Adaptive coupling control for overhead crane systems

Due to the requirements of high positioning accuracy, small swing angle, short transportation time, and high safety, both motion and stabilization control for an overhead crane system becomes an interesting issue in the field of control technology development. Since the overhead crane system is subject to underactuation with respect to the load sway dynamics, it is very hard to manipulate the crane system in a desired manner, namely, gantry position tracking and sway angle stabilization. Hence, in this paper, a nonlinear control scheme incorporating parameter adaptive mechanism is devised to ensure the overall closed-loop system stability. By applying the designed controller, the position error will be driven to zero while the sway angle is rapidly damped to achieve swing stabilization. Stability proof of the overall system is given in terms of Lyapunov concept. To demonstrate the effectiveness of the proposed controller, results for both computer simulation and experiments are also shown.     

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.     

Neural-network-based adaptive control for induction servomotordrive system

A neural-network-based adaptive control (NNAC) design method is proposed to control an induction servomotor. In this NNAC design, a neural network (NN) controller is investigated to mimic a feedback linearization control law; and a compensation controller is designed to compensate for the approximation error between the feedback linearization control law and the NN controller. The interconnection weights of the NN can be online tuned in the sense of the Lyapunov stability theorem; thus, the stability of the control system can be guaranteed. Additionally, in this NNAC system design, an error estimation mechanism is investigated to estimate the bound of approximation error so that the chattering phenomenon of the control effort can be reduced. Simulation and experimental results show that the proposed NNAC servomotor control systems can achieve favorable tracking and robust performance with regard to parameter variations and external load disturbances     

Antisway Tracking Control of Overhead Cranes With System Uncertainty and Actuator Nonlinearity Using an Adaptive Fuzzy Sliding-Mode Control

An adaptive fuzzy sliding-mode control (AFSMC) is presented for the robust antisway trajectory tracking of overhead cranes subject to both system uncertainty and actuator nonlinearity. First, a fuzzy sliding-mode control (FSMC) law is designed for the antisway trajectory tracking of the nominal plant. In association with a conventional trajectory tracking control law, this FSMC law guarantees asymptotic stability as well as improved transient response of the load sway dynamics while the trolley tracking error dynamics is rendered uniformly asymptotically stable. Second, a fuzzy uncertainty observer is designed to cope with system uncertainty as well as actuator nonlinearity present in an actual plant, and it is incorporated with the FSMC law for the development of the AFSMC law. In addition to stability analysis, the robust performance of the proposed AFSMC law is verified via numerical simulations and experiments.      

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.     

基于多参数反馈控制的港口桥式吊车实验教学系统设计与分析

文章设计了一种适合教学中使用的桥式吊车实验平台, 在此基础上通过建立模型, 进行速度反馈、位置反馈、角度反馈以及多参数反馈形式的仿真分析, 实现对桥式吊车多方位控制, 从而验证了多参数反馈对于稳定控制的有效性。     

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.     

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.     

A Joint Evaluation of Energy-Efficient Downlink Scheduling and Partial CQI Feedback for LTE Video Transmission

A green cellular technology is proposed to optimize the energy and spectrum resources. Such optimization will require perfect channel state information at the transmitting base station. However, reporting the channel status of the entire bandwidth requires huge undesirable feedback overhead. Therefore, the aim of this paper is to optimize the energy and bandwidth resources while maintaining quality-of-service at the downlink when a partial feedback is considered. In this paper, a modified downlink scheduler based on a Packet Prediction Mechanism (PPM) is conducted at the eNodeB to optimize the energy and spectrum resources. On the user equipment side, a partial channel feedback scheme based on an adaptive feedback threshold is developed. A primary concern of this feedback scheme is to reduce the uplink signaling overhead without a substantial loss in downlink performances. Finally, the downlink packet scheduling and the partial feedback are jointly evaluated to further enhance the system performance. Based on a system-level simulation results, the proposed energy-efficient scheduling with partial feedback has achieved an improvement in EE of up to 79% compared to the PPM scheduler. Besides, it minimizes the degradation caused by the partial channel quality indicator feedback. Thus, the proposed two-sided algorithm gives the best tradeoff between uplink and downlink performances.     

A simple active damping control for compliant base manipulators

When a robotic manipulator is mounted to a crane, boom or mobile platform, it loses its accuracy and speed due to the compliance of the base. This paper presents a simple robust control strategy that will reduce mechanical vibrations and enable better tip positioning. The control algorithm uses the sensory feedback of the base oscillation to modulate the manipulator actuator input to induce the inertial damping forces. The authors' previous work (1999) demonstrated the feasibility of the proposed concept using linear analysis. This work extends the concept to a more general case of a nonlinear multiple link manipulator using acceleration feedback and one sample delayed torque. A simulation and an experimental study show very promising results for a test bed consisting of a two-link manipulator and a compliant base     

Lightweight distributed geographical: a lightweight distributed protocol for virtual clustering in geographical forwarding cognitive radio sensor networks

Recent literature characterizes future wireless sensor networks (WSN) with dynamic spectrum capabilities. When cognitive radio is introduced as a main component of a network, a network management protocol is needed to ensure network connectivity and stability especially in highly dynamic environments. Implementing such protocols in WSN opens more challenges because of the resource constraints in sensor networks. We propose a distributed lightweight solution that fulfills this need for WSN. With this protocol, a node in a multichannel environment is quickly able to establish a control channel with neighboring nodes. Lightweight distributed geographical either increases or reduces the coverage area of the control channel based on perceived interference and adequately takes care of intersecting nodes with minimal overhead. By identifying local minima nodes, it also has the potentiality of reducing route failure by 70% further reducing the time and energy overhead incurred by switching to angle routing or maximum power transmission schemes usually used to solve the local minima issue. The work shows best operating values in terms of duty cycle and signal to noise ratio threshold frequencies and the lightweight nature of lightweight distributed geographical in terms of energy and communication overhead, which suits network management protocols for cognitive radio sensor networks. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic control plane management for software‐defined networks

Software‐defined network (SDN) is an emerging network paradigm that allows flexible network management by providing programmability from a separated control plane. Because of the centralized management scheme that SDN adopts, intensive control plane overhead incurs as the scale of SDN increases. The control plane overhead is mainly caused by a massive amount of control messages generated during data plane monitoring and reactive flow instantiation. By far, very few works have addressed the overhead issue on reaction flow instantiation; therefore, we mainly focus on alleviating such overhead in this work. To achieve this goal, we propose a new control plane management (CPMan) method. CPMan aims to realize the following two objectives: first, reduce the number of control messages exchanged through the control channel and second, evenly distribute the control workload across multiple controllers to mitigate the potential performance bottleneck. To realize the former, we propose a lightweight feedback loop‐based control scheme, whereas for the latter, we propose a dynamic switch‐to‐controller (DSC) placement scheme. To show the feasibility of our proposal, we implemented a prototype of the two proposed schemes on top of a carrier‐grade SDN controller and validated its performance in an emulated network. We achieved approximately 57.13% overhead reduction with feedback loop‐based control scheme, while achieved approximately 98.68% balance ratio with DSC placement scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

Contact transition control via joint acceleration feedback

Stable and controllable transition from free motion to constrained motion is of central importance for robots in contact with the environment in many applications. In this paper, a joint acceleration feedback control scheme of high bandwidth is employed to damp oscillations during the contact transition when the approaching speed does not vanish. In this control scheme, a classical integral force controller is refined by means of joint acceleration and velocity feedback. This is intended to achieve a stable contact transition without need of adjusting the controller parameters adaptive to the unknown or changing environments. Extensive experiments are conducted on the third joint of a three-link direct-drive robot to verify the proposed scheme for the environments of various stiffnesses, including elastic (sponge), less-elastic (cardboard), and hard (steel plate) surfaces. Results are also compared with those by the transition control without the acceleration feedback. The proposed scheme is shown to be promising in terms of robustness, stability and adaptability     

Design of feedback control laws for switching regulators based onthe bilinear large signal model

A method for the design of a linear feedback control law for switching regulators based on the bilinear large-signal model is presented. The resulting system guarantees a satisfactory stability region in the state space, and meets the requirements of large damping on transient responses with small feedback control energy. Large-signal transient responses are simulated and compared with the results obtained by R.W. Erickson et al. (1985). The proposed method is well suited for converter topologies with more than two state variables     

Force control of a very lightweight single-link flexible arm based on coupling torque feedback

In this paper, a feedback control law is proposed for regulating the contact force exerted by a very lightweight single-link flexible manipulator when it comes into contact with a motionless object. This control law is based on a lumped-parameter model. The tracking of the desired contact force is obtained by using a feedback loop control of the coupling torque between the motor and the flexible arm. To achieve a good performance on the force control it is only necessary to measure the coupling torque at the root of the arm. Neither the contact force sensor nor the angular position sensor of the motor are used in the control method. A modified PID controller is proposed for this control law. In this work the force control problem is studied for both free and constrained motions of the flexible manipulator, and a collision detection algorithm is also described.     

An energy feedback control of series resonant converter

An energy feedback control utilizing the resonant tank circuit energy as an inner feedback loop is proposed to improve the stability and dynamic characteristics of the series resonant converter (SRC). The energy-feedback-controlled SRC is modeled and analyzed in discrete time domain. In this analysis, the eigenvalues of the controlled system are dependent on the energy feedback gain ratio, and the design guidelines which can be used to select this ratio are derived. Experimental results show a good agreement with theoretical analysis     

A modified whale-dragonfly algorithm and self-adaptive cuckoo search-based clustering strategy for augmenting network lifetime in wireless sensor networks

Designing an energy efficient and durable wireless sensor networks (WSNs) is a key challenge as it personifies potential and reactive functionalities in harsh antagonistic environment at which wired system deployment is completely infeasible. Majority of the clustering mechanisms contributed to the literature concentrated on augmenting network lifetime and energy stability. However, energy consumption incurred by cluster heads (CHs) are high and thereby results in minimized network lifetime and frequent CHs selection. In this paper, a modified whale-dragonfly optimization algorithm and self-adaptive cuckoo search-based clustering strategy (MWIDOA-SACS) is proposed for sustaining energy stability and augment network lifetime. In specific, MWIDOA-SACS is included for exploiting the fitness values that aids in determining two optimal nodes that are selected as optimal CH and cluster router (CR) nodes in the network. In MWIDOA, the search conduct of dragon flies is completely updated through whale optimization algorithm (WOA) for preventing load balancing at CHs. It minimized the overhead of CH by adopting CHs and CR for collecting information from cluster members and transmitting the aggregated data from CHs to the base station (BS). It included self-adaptive cuckoo search (SACS) for achieving sink mobility using radius, energy stability, received signal strength, and throughput for achieving optimal data transmission process after partitioning the network into unequal clusters. Simulation experiments of the proposed MWIDOA-SACS confirmed better performance in terms of total residual energy by 21.28% and network lifetime by 26.32%, compared to the competitive CH selection strategies.     

Hybrid cascode compensation with feedforward stage for high-speed area-efficient three-stage CMOS amplifiers

Hybrid cascode feedforward compensation (HCFC) is proposed for low-power area-efficient three stage amplifiers driving large capacitive loads. With no overhead in power or area, the total compensation capacitor is divided and shared between two internal high-speed loops instead of solely one loop as is common in prior art. Detailed analysis of HCFC shows significant improvement in terms of stability and bandwidth. This is verified for a 1.2-V amplifier driving a 500-pF capacitive load in 90-nm CMOS technology, where HCFC reduces the total capacitor size and improves the gain-bandwidth by at least 30 and 40 %, respectively, compared to the prevailing schemes.     

多天线两小区蜂窝系统的低开销线性干扰对齐算法

在蜂窝系统中,由于干扰的存在,用户性能受到影响,特别是对于小区边缘用户,其通信质量较差。干扰对齐作为一种能够消除干扰、提高系统容量的技术,近年来受到广泛关注。针对多天线两小区蜂窝系统的边缘用户,本文给出了一种系统开销小、需要天线数少的线性干扰对齐算法。该算法利用发送端预编码矢量消除小区内干扰,利用接收端干扰抑制矢量消除小区间干扰。采用本文算法后,在每个小区有 个用户、基站有 根发送天线、用户有 根接收天线的情况下,只需 和 就可以实现上下行的干扰对齐,整个系统可以达到 的自由度,并且在下行链路中不需要小区间反馈,而在上行链路中只需要较小的小区间反馈。仿真结果表明,本文提出的算法能够以较小的开销实现比以往的算法更好的性能。      

An effective logic BIST scheme based on LFSR-reseeding and TVAC

An effective logic built-in self-test scheme aiming at reducing the area overhead of IC testing and improving the fault average is proposed, which combines strategies of linear feedback shift register (LFSR)-reseeding with test vectors applied by circuit-under-test itself (TVAC). LFSR-reseeding technology is first applied to decrease the size of test set and the number of interior feedback wires, while TVAC technology is applied to decrease the number of stored seeds. An efficient LFSR-reseeding algorithm and a modified quick judgment method for path search are proposed. Experimental results for ISCAS 85 benchmarks demonstrate that the proposed method reduces the number of interior feedback wires more than 50% on average and can achieve full fault coverage with much less groups as well as area overhead compared with previous TVACs.