起重机的在线学习控制

解决港口起重机起升货物的偏摆问题 ,采用经典控制方法效果不好。而一个熟练的司机可以比较好地控制货物的偏摆 ,本文借鉴了他们的经验知识作为建立规则的依据并采用了一种学习控制结构来解决这个问题 ,得到了好的控制效果。     

Payload pendulation and position control systems for an offshore container crane with adaptive‐gain sliding mode control

When container ports are not available for heavy ships, the offshore ship‐to‐ship transfer operation is an alternative method to an inland container terminal. This process is performed between a large container ship and a smaller ship, which is equipped with a container crane, called the mobile harbor or the ship‐mounted crane. The sea‐state condition is a crucial factor in open‐sea operations. The presence of waves, wind, and current disturbances excite the pendulum oscillations of the crane's hanging container. In this study, the problem of payload pendulation and container position for an offshore container crane using an adaptive‐gain sliding mode control (SMC) scheme is investigated. The primary control task during the loading and unloading process is to keep the container in the desired region under the harsh oceanic environment. The proposed control architecture incorporates an adaptive‐gain SMC with a compensation part and a prediction mechanism. Therein, a sliding surface is design to combine the desired sway motion of the payload with the desired trolley trajectory. Furthermore, a varying control gain is proposed in the sliding control, obtained by an adaption law that transitions the system into sliding mode. By constructing an appropriate Lyapunov function, we show that the proposed control law ensures the asymptotic stability of the ship‐mounted crane. Numerical simulations are presented to show the effectiveness and robustness of the proposed control system.     

Steady-state drifting stabilization of RWD vehicles

A control scheme to stabilize rear-wheel-drive (RWD) vehicles with respect to high-sideslip cornering (drifting) steady-states using coordinated steering and drive torque control inputs is presented in this paper. The choice of coordinated control inputs is motivated by the observed data collected during the execution of drifting maneuvers by an expert driver. In addition, the steering and drive torque input variables directly correlate to a human driver's steering wheel and throttle commands. The control design is based on a comprehensive vehicle model with realistic tire force and drive-train characteristics, and validated in a high-fidelity simulation environment.     

Learning to Walk by Imitation in Low-Dimensional Subspaces

In this paper, we provide the first demonstration that a humanoid robot can learn to walk directly by imitating a human gait obtained from motion capture (mocap) data without any prior information of its dynamics model. Programming a humanoid robot to perform an action (such as walking) that takes into account the robot's complex dynamics is a challenging problem. Traditional approaches typically require highly accurate prior knowledge of the robot's dynamics and environment in order to devise complex (and often brittle) control algorithms for generating a stable dynamic motion. Training using human mocap is an intuitive and flexible approach to programming a robot, but direct usage of mocap data usually results in dynamically unstable motion. Furthermore, optimization using high-dimensional mocap data in the humanoid full-body joint space is typically intractable. We propose a new approach to tractable imitation-based learning in humanoids without a robot's dynamic model. We represent kinematic information from human mocap in a low-dimensional subspace and map motor commands in this low-dimensional space to sensory feedback to learn a predictive dynamic model. This model is used within an optimization framework to estimate optimal motor commands that satisfy the initial kinematic constraints as best as possible while generating dynamically stable motion. We demonstrate the viability of our approach by providing examples of dynamically stable walking learned from mocap data using both a simulator and a real humanoid robot.     

Command-induced vibration analysis using input shaping principles

Input shaping is a well-established technique used for reducing the vibratory response of dynamic systems. Analytical tools are available for systems utilizing input shaping. These tools aid in performance analysis by providing intuitive and computationally simple methods for determining key system attributes, such as the residual vibration in response to a command. This paper describes methods whereby arbitrary reference commands may be interpreted as input-shaped commands. This capability allows input shaping analysis tools to be used on systems without input shapers. Experimental results obtained from an industrial 10-ton bridge crane validate the theoretical developments.     

Intelligent Adaptive Motion Control Using Fuzzy Basis Function Networks for Electric Unicycle

This paper presents two intelligent adaptive controllers, called self‐balancing and speed controllers, for self‐balancing and motion control, respectively, of an electric unicycle using fuzzy basis function networks (FBFN), which are employed to approximate model uncertainties and unknown friction between the wheel and the terrain surface. Both controllers are established based on the linearized model of the vehicle whose model uncertainties and parameter variations are caused by different riders and terrain. An adaptive backstepping controller together with online learning FBFN and sensing information of the rider's body inclination then is presented to achieve self‐balancing motion control. By adding an electronic throttle as the input device of speed commands, a decoupling sliding‐mode controller with online learning FBFN is proposed to accomplish self‐balancing and speed control. The performance and merit of the two proposed control methods are exemplified by conducting four simulations and three experiments on a laboratory‐built electric unicycle.     

基于嵌套饱和方法的吊车系统非线性控制

针对吊车系统定位和防摆的控制要求,提出了一种基于嵌套饱和方法的非线性控制策略。对吊车系统动力学方程进行部分反馈线性化,并通过坐标变换将其转化为便于控制器设计的严格前馈级联规范型;在此基础上利用嵌套饱和非线性控制方法设计了吊车定位防摆控制器。仿真结果表明,该方法在较小的控制力作用下实现了吊车系统的定位和防摆,并且对于吊车系统参数的变化具有很强的鲁棒性。     

Autonomous mobile robot model predictive control

This paper presents model predictive control of an autonomous vehicle. Simulation and experimental results have been shown and compared with input–output linearization method. The results obtained show that the MPC is an efficient method that allows for accurate control and navigation of an autonomous vehicle. Model based predictive control is tested in simulations for motion on an inclined plane. This is done to prepare future work regarding the avoidance of the violation of the smoothness condition for exact linearization, while at the same time by modifying the input commands the geometric path planning results are conserved. The approach is presented for the wheel-ground slippage and tip-over avoidance of the three-wheeled vehicle for inclined plane motion. A complete three-dimensional dynamic model using Newtonian dynamics is also presented. Simulation results using a three-wheeled vehicle built in our laboratory illustrate the performance of the proposed controller.     

A Smooth Wave‐Form Shaped Command with Flexible Maneuvering Time: Analysis and Experiments

Shaped commands are used to eliminate residual oscillations of crane payloads. Command jerks are detrimental to the safe and efficient operation of cranes. Smooth shaped commands are recommended to avoid such jerks in motion commands to crane motors. The amplitude of the shaped command is governed by its time length. The time length of the shaped command is highly dependent on the natural period of oscillation of the payload. A flexible time length of the shaped command introduces flexibility in selecting the desired command amplitude that would lead to a reduced stress on the crane actuators. In this work, a smooth wave‐form acceleration command is proposed to eliminate residual oscillations in rest‐to‐rest maneuvers of cranes. The proposed shaped command is derived analytically. The system performance is simulated numerically and validated experimentally on a scaled model of an overhead crane. The proposed wave‐form is further modified to relax the dependence of the profile on the natural period of oscillation of the payload.     

Modeling and constraining human interactions in shared controlutilizing a discrete event framework

Human integration is essential in systems where autonomous control alone would not be successful. In this paper, we present a framework for integrating a human supervisor into an otherwise autonomous control system. To facilitate integration, discrete event systems theory is adopted to model human interactions. It is via this interaction model that human commands can be combined with commands from an automated control system. For control synthesis, a method based on constraints is being used to generate velocity commands from the autonomous task level controller. The constraints are also utilized to limit human input so that erroneous human input is minimized. The methods are demonstrated by experiments     

Performance studies of human operators driving double-pendulum bridge cranes

Oscillation of crane payloads makes it challenging to manipulate payloads quickly, accurately, and safely. The problem is compounded when the payload creates a double-pendulum effect. This paper evaluates an input-shaping control method for reducing double-pendulum oscillations. Human operator performance testing on a 10-ton industrial bridge crane is used to verify the effectiveness and robustness of the method. Fifty operators drove the crane with a standard control pendent, as well as a wireless touchscreen interface. Data from these experiments show that human operators drive the crane much faster and safer with the input-shaping control scheme. Furthermore, considerably less operator effort is required when input shaping is used to limit the oscillation. Additional tests required the operators to drive the crane numerous times over a period of eight days. These experiments show that significant learning occurred when operators did not have the aid of input shaping. However, the performance never approached that achieved by untrained operators using input shaping.     

基于输入整形技术的吊车系统防摆控制

针对传统吊车防摆闭环控制方法存在的控制器设计相对复杂、控制效果不理想、不易实现等问题,提出了一种基于经典控制理论与前馈输入整形技术相结合的控制技术。首先,对吊车系统进行建模并简化数学模型,采用经典控制理论设计吊车的伺服控制系统。其次,在吊车伺服系统的基础上,引入输入整形技术设计吊车系统的ZV输入整形器。最后,通过MATLAB仿真验证所提出控制技术的有效性。     

Modeling and controlling the mobile harbour crane system with virtual prototyping technology

Virtual simulation of the real behaviour of mobile harbour crane (MHC) without using the traditional build-and-test method is an imperative approach to the design stage that can increase the quality of the product by reducing manufacturing cost and errors. This paper introduces an engineering model that describes the mechanical behaviour of MHC, and the control design for increasing the position accuracy. Based on a concept of the MHC, a virtual mechanical model was created using SOLIDWOKS, which was then exported to the Automatic Dynamic Analysis of Mechanical System (ADAMS) environment. This model was simulated to investigate the dynamic behaviour of the MHC system. In addition, an adaptive siding mode PID controller was also developed in MATLAB/Simulink to control the crane trolley position and suppress the swing angle of the load. This co-simulation demonstrates the reliability of the mechanical and control functionalities of the developed system.     

Tracking and load sway reduction for double‐pendulum rotary cranes using adaptive nonlinear control approach

Because of the existence of rotational boom motion, the load sway characteristics is more complex. In particular, when the sway presents double‐pendulum phenomenon, the design of the controller is more challenging. Furthermore, the uncertain parameters and external disturbances in crane system make it difficult for traditional control methods to obtain satisfactory control performance. Hence, this paper presents an adaptive nonlinear controller based on the dynamic model of double‐pendulum rotary crane. Unlike a traditional method, the proposed one does not need to linearize the crane system for controller design; therefore, the control performance can be guaranteed even if the system states are far away from the equilibrium point. By using Lyapunov technique and LaSalle's invariance theorem, it is strictly proved that the whole control system is asymptotically stable at the equilibrium point. The effectiveness of the presented controller is demonstrated via comparative simulations.     

Effects of hoisting on the input shaping control of gantry cranes

The dynamic behavior of a planar gantry crane with hoisting of the load is investigated. The command generation method of input shaping is proposed for reduction of the residual vibration. Several versions of input shaping are evaluated and compared with time-optimal rigid-body commands over a wide range of parameters. Input shaping provides significant reduction in both the residual and transient oscillations, even when the hoisting distance is a large percentage of the cable length. Experimental results from a 15-ton gantry crane at the Savannah River Technology Center are used to support the numerical results.     

An Analytical Approach to Creating Multitouch Gesture Vocabularies in Mobile Devices: A Case Study for Mobile Web Browsing Gestures

This study proposes an analytical approach to the creation of multitouch control-gesture vocabularies applicable to mobile devices. The approach consists of four steps: (a) identifying target commands, (b) extracting gesture features of the target commands, (c) analyzing usage patterns based on elements that consist of multitouch gestures, and (d) creating gesture vocabularies based on the gesture features and elements. Usefulness and practicality of the proposed approach were validated in a case study. The case study created 11 mobile web browsing gestures to improve short-cut interactions. Six volunteers created gestures based on systematic procedures and practical methods. A total of 314 gestures were created in the case study, and the results were compared with those of a previous study that used an empirical approach to design control gestures. The proposed approach helped designers to create appropriate gestures for various commands on mobile devices. It was very practicable for all designers, including even novice users.     

An application of Lyapunov stability analysis to improve the performance of NARMAX models

Previously we presented a novel approach to program a robot controller based on system identification and robot training techniques. The proposed method works in two stages: first, the programmer demonstrates the desired behaviour to the robot by driving it manually in the target environment. During this run, the sensory perception and the desired velocity commands of the robot are logged. Having thus obtained training data we model the relationship between sensory readings and the motor commands of the robot using ARMAX/NARMAX models and system identification techniques. These produce linear or non-linear polynomials which can be formally analysed, as well as used in place of “traditional robot” control code.In this paper we focus our attention on how the mathematical analysis of NARMAX models can be used to understand the robot’s control actions, to formulate hypotheses and to improve the robot’s behaviour. One main objective behind this approach is to avoid trial-and-error refinement of robot code. Instead, we seek to obtain a reliable design process, where program design decisions are based on the mathematical analysis of the model describing how the robot interacts with its environment to achieve the desired behaviour. We demonstrate this procedure through the analysis of a particular task in mobile robotics: door traversal.     

无线远程终端系统的设计与实现

为使手机用户通过手机轻松地控制计算机,研究开发了＂无线远程终端＂系统。利用手机登录WAP网站发送指令至＂信息中转站＂,再由＂信息中转站＂把指令转发给受控计算机,指令经过计算机处理后,受控计算机再通过＂信息中转站＂将运行结果返回给手机,从而实现了一个手机无线远程控制计算机的过程。此设计方法极大地提高了程序的耦合度,方便了用户操作,能够满足用户生活中的信息化需求。     

A Receding Horizon Sliding Controller for Automotive Engine Coldstart: Design and Hardware‐in‐the‐Loop Testing With an Echo State Network High‐Fidelity Model

The aim of the current study is to probe the potential of receding horizon sliding control (RHSC) technique for reducing the coldstart hydrocarbon (HC) emissions of automotive spark‐ignited (SI) engines. The RHSC approach incorporates the potentials of sliding control (SC) and nonlinear model predictive control (NMPC) to employ the future information of the considered engine to keep the system's trajectories close to a stable manifold. To calculate the control commands, the authors adopt an efficient optimization technique, known as the multivariate quadratic fit sectioning algorithm (MQFSA), and also, define three different objective functions, based on l₁, l₂, and l_∞ norms. To demonstrate the efficacy of RHSC controller, its performance is compared with two other well‐known controllers extracted from the literature, namely NMPC and Pontryagin's minimum principle (PMP)‐based controllers. Through numerical simulations for three distinctive operating conditions, it is demonstrated that the RHSC controller is very effective for reducing the total tailpipe HC emissions over the coldstart period of the considered engine system. Moreover, by conducting a hardware‐in‐the‐loop (HIL) test using an echo state network high‐fidelity model, it is indicated that the computational speed of calculating control commands is fast enough to enable RHSC to be used for real‐time implementations in practice.     

Posture control of robot manipulators with fuzzy voice commands using a fuzzy coach–player system

This paper presents a method of controlling robot manipulators with fuzzy voice commands. Recently, there has been some research on controlling robots using information-rich fuzzy voice commands such as 'go little slowly' and learning from such commands. However, the scope of all those works was limited to basic fuzzy voice motion commands. In this paper, we introduce a method of controlling the posture of a manipulator using complex fuzzy voice commands. A complex fuzzy voice command is composed of a set of fuzzy voice joint commands. Complex fuzzy voice commands can be used for complicated maneuvering of a manipulator, while fuzzy voice joint commands affect only a single joint. Once joint commands are learned, any complex command can be learned as a combination of some or all of them, so that, using the learned complex commands, a human user can control the manipulator in a complicated manner with natural language commands. Learning of complex commands is discussed in the framework of fuzzy coach–player model. The proposed idea is demonstrated with a PA-10 redundant manipulator.