks

A neural network control scheme with mixed H2/H∞performance was proposed for robot force/position control under parameter uncertainties and external disturbances. The mixed H2/H∞tracking performance ensures both robust stability under a prescribed attenuation level for external disturbance and H2optimal tracking. The neural network was introduced to adaptively estimate nonlinear uncertainties, improving the system’s performance under parameter uncertainties as well as obtaining the H2/H∞tracking performance. The simulation shows that the control method performs better even when the system is under large modeling uncertainties and external disturbances.

Adaptive hybrid force/position control for an industrial robot： theory and experiments

This paper proposes a feasible force/position control method for industrial robots utilized for such tasks as grinding, polishing, deburring, and so on. Specifically, an adaptive force/position control strategy is designed in this paper which regulates the contact force between a robot and a workpiece to reach any given set-point exponentially fast, and enables the robot to follow a chosen trajectory simultaneously without requiring prior knowledge of the system parameters. The stability of the closed-loop system is analyzed by Lyapunov techniques. To test the validity of the force/position control method, some simulation results are first collected for the closed-loop system. Furthermore, some experiments are implemented on a 5DOF （degree of freedom） industrial robot for the constructed adaptive force controller. Both simulation and experiment results demonstrate the superior performance of the designed adaptive force/position control strategy.

Research on Suspension Gravity Compensation System of Lunar Rover with Magnetic Levitation Servo

In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation method of lunar rover based on the combination of active suspension and active position following of magnetic levitation is proposed,and the overall design is carried out.The dynamic model of the suspension module of microgravity compensation system was established,and the decoupling control between the constant force component and the position servo component was analyzed and verified.The constant tension control was achieved by using hybrid force/position control.The position following control was realized by using fuzzy adaptive PID(proportional⁃integral⁃differential)control.The stable suspension control was realized based on the principle of force balance.The simulation results show that the compensation accuracy of constant tension could reach more than 95%,the position deviation was less than 5 mm,the position deviation angle was less than 0.025°,and the air gap recovered stability within 0.1 s.The gravity compensation system has excellent dynamic performance and can meet the requirements of microgravity simulation experiment of lunar rover.

半坐下肢抬高位在喉梗阻强迫体位气管切开术中的应用

目的 探讨半坐下肢抬高位(V形体位)在喉癌引起的喉梗阻患者强迫体位气管切开术中的应用优势。方法收集2010年1月~2015年1月喉癌强迫体位喉梗阻在半坐位行气管切开术(半坐位组)患者20例,与2015年1月~2019年1月喉癌强迫体位喉梗阻在V形体位下行气管切开术(V形体位组)患者25例,进行临床对比分析。结果 两组患者手术均顺利完成,其中V形体位组4例出现术后并发症,半坐位组7例出现术后并发症,两组比较差异无统计学意义(χ^(2)=2.172,P>0.05)。V形体位组手术总时间及气管切开时间分别为(5.16±0.94)min、(3.44±0.77)min,半坐位组手术总时间及气管切开时间分别为(6.60±0.68)min、(5.00±0.79)min,两者相比差异有统计学意义(t分别为6.67、5.94,P<0.05)。结论 不能平卧的喉癌伴强迫体位喉梗阻患者可考虑采取V形体位行紧急气管切开手术。

Design,analysis and control for an antarctic modular manipulator

Antarctic scientific expedition has important strategic significance. It is an inevitable trend to apply robots to assist researchers during the Antarctic expedition. However, the robot manipula- tors at present have a series of problems and unable to meet the requirements of the Antarctic expe- dition. In this paper, a novel Antarctic modular robot manipulator is proposed, which has a compact structure with modular joints. The robot manipulator has high reliability, and quick assembling-and- disassembling ability. Through well wires arranging and thermal controlling, the manipulator can better adapt to the Antarctic environment. In addition, the work space of the manipulator is serious- ly analyzed, and a new hybrid position/force control method is adopted to make the manipulator per- form better. Simulation results validate the control method and show that the robot manipulator has a good performance to meet the requirements of Antarctic expedition.

Mechanical Design and Drive Control of a Novel Dexterous Hand for On-Orbit Servicing

In order to meet the requirements of on-orbit servicing outside the cabin, a flexible, dexterous hand with easy grasping ability and strong loading capacity is designed. The dexterous hand is comprised of three fingers. Each finger is driven by a set of four linkages. Furthermore, two fingers have a set of axial rotational degrees of freedom. In order to achieve the position control and keep griping stability, the dexterous hand adopts a mechanism of hybrid force/position control. In the end, experimental results demonstrates that the on-orbit servicing dexterous hand has great adaptability and operational capability.

Study on the Robot Robust Adaptive Control Based on Neural Networks

Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The technique will improve the adaptability to environment stiffness when the end-effector is in contact with the environment, and does not require any a priori knowledge on the upper bound of syste uncertainties. Moreover, it need not compute the inverse of inertia matrix. Learning algorithms for neural networks to minimize the force error directly are designed. Simulation results have shown a better force/position tracking when neural network is used.

Position/Force Hybrid Control System for High Precision Aligning of Small Gripper to Ring Object

A position/force hybrid control system based on impedance control scheme is designed to align a small gripper to a special ring object. The vision information provided by microscope vision system is used as the feedback to indicate the position relationship between the gripper and the ring object. Multiple image features of the gripper and the ring object are extracted to estimate the relative positions between them. The end-effector of the gripper is tracked using the extracted features to keep the gripper moving in the field of view. The force information from the force sensor serves as the feedback to ensure that the contact force between the gripper and the ring object is limited in a small safe range. Experimental results verify the effectiveness of the proposed control strategy.

Design and experiment of fuzzy-PID based tillage depth control system for a self-propelled electric tiller

The research on the self-propelled electric tiller is vital for further improving the quality and efficiency of greenhouse rotary tillage operation,reducing the work intensity and operation risk of operators,and achieving environmentally friendly characteristics.Most of the existing self-propelled tillers rely on manual adjustment of the tillage depth.Moreover,the consistency and stability of the tillage depth are difficult to guarantee.In this study,the automatic control method of tillage depth of a self-propelled electric tiller is investigated.A method of applying the fuzzy PID(Proportional Integral Derivative)control method to the tillage depth adjustment system of a tiller is also proposed to realize automatic control.The system uses the real-time detection of the resistance sensor and angle sensor.The controller runs the electronically controlled hydraulic system to adjust the force and position comprehensively.The fuzzy control algorithm is used in the operation error control to realize the double-parameter control of the tillage depth.The simulation and experimental verification of the system are conducted.Results show that the control system applying fuzzy PID can improve the soil breaking rate by 3%in the operation process based on reducing the stability variation of tillage depth by 24%.The control strategy can reach the set value of tillage depth quickly and accurately.It can also meet the requirement of tillage depth consistency during the operation.