Enhancing Design of Visual-Servo Delayed System

A robust adaptive predictor is proposed to solve the time-varying and delay control problem of an overhead crane system with a stereo-vision servo. The predictor is based on the use of a recurrent neural network (RNN) with tapped delays, and is used to supply the real-time signal of the swing angle. There are two types of discrete-time controllers under investigation, i.e., the proportional-integral-derivative (PID) controller and the sliding controller. Firstly, a design principle of the neural predictor is developed to guarantee the convergence of its swing angle estimation. Then, an improved version of the particle swarm optimization algorithm, the parallel particle swarm optimization (PPSO) method is used to optimize the control parameters of these two types of controllers. Finally, a homemade overhead crane system equipped with the Kinect sensor for the visual servo is used to verify the proposed scheme. Experimental results demonstrate the effectiveness of the approach, which also show the parameter convergence in the predictor.     

Nonlinear coupling control laws for an underactuated overhead crane system

In this paper, we consider the regulation control problem for an underactuated overhead crane system. Motivated by recent passivity-based controllers for underactuated systems, we design several controllers that asymptotically regulate the planar gantry position and the payload angle. Specifically, utilizing LaSalle's invariant set theorem, we first illustrate how a simple proportional-derivative (PD) controller can be utilized to asymptotically regulate the overhead crane system. Motivated by the desire to achieve improved transient performance, we then present two nonlinear controllers that increase the coupling between the planar gantry position and the payload angle. Experimental results are provided to illustrate the improved performance of the nonlinear controllers over the simple PD controller.     

An energy exchanging and dropping-based model-free output feedback crane control method

For the overhead crane control problem, velocity-related terms (corresponding to full-state feedback) are generally required in the designed control systems for damping injection to achieve (asymptotic) stability. However, it is known that velocity signals may be noisy or even unmeasurable. Also, most existing controllers require full or partial plant physical parameters like rope length or load mass. To resolve these issues, a model-free energy exchanging and dropping-based control law is proposed to achieve output (only position/swing-angle) feedback control for overhead cranes. We synthesize a total energy function, consisting of the (generalized) crane energy and the controller energy, to render it to achieve its (local) minimum at the desired equilibrium point. The proposed control law is dynamically generated by an artificial block-spring system, which exchanges energy with the crane dynamics and then drops the energy via an elegant dropping mechanism to gradually attenuate the total energy. The corresponding stability and convergence analysis is implemented using some Lyapunov-like analysis. Simulation and experimental results suggest the effectiveness and feasibility of the proposed method for crane control, in terms of rapid swing suppression, efficient trolley positioning, as well as increased robustness.     

Anti-swing control of a hydraulic loader crane with a hanging load

In this paper, anti-swing control for a hydraulic loader crane is presented. The difference between hydraulic and electric cranes are discussed to show the challenges associated with hydraulic actuation. The hanging load dynamics and relevant kinematics of the crane are derived to create the 2-DOF anti-swing controller. The anti-swing controller is added to the electro-hydraulic motion controller via feedforward. A dynamic simulation model of the crane is made, and the control system is evaluated in simulations with a path controller in actuator space. Simulation results show significant reduction in the load swing angle during motion. Experiments are carried out to verify the performance of the anti-swing controller, showing good suppression of the payload angle in practice.     

Adaptive Fuzzy Controller of the Overhead Cranes With Nonlinear Disturbance

Overhead cranes are common industrial structures that are used in many factories and harbors. They are usually operated manually or by some conventional control methods, such as the optimal and PLC-based methods. The theme of this paper is to provide an effective all-purpose adaptive fuzzy controller for the crane. This proposed method does not need the complex dynamic model of the crane system, but it uses trolley position and swing angle information instead to design the fuzzy controller. An adaptive algorithm is provided to tune the free parameters in the crane control system. The ways to speed the transportation and reduce the computational efforts are also given. Therefore, the designing procedure of the proposed controller will be very easy. External disturbance, such as the wind and the hit, which always deteriorates the control performance, is also discussed in this paper to verify the robustness of the proposed adaptive fuzzy algorithm. At last, several experimental results with different wire length and payload weight compare the feasibility and effectiveness of the proposed scheme with conventional methods     

基于滑模预测的三维起重机防摆控制方法研究

为了使起重机安全、高效运行,同时为了减少附加设备,达到节能减排的目标,运用电子防摆控制方法的研究成了国内外学者广泛关注的课题。本文主要针对桥式起重机三维模型,利用滑模预测的方法来设计控制器,使用预测控制中的滚动优化和反馈校正方法来优化滑模轨迹的到达过程,以最终达到削弱抖振和增强鲁棒性的目的。仿真结果表明,该控制方法可以较好地对起重机系统的大、小车及负载的摆角进行控制,高效的消除起重机的摆动,达到了设计的预期目的。     

Payload trajectory tracking of a 5-DOF tower crane with a varying-length hoist cable: A passivity-based adaptive control approach

This paper presents a passivity-based adaptive control method for a 5 degree-of-freedom (DOF) tower crane that guarantees robust payload trajectory tracking. The 5-DOF tower crane system considered in this work features three actuated degrees of freedom (including a varying-length hoist cable) and two unactuated degrees of freedom in the hoist cable sway. The proposed controller includes an adaptive feedforward-like control input that is used to ensure that the tower crane features an output strictly passive input–output mapping. The Passivity Theorem is invoked to guarantee closed-loop input–output stability for any output strictly passive negative feedback controller. A novel approach is developed to bound the time derivative of the system’s mass matrix, which is a critical aspect of the proof of passivity. Experimental tests are performed, which demonstrate the effectiveness of the control law on a small-scale three-dimensional tower crane.     

Maximum Likelihood Identification of a Posture Control System

To identify characteristics of a sensory feedback path of a posture control system without external disturbances, the maximum likelihood identification method was applied to data of an antero-posterior sway during quiet stance. A subject stood on a force plate and the sway angle of a body (input) was measured by a position sensor camera and the ankle joint moment (output) was measured by the force plate. Using data of 500 input-output pairs sampled every 0.1 s, parameters of the sensory feedback path were estimated and frequency response functions were calculated. These showed derivative characteristics that are necessary for stabilization of the posture control system. Gain characteristics under the closed eyes condition tended to be greater than those under the open eyes condition.     

行车电气系统的模糊控制及仿真

行车起重系统主要应用在冶金、机械制造等重型企业,其主要任务是把负载吊起并移动到预定的位置。模糊控制系统是一种自动控制系统,模糊控制不需要对象的数学模型,是解决不确定系统控制的一条有效途径。用模糊控制技术来解决行车吊装设备启停过程中出现的摇摆问题,以便操作者能平稳、安全的驾驶行车。应用Matlab进行仿真模拟,结果表明,行车物料摆角较小,能达到安全平稳的目的。     

Fuzzy motion control of an auto-warehousing crane system

Fuzzy motion control of an auto-warehousing crane system is presented in this paper. Using the concept of linguistic variable, a fuzzy logic controller (FLC) can convert the knowledge and experience of an expert into an automatic control strategy. The designed FLC with a rule base and three sets of parameters is used to control the crane system in x, y, and z directions. The unloaded weight and the fully loaded weight of the crane system in discussion are 1.35×10⁴ kg and 1.5×10⁴ kg, respectively. For various loading conditions and varying distances, the FLC still controls the crane system very well with positioning accuracy less than 2×10 ^-3 m for all directions. The distance-speed reference curve for control of the crane system is designed to meet the engineering specifications of motion such as acceleration, deceleration, maximum speed, and creep speed in each direction, and is generated automatically according to varying distance. The method for designing the distance-speed reference curve can make the crane move at relatively high speed to approach the target position. Simulations of the motion control in the three directions are demonstrated     

二维耦合光学摆镜伺服控制系统

二维耦合光学摆镜是扫描式星载红外光学系统的关键运动部件,其运动特性对伺服系统提出了高精度位置控制与运动解耦的特殊要求。在建模与仿真分析的基础上,提出了一种新的耦合偏移补偿与分割步进的解耦策略,采用位置环与速度环双闭环的PID控制算法,使用有限转角力矩电机和高精度旋转变压器作为执行与测量元件,以DSP为核心构建了二维耦合光学摆镜伺服控制系统。实验结果表明:该方法设计的控制系统二维运动解耦正确,控制精度高,响应时间短,动态特性好且超调小,可广泛应用于高精度摆动扫描控制系统的研究领域,具有很好的工程应用前景。     

Fixed-order gain-scheduling anti-sway control of overhead bridge cranes

Acceleration and deceleration in overhead cranes may induce undesirable load swinging, which is unsafe for the surrounding human operators. In this paper, it is shown that such oscillatory behavior depends on the length of the rope and thus a gain-scheduling control law is proposed to reduce such an effect. Specifically, to take into account the technological limits in the controller implementation, a fixed-order controller is tuned, by also enforcing robustness and performance constraints. The proposed strategy is experimentally tested on a real bridge crane and compared to a time-invariant solution.     

基于AVR单片机的旋转倒立摆设计

对简易旋转倒立摆的各个模块做了相关介绍,对系统的实现方案和设计步骤进行描述。采用ATmega16单片机作为主控元件,以BTS7960模块作为驱动器,使用直流伺服电机作为驱动电机。采用增量式PID算法控制摆杆达到稳定,对摆杆所处位置的角度进行分段,然后采用分段PID算法进行控制,以使摆杆快速趋于稳定状态,得到良好的控制效果。     

起重机轨道检测机器人激光姿态角变结构双闭环控制研究

针对起重机轨道检测机器人上的激光姿态角自动调节系统采用经典PID控制效果不佳,无法满足轨道检测要求的问题,提出采用滑膜变结构双闭环的控制方法。文中建立了激光姿态角自动调节系统的数学模型,基于指数趋近律的方法设计了滑膜变结构控制器,并搭建轨道检测机器人及其激光姿态角调节系统。通过仿真研究可知,滑膜变结构控制下激光姿态角调节的时间比PID控制下快0.11 s,超调量减小了0.3%,且运动平稳。仿真试验研究结果为起重机轨道检测机器人的研发与应用提供了依据。     

Data-based error compensation for georeferenced payload path tracking of automated tower cranes

In order to increase the productivity on construction sites, a current topic of research is the automation of the payload transport by tower cranes. Thereby, a key requirement is to ensure that the tower crane precisely tracks the planned paths and positions the payload at the specified target location. Most of the state-of-the-art tower crane controllers damp load sway while moving each driving system to its desired position. However, the path error also consists of bending displacements of the tower crane’s mechanical structure, observer errors, or sensor offsets once the crane hook position is considered in a fixed georeferenced construction site system. These errors have not been addressed in literature on tower cranes so far. This paper introduces an approach to reduce the path error of automated tower cranes without permanently integrating additional sensors. A regression model is derived for predicting the path error and a least absolute shrinkage and selection operator (LASSO) is used to select the most important features. The predicted error is then used to compute a compensating hook path such that the measured hook path matches the desired hook path. The effectiveness of the approach is experimentally validated utilizing a real large-scale tower crane showing a reduction of the path error of more than 50% and a position accuracy of less than 16 cm.     

Multiple-model control architecture for a quadrotor with constant unknown mass and inertia

This paper presents a methodology for height and yaw angle control of a quadrotor that transports an unknown constant load added before the flight. Based on measurements from the onboard sensors, estimates of inertial parameters – mass and z-axis inertia – and state variables – vertical position, velocity, yaw angle and rate – are provided resorting to Multiple-Model Adaptive Estimators. The number and worst case performance of Kalman filters is selected based on the Baram Proximity Measure. The proposed control methods are a steady state Linear Quadratic Regulator (LQR) with integrative action for the height, and an LQR controller for the yaw angle. The overall system obtained is validated with load variations of up to 10% of the vehicle mass, both in simulation and experimentally, resorting to an off-the-shelf commercially available quadrotor.     

基于速度位置双闭环控制的视轴稳定系统设计

视轴稳定伺服系统用于隔离振动或冲击对摄像系统成像的影响。系统由航向和俯仰框架组成,速度传感器、角位置传感器、航向电机、俯仰电机、主控制器构成了速度、位置双闭环稳定控制系统。利用位置环调节来保证系统准确性的基础上加入速度环调节来提高系统响应速度,使系统的响应时间小于50 ms,过渡时间小于200ms。     

Hybrid control of the Pendubot

Swing up and balance control are two interesting control problems for the Pendubot. Many studies have been conducted for swing up control of the Pendubot. A few results have been reported for feedback stabilization of the Pendubot. In this paper, we apply a new hybrid controller for feedback stabilization of the Pendubot. It is well-known that it is impossible to use smooth feedback to stabilize a class of underactuated mechanical systems around their equilibra, even locally. Various nonsmooth controllers have been presented for feedback stabilization of this type of system. However, most of the studies are either based on theoretical proofs or simulations. There is a strong need for experimental study. The Pendubot arises as a special test bed for this purpose. This experimental study has a particular interest for feedback stabilization of underactuated mechanical systems that are not feedback stabilizable using smooth control     

基于嵌入式的智能塔吊远程控制系统的设计

为提高塔吊操作的可靠性与安全性,解决操作人员高空作业问题,实现塔吊的远程智能化控制,借助于嵌入式技术,研究设计一个基于嵌入式的智能塔吊远程控制系统。系统分为处理器和无线控制器两部分,通过无线控制器中的PC机向塔吊操作人员显示塔机实时运行情况及工作参数等信息,同时位于塔吊上的处理器接收控制器发出的动作指令,通过驱动接口电路控制塔吊的运行。塔吊操作人员远离现场,施工作业的安全性和自动化都得到了极大地提高,减少安全事故发生。     

Controller Resynthesis for Testability Enhancement of RTL Controller/Data Path Circuits

In this paper, we propose a controller resynthesis technique to enhance the testability of register-transfer level (RTL) controller/data path circuits. Our technique exploits the fact that the control signals in an RTL implementation are don't cares under certain states/conditions. We make an effective use of the don't care information in the controller specification to improve the overall testability (better fault coverage and shorter test generation time). If the don't care information in the controller specification leaves little scope for respecification, we add control vectors to the controller to enhance the testability. Experimental results with example benchmarks show an average increase in testability of 9% with a 3–4 fold decrease in test generation time for the modified implementation. The area, delay and power overheads incurred for testability are very low. The average area overhead is 0.4%, and the average power overhead is 4.6%. There was no delay overhead due to this technique in most of the cases.