A cross‐coupling controller using an H∞ scheme and its application to a two‐axis direct‐drive robot

A cross‐coupling controller (CCC) using an H_∞ control scheme has been proposed to reduce the contouring error for a two‐axis, direct‐drive robot in tracking linear and circular contours effectively. Under the consideration that contour‐tracking performance is a primary target over point‐to‐point tracking performance in a trajectory‐tracking task, a CCC has been associated with joint controllers to reduce the contouring error by coordinating the motion of a two‐axis robot arm. Contouring performance can thus be improved significantly. Furthermore, the proposed CCC design, which is a typical Multi‐Input Multi‐Output (MIMO) system with linear time varying (LTV) characteristics, has been verified as being internally stable. A USM (ultrasonic motor)‐driven, two‐axis, direct‐drive robot is utilized to demonstrate the feasibility of the proposed scheme. Several experiments under various operating conditions are performed to validate its efficacy, and the results showed that the proposed scheme can reduce the contouring error significantly. © 2002 Wiley Periodicals, Inc.     

Profit data caching and hybrid disk‐aware Completely Fair Queuing scheduling algorithms for hybrid disks

Recently, a hybrid disk drive that integrates a small amount of flash memory within a mechanical drive has received significant attention. The hybrid drive extends the storage hierarchy by using flash memory to cache data from the mechanical disk. Unfortunately, current caching architectures fail to fully exploit the potential of the hybrid drive. Furthermore, current disk input/output (I/O) schedulers are optimized for rotational mechanical disk drives and thus must be re‐targeted for the hybrid disk drive. In this paper, we propose a new data caching scheme, called Profit Caching, for hybrid drives. Profit Caching is a self‐optimizing caching algorithm. It considers and seamlessly integrates all possible data characteristics that impact the performance of hybrid drives, including read count, write count, sequentiality, randomness, and recency, to determine the caching policy. Moreover, we propose a hybrid disk‐aware Completely Fair Queuing (HA‐CFQ) scheduler to avoid unnecessary I/O anticipations of the CFQ scheduler. We have implemented Profit Caching and HA‐CFQ scheduler in the Linux kernel. Coupled with a trace‐driven simulator, we have also conducted detailed experiments under a variety of workloads. Experimental results show that Profit Caching provides significantly improved performance compared with the previous schemes. In particular, the throughput of Profit Caching outperforms previous Random Access First and FlashCache caching schemes by factors of up to 1.8 and 7.6, respectively. In addition, the HA‐CFQ scheduler reduces the total execution time of the CFQ scheduler by up to 1.74%. Finally, the experimental results show that the runtime overhead of Profit Caching is extremely insignificant and can be ignored. Copyright © 2014 John Wiley & Sons, Ltd.     

H∞ Non‐Fragile Synchronous Guaranteed Control of Uncertainty Complex Dynamic Network with Time‐Varying Delay

A kind of H_∞ non‐fragile synchronization guaranteed control method is put forward for a class of uncertain time‐varying delay complex network systems with disturbance input. The network under consideration includes unknown but bounded nonlinear coupling functions f(x) and the coupling term and node system with time‐varying delays. The nonlinear vector function f(x) need not be differentiable but should satisfy the norm bound. A non‐fragile state feedback controller of the gain with sufficiently large regulation margin is designed. It is ensured that the parameters of the controller could still be effective under small perturbation. The sufficient conditions for the existence of H_∞ synchronous non‐fragile guaranteed control of this system have been obtained by constructing a suitable Lyapunov‐Krasovskii functional, adopting matrix analysis, using the theorem of Schur complement and linear matrix inequalities (LMI). These conditions can guarantee robust asymptotic stability for each node of network with disturbance as well as achieve a prescribed robust H_∞ performance level. Finally, the feasibility of the designed method is verified by a numerical example.     

板球系统的间接模糊自适应控制

针对具有强耦合、不确定摩擦力的多变量非线性板球系统,利用Lyapunov稳定理论,设计一种间接模糊自适应控制器。该控制器可以在确保系统变量在有限范围内变动的同时保持收敛性,并且在系统的增益矩阵不可逆时,使得板球系统稳定并跟踪误差收敛到零邻域内。控制器是由监督、间接模糊自适应和自适应补偿3种控制算法结合的。仿真实验表明,所提出的控制方法能够确保板球系统跟踪控制的稳定性和收敛性。     

Design and Testing of a 2-DOF Ball Drive

Omnidirectional mobile robots offer interesting features for industrial and service applications, in particular, when operating in tight spaces. Compared to car-like nonholonomic vehicles, they provide a higher degree of maneuverability, and often require less complex path planning and control schemes. Three different types of holonomic wheels that enable omnidirectional motion have been proposed in literature: universal, Mecanum, and ball wheel mechanisms. A problem commonly associated with the first two wheel types is that they induce vibrations in the system due to the discontinuous contact points. In this article, a ball wheel mechanism with superior features including slip measurement, free-wheel modus and attrition sensing is presented. The first prototype was built using additive manufacturing. The requirements for the design and possible improvements for future versions are discussed. Based on the presented ball wheel drive, a design for an omnidirectional mobile robot platform driven by three redundant ball wheel units is proposed. The velocity kinematic model of this mobile base is also addressed. Moreover, motion planning for an individual ball drive is demonstrated by means of an online trajectory generation scheme. The pseudocode of the trajectory planning algorithm implemented in LabVIEW is then presented. Finally, the motion characteristics of the ball drive mechanism are tested and its functionality is evaluated in detail. Measurements obtained from these tests show that the slip between the ball wheel and the ground can be estimated quite accurately. Hence, it is expected that these improved dead-reckoning estimates will result in a higher positioning accuracy of the final base.     

Data‐based iterative learning mechanism for unknown input‐output coupling parameters/matrices

In this paper, we explore how to get the information of input‐output coupling parameters (IOCPs) for a class of uncertain discrete‐time systems by using iterative learning technique. Firstly, by taking advantage of repetitiveness of control system and informative input and output data, we design an iterative learning scheme for unknown IOCPs. It is shown that we can get the exact values of IOCPs one by one through running the repetitive system T+1 times if the control system is with identical initial state and noise free. Secondly, we give the iterative learning scheme for unknown IOCPs in the presence of measurement noise, system noise, or initial state drift and analyze the influence factors on the performance of developed iterative learning scheme. Meanwhile, we introduce the maximum allowable control deviation into the iterative learning mechanism to minimize the negative impact of noise on the performance of learning scheme and to enhance the robust of iterative learning scheme. Thirdly, for a class of multiple‐input–multiple‐output systems, we also develop iterative learning mechanism for unknown input‐output coupling matrices. Finally, an illustrative example is given to demonstrate the effectiveness of proposed iterative learning scheme.     

A Novel Robust Constraint Force Servo Control for Under‐actuated Manipulator Systems: Fuzzy and Optimal

We consider the control design for under‐actuated manipulator systems. The task is to drive the system to be close to a prescribed constraint. The system contains uncertainty. It is bounded where the bounding information is prescribed by a fuzzy set (e.g., the bound is close to 1). The initial condition is also prescribed by a fuzzy set. A class of robust control is proposed, which guarantees a deterministic performance. On top of that, the choice of a control design parameter is cast into a fuzzy‐theoretic setting. A performance index, consisting of accumulated fuzzy‐based system performance and control cost, is proposed. The optimal control design parameters, which minimize the performance index, can be obtained by solving two algebraic quartic (fourth‐order) equations. As a result, the control design problem, which addresses both fuzzy and optimal characteristics, is completely solved.     

基于模糊PID的磁悬浮球控制系统研究

针对磁悬浮球系统的本质不稳定性,设计模糊PID算法实现系统的稳定控制,并使之动态性能及稳态性能满足要求;文中首先分析了磁悬浮球系统的基本原理,并进行力学分析,建立系统的数学模型,并对其中的非线性部分进行了平衡点处的线性化,而后采用用PID控制设计,PID可以实现系统的稳定控制,且控制精度较高,但对于动态性能的改善不足,且当模型中的参数改变时,PID参数的适应性较差;因此在PID参数的基础上,采用模糊PID控制,使得系统既可以满足三性要求,又可以使其具有参数变化的适应能力。     

Dynamic intermittent Q‐learning–based model‐free suboptimal co‐design of ‐stabilization

This paper proposes an intermittent model‐free learning algorithm for linear time‐invariant systems, where the control policy and transmission decisions are co‐designed simultaneously while also being subjected to worst‐case disturbances. The control policy is designed by introducing an internal dynamical system to further reduce the transmission rate and provide bandwidth flexibility in cyber‐physical systems. Moreover, a Q‐learning algorithm with two actors and a single critic structure is developed to learn the optimal parameters of a Q‐function. It is shown by using an impulsive system approach that the closed‐loop system has an asymptotically stable equilibrium and that no Zeno behavior occurs. Furthermore, a qualitative performance analysis of the model‐free dynamic intermittent framework is given and shows the degree of suboptimality concerning the optimal continuous updated controller. Finally, a numerical simulation of an unknown system is carried out to highlight the efficacy of the proposed framework.     

ANN-based MPPT algorithm for solar PMSM drive system fed by direct-connected PV array

In this paper, artificial neural network (ANN) based on a maximum power point tracking (MPPT) algorithm is developed for a solar permanent magnet synchronous motor (PMSM) drive system used without a boost converter and batteries. The discontinuous space vector PWM technique is used to drive two-level inverter which is directly fed by three parallel-connected Kyocera KD205GX-LP PV modules. The ANN-based MPPT algorithm estimates the voltages and currents corresponding to maximum powers produced by PV array at the maximum power point (MPP) for swiftly changing situations such as solar radiance and temperature. These maximum powers are given as input signal to vector control algorithm of PMSM. The PMSM is designed by using Infolytica/MotorSolve software so that the phase-to-phase maximum value of its operating voltage is 20 V. The use of three-phase PMSM presents more efficient solutions to the trading solar systems with dc motor or induction motor. Thus, an effective solar system is achieved. The performance of developed ANN-based MPPT algorithm, designed PMSM, vector-controlled driver and solar system is analyzed by using MATLAB/SimPowerSystems blocks under the rapidly changing environmental conditions.

     

Event‐triggered output feedback H∞ control for networked control systems

This paper investigates event‐triggered output feedback H_∞ control for a networked control system. Transmitted through a network under an event‐triggered scheme, the sample outputs of the plant are used to drive the dynamical output feedback controller to generate a new control signal in the discrete‐time domain. The discrete‐time control signals are also transmitted through the network to drive the plant. As a result of two types of transmission delays, the controlled plant and the dynamical output feedback controller are driven by the discrete‐time outputs and control signals at different instants of time. An interval decomposition method is introduced to place the controlled plant and the output feedback controller into the same updated time interval but with updated signals at different instants. Based on a proper Lyapunov‐Krasovskii functional, sufficient conditions are derived to ensure H_∞ performance for the controlled plant. Finally, numerical simulations are used to demonstrate the practical utility of the proposed method.     

磨煤机制粉系统解耦内模控制器的设计及仿真

本文针对工业过程中常见的多变量时滞耦合输入输出系统,基于内模控制结构提出了一种多变量解耦内模控制设计的方法,该方法设计的内模控制器同时具有解耦器和控制器的作用。其优点是能够实现标称系统输出响应之间的近似或完全解耦,并且改善了系统的大迟延的特性。并与PID对角矩阵解耦设计方法相对比,结果表明：解耦内模控制器设计方法有更好的鲁棒性。     

Variable Structure Predefined‐Time Stabilization of Second‐Order Systems

A controller that stabilizes second‐order vector systems in predefined‐time is introduced in this paper. That is, for second‐order systems a controller is designed such that the trajectories reach the origin in a time defined in advance. The proposed controller is a variable structure controller that first drive the system trajectories to a linear manifold in predefined time and then drives the system trajectories to a non‐smooth manifold with the predefined‐time stability property, in predefined time also; this is done in order to avoid the differentiability problem that inherently appears when stabilizing high‐order systems in finite time under the block control principle technique. The proposal is applied to the predefined‐time exact tracking of fully actuated mechanical systems. As an example, the proposed solution is applied to a two‐link planar manipulator, and numerical simulations are conducted to show its performance.     

Design of a two‐level controller for an active suspension system

The paper focuses on a control design for a vehicle suspension system in which a balance between different performance demands is achieved. The starting point of the control design is a full–car model which contains nonlinear components, i.e. the dynamics of the dampers and springs and nonlinear actuator dynamics. In order to handle the high complexity of the problem this paper proposes the design of a two‐level controller of an active suspension system. The required control force is computed by applying a high‐level controller, which is designed using a linear parameter varying (LPV) method. For the control design the model is augmented with weighting functions specified by the performance demands and the uncertainty assumptions. The actuator generating the necessary control force is modelled as a nonlinear system for which a low‐level force‐tracking controller is designed. To obtain the low‐level controller a backstepping method is proposed. As an alternative solution a feedback linearization method is also presented. The operation of the controller is illustrated through simulation examples. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

An improved sum‐of‐squares based approach to fuzzy tracking control design of nonlinear systems

In this paper, using a more general Lyapunov function, less conservative sum‐of‐squares (SOS) stability conditions for polynomial‐fuzzy‐model‐based tracking control systems are derived. In tracking control problems the objective is to drive the system states of a nonlinear plant to follow the system states of a given reference model. A state feedback polynomial fuzzy controller is employed to achieve this goal. The tracking control design is formulated as an SOS optimization problem. Here, unlike previous SOS‐based tracking control approaches, a full‐state‐dependent Lyapunov matrix is used, which reduces the conservatism of the stability criteria. Furthermore, the SOS conditions are derived to guarantee the system stability subject to a given H_∞ performance. The proposed method is applied to the pitch‐axis autopilot design problem of a high‐agile tail‐controlled pursuit and another numerical example to demonstrate the effectiveness and benefits of the proposed method.     

随机激励下板球系统建模与有限时间全状态预设性能跟踪控制

研究板球系统受到随机激励时的数学建模与轨迹跟踪控制问题. 首次建立了板球系统的随机数学模型, 并 结合backstepping方法、有限时间预设性能函数、全状态约束及新的预设性能推导方法设计了具有未知输入饱和的 随机板球系统实际有限时间全状态预设性能跟踪控制器, 实现了随机激励下板球系统的有限时间预设性能轨迹跟 踪控制. 所设计的控制器保证了系统跟踪误差能够被预先给定的有限时间性能函数约束, 并且能在任意给定的停息 时间内收敛到预先给定的邻域内. 最后通过仿真实验验证了所设计控制器具有更好的控制效果.     

Hybrid Model Predictive Power Management of A Fuel Cell‐Battery Vehicle

This paper considers optimal power management of a fuel cell‐battery hybrid vehicle (FCHV) powertrain having three distinct modal configurations (modes): electric motor propelling/battery discharging, propelling/charging, and generating/charging. Each mode has a distinct set of dynamics and constraints. Using component dynamical/algebraic models appropriate to power flow management, the paper develops a supervisory‐level switched system model as an interconnection of subsystems. Given the model, the paper sets forth a hybrid model predictive control strategy based on a minimization of a performance index (PI) that trades off tracking and fuel economy in each operational mode. Specifically, the PI trades off velocity tracking error, battery state of charge variance, and electric drive and hydrogen fuel usages while penalizing frictional braking to encourage regenerative braking. The optimization is performed using an embedded system model and collocation with matlab 's fmincon to compute mode switches and continuous time controls. The methodology avoids the computational complexity of alternate approaches based on, e.g., mixed integer programming. Projection methods for approximating the switched system solution from the embedded solution are empirically evaluated. To demonstrate the methodology, an example of a FCHV is simulated using three standard velocity driving profiles: a sawtooth profile with a hill climb, the EPA urban dynamic driving schedule, and the New European Driving Cycle. Also, drive cycle fuel usage is compared to that from the Equivalent Consumption Minimization Strategy.     

Coupled and decoupled actuation of robotic mechanisms

In this paper, we describe two types of seemingly opposing design and control concepts for the realization of a high performance robotic system. One of them is the coupled drive. It is a design and control strategy to maximize the output power of the robotic system by actively coupling the drive of installed actuators. We show two design examples of the coupled drive - design of a leg mechanism and gait control of the wall-climbing robot NINJA-II, and design of a multi-degrees-offreedom manipulator CT-Arm. Another is the gravitationally decoupled actuation (GDA). This is a design and control strategy to maximize energy efficiency of a robotic system by means of decoupled drive of the installed actuators. We show two design examples based on the GDA - design of leg mechanism and control of quadruped walking robots. In the final part of the paper, we discuss a methodology to merge the two above-mentioned seemingly contradictory design methods and apply the merged concept to posture control of a walking robot on a three-dimensional terrain.     

Boundary control of linear stochastic reaction‐diffusion systems

This paper considers the boundary control problem for linear stochastic reaction‐diffusion systems with Neumann boundary conditions. First, when the full‐domain system states are accessible, a boundary control is designed, and a sufficient condition is established to ensure the mean‐square exponential stability of the resulting closed‐loop system. Next, when the full‐domain system states are not available, an observer‐based control is proposed such that the underlying closed‐loop system is stable. Furthermore, observer‐based controller is designed for the systems with an H_∞ performance. Simulation examples are given to demonstrate the effectiveness and potential of the new design techniques.