基于模糊与自校正技术的超声电机伺服控制

通过电机的工作原理和速度特性分析,选定驱动频率为其控制变量;为实现电机快速而高精度位置控制,引入模糊和自校正复合控制技术,其中,模糊逻辑控制技术意在实现控制的快速性,自校正技术用以提高控制精度;组建了控制系统,完成了相应的控制实验;结果表明:在超声电机上采用这种复合控制技术上可以得到较好的控制效果。     

超声电机测控系统的一种实现方法

设计了一套基于微机的超声电机速度和位置测试与控制系统.该系统解决了超声电机长时间工作时由于压电陶瓷特性的改变导致电机速度不稳定问题,采用PI算法的闭环控制时,电机速度可以稳定在3%之内.位置控制实验结果表明:采用模糊推理 PI控制器对电机进行位置精密伺服控制是完全可行的,精度可以达到0.09°.     

Design of a PID optimized neural networks and PD fuzzy logic controllers for a two‐wheeled mobile robot

In this paper, two intelligent techniques for a two‐wheeled differential mobile robot are designed and presented: A smart PID optimized neural networks based controller (SNNPIDC) and a PD fuzzy logic controller (PDFLC). Basically, mobile robots are required to work and navigate under exigent circumstances where the environment is hostile, full of disturbances such as holes and stones. The robot navigation leads to an autonomous decision making to overcome an obstacle and/or to stop the engine to protect it. In fact, the actuators that drive the robot should in no way be damaged and should stop to change direction in case of insurmountable disturbances. In this context, two controllers are implemented and a comparative study is carried out to demonstrate the effectiveness of the proposed approaches. For the first one, neural networks are used to optimize the parameters of a PID controller and for the second a fuzzy inference system type Mamdani based controller is adopted. The goal is to implement control algorithms for safe robot navigation while avoiding damage to the motors. In these two control cases, the smart robot has to quickly perform tasks and adapt to changing environment conditions while ensuring stability and accuracy and must be autonomous with regards to decision making. Simulations results aren't done in real environments, but are obtained with the Matlab/Simulink environment in which holes and stones are modeled by different load torques and are applied as disturbances on the mobile robot environment. These simulation results and the robot performances are satisfactory and are compared to a PID controller in which parameters are tuned by the Ziegler–Nichols tuning method. The applied methods have proven to be highly robust.     

Design,development, and control of a tough electrohydraulic hexapod robot for subsea operations

Abstract

In this paper, the design, the development, and the control for an 18 degree-of-freedom electrohydraulic hexapod robot for subsea operations are presented. The hexapod, called HexaTerra, can be equipped with a trenching machine, and move over obstacles and on sloped terrain. Optimization techniques are employed to size the robot legs. Rigid body equations of motion and hydraulic dynamics are developed. Compact electrohydraulic components are sized and selected taking into account the leg kinematics and system dynamic analysis. A model-based control system design is implemented in a real-time environment, able to produce the overall functionality and performance. Experimental results obtained from preliminary tests with the developed electrohydraulic hexapod show good controlled performance and demonstrate excellent system stability over obstacles.     

Neuro-fuzzy and model-based motion control for mobile manipulator among dynamic obstacles

This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with unknown dynamic obstacles. A union of both procedures is used to solve the general problems of collision-free motion. The problem of collision-free motion for mobile manipulators has been approached from two directions, Planning and Reactive Control. The dynamic path planning can be used to solve the problem of locomotion of mobile platform, and reactive approaches can be employed to solve the motion planning of the arm. The execution can generate the commands for the servo-systems of the robot so as to follow a given nominal trajectory while reacting in real-time to unexpected events. The execution can be designed as an Adaptive Fuzzy Neural Controller. In real world systems, sensor-based motion control becomes essential to deal with model uncertainties and unexpected obstacles.     

Placement optimization of actuator and sensor and decentralized adaptive fuzzy vibration control for large space intelligent truss structure

Large space truss structure is widely used in spacecrafts.The vibration of this kind of structure will cause some serious problems.For instance,it will disturb the work of the payloads which are supported on the truss,even worse,it will deactivate the spacecrafts.Therefore,it is highly in need of executing vibration control for large space truss structure.Large space intelligent truss system(LSITS) is not a normal truss structure but a complex truss system consisting of common rods and active rods,and there...     

A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results

In this paper an adaptive fuzzy variable structure control (kinematic control) integrated with a proportional plus derivative control (dynamic control) is proposed as a robust solution to the trajectory tracking control problem for a differential wheeled mobile robot. The variable structure controller, based on the sliding mode theory, is a well known, proven control method, fit to deal with uncertainties and disturbances (e.g., structural and parameter uncertainties, external disturbances and operating limitations). To minimize the problems found in practical implementations of the classical variable structure controllers, an adaptive fuzzy logic controller replaces the discontinuous portion of the control signals (avoiding the chattering), causing the loss of invariance, but still ensuring the robustness to uncertainties and disturbances without having any a priori knowledge of their boundaries. Moreover, the adaptive fuzzy logic controller is a feasible tool to approximate any real continuous nonlinear system to arbitrary accuracy, and has a simple structure by using triangular membership functions, a low number of rules that must be evaluated, resulting in a lower computational load for execution, making it feasible for real time implementation. Stability analysis and the convergence of tracking errors as well as the adaptation laws are guaranteed with basis on the Lyapunov theory. Simulation and experimental results are explored to show the verification and validation of the proposed control strategy.     

时滞分布参数系统的移动传感器/执行器防碰撞控制

针对一类状态时滞的分布参数系统,考虑了传感器/执行器间的防碰撞问题和最大通讯距离的最小通讯能耗问题,以及系统的稳定性问题.利用抽象发展方程理论和Lyapunov稳定性方法,设计了一种基于时滞分布参数系统的智能体移动控制策略,包括输出反馈控制器和移动控制力.通过理论推导和仿真实验验证,文中设计的控制策略能够使得时滞分布参数系统是渐近稳定的,同时智能体在移动过程中是防碰撞的,也验证了智能体在最大通讯距离的最小能耗.     

受侧滑和滑移影响的移动机器人自抗扰控制

对存在侧滑和滑移干扰问题的轮式移动机器人轨迹跟踪问题进行研究。首先利用移动机器人系统的运动学模型,通过设计其辅助运动学控制器,使得机器人的辅助速度渐近收敛到期望速度;然后利用反步法思想设计了基于动力学模型的一阶线性自抗扰控制（LADRC）,通过扩张状态观测器（ESO）实时估计和补偿机器人运行过程中的侧滑和滑移干扰,使得机器人的实际速度渐近收敛到辅助速度;最终使得移动机器人的轨迹误差渐近趋近于零。通过仿真及实验验证了所设计方法的有效性。