A framework for adaptive motion control of autonomous sociable guide robot

We present a framework by which the motion of an autonomous mobile guide robot is adaptively controlled. A sociable robot should adapt its speed and path to suit the users' activities, without restricting the user movement. By generating adaptive artificial potential fields for the users and the subgoal separately, and integrating them with the basic potential fields generated from obstacles, our robot can adapt to the users' activities and provide sociable tour‐guide services. The robot predicts a user's moving speed and adapts to it to maintain the social distance. Moreover, with the proposed framework, users can deviate from the guided path temporarily and return to the original task afterward. Instead of waiting for the users and taking the risk of losing them, the robot deviates from its original path to follow the users and also prepares for returning to the guiding task. The robot restarts the guiding task at that place, which ensures the least cost to reach the goal. Simulation and experimental results show that our framework can automatically generate suitable motion patterns to control the robot adaptively, making it sociable while providing tour guide services. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

带有逆向力补偿的Stewart平台自适应鲁棒控制

针对Stewart平台复杂的动力学特性以及参数不确定性,提出了带有逆向力补偿自适应鲁棒控制方法.依据对平台动力学特性的分析,采用Lagrange方法建立了上平台的前向动力学模型,同时利用Newton-Euler法对六连杆部分的动态特性进行逆向力补偿,得到了具有机械系统物理特征,且形式简单的误差动态系统.针对上平台参数摄动、逆向力补偿残量以及未建模动态等各种不确定性,依据耗散性理论设计自适应鲁棒控制器.由于平台动力学方程中形式最为复杂的六连杆动态特性被有效地加以补偿,从而控制器中动力学计算部分得以简化.平台动力学方程中上平台部分物理特征明显,可以方便地构造出合适的李雅普诺夫函数.仿真结果验证了该方法的有效性和分析的正确性.     

Disturbance suppression control with preview action for a linear dc brushless motor

This paper proposes a disturbance suppression control with preview action for a brushless and coreless-type linear dc motor. The brushless and coreless-type linear dc motor is coggingless and has long life. It is suitable for high speed and precise positioning control. Parameter variation and load change are regarded as an equivalent disturbance signal and the compensation action is applied by utilizing the estimated value of the equivalent disturbance inside the inner loop. Next, an optimal preview control system is synthesized including the disturbance suppression control system mentioned in the foregoing. Disturbance suppression, improving phase delay and lowering the input peak value are attained in this control system. These effects are confirmed by applying the linear dc motor.     

三相Z源逆变器的最优滑模预见重复控制

针对微网逆变器带不平衡和非线性负载时三相逆变器输出电压电流谐波大的问题,提出一种最优滑模预见重复控制的方法,实现对不平衡负载和非线性负载等非正常工况的快速响应和参考电压的高精度跟踪。首先,在前馈补偿环节引入预见控制器,并利用差分算子,设计包含目标值信号和滞后环节反馈的扩大状态误差系统,将逆变器的控制问题转化为线性离散系统的调节问题;进一步,利用Lyapunov方法和线性矩阵不等式及最优控制器的设计方法,得到包含滑模控制、状态反馈、重复控制、和预见补偿的最优滑模预见重复控制器。实验结果表明,最优滑模预见重复控制带线性负载时电压波形畸变率从3.12%减少到0.78%,响应时间从10 ms减小为5 ms;其带非线性负载时电压波形畸变率从6.72%减少到0.92%,验证了所提方法的有效性。     

Adaptive compensation for infinite number of actuator failures with an application to flight control

In this paper, a new adaptive compensation control scheme is proposed for a class of nonlinear systems with unknown parameters and unknown actuator failures. The normal operation case and different failure cases of actuators are unified through a time‐varying model. By introducing a smooth function, an integrable auxiliary signal, and a bound estimation approach, the effect of failures is successfully compensated for, and the total number of failures is not restricted to be finite. It is shown that all closed‐loop signals are globally uniformly bounded, and the tracking error converges to zero asymptotically regardless of the possibly infinite number of actuator failures. An application to the longitudinal dynamic model of a twin otter aircraft is presented to illustrate the effectiveness of the proposed scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

基于逆系统理论的飞机自动着陆控制系统仿真分析

飞机自动着陆系统是现代飞行控制系统的重要组成部分。为解决飞机的精确定位问题,本文采用非线性逆系统方法对飞机自动着陆系统进行控制。通过状态变换输出与输人间的线性关系使飞机原非线性方程反馈线性化,使原非线性系统解耦为一个一阶和一个二阶线性系统,并设计了神经网络控制器。仿真研究结果表明,基于非线性逆系统的神经网络滑模控制器方法能较好实现飞机自动着陆系统的有效独立控制。     

Precision motion control of a small launching platform with disturbance compensation using neural networks

A kind of launching platform driven by two permanent magnet synchronous motors which is used to launch kinetic load to hit the target always faces strong parameter uncertainties and strong external disturbance such as the air current impulsion which would degrade their tracking accuracy greatly. In this paper, a practical method which combines adaptive robust control with neural network‐based disturbance observer is proposed for high‐accuracy motion control of the launching platform. The proposed controller not only accounts for the parametric uncertainties but also takes the external disturbances into account. Adaptive control is designed to compensate the former, while neural network‐based disturbance observer is designed to compensate the latter respectively and both of them are integrated together via a feedforward cancellation technique. A new kind of parametric adaptation and weight adaptation strategy is designed by using the linear combination of the system's tracking error and the weight estimation error as a driving signal for parametric adaptation and disturbance approximation. The stability of the novel control scheme is analyzed via a Lyapunov method and this method presents a prescribed output tracking performance in the presence of both parameter uncertainties and unmodeled nonlinearities. Extensive comparative simulation and experimental results are obtained to verify the high‐performance of the proposed control strategy. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive prescribed performance control for hydraulic system with disturbance compensation

In this article, an adaptive prescribed performance controller is developed for hydraulic system with uncertainties. An extraordinary feature is that better prescribed performance control can be achieved by compensating the uncertainties including parameter uncertainties and disturbances. For this reason, the transformation of system output error is realized by a prescribed performance function, which is employed to constrain the boundary of tracking error and convergence rate, then the tracking error of the original system with a priori prescribed performance can be realized by stabilizing the transformed system. Adaptive control is employed to solve the system parametric uncertainties; extended state observers are built to estimate the multiple disturbances. Based on the backstepping method, they are integrated into the design of the novel controller to guarantee prescribed tracking error performance. The stability analysis of the proposed controller is carried out via the Lyapunov theory. Finally, experimental results indicate good performance of the proposed algorithm.     

Adaptive state‐feedback control with sensor failure compensation for asymptotic output tracking

This paper addresses a new adaptive output tracking problem in the presence of uncertain plant dynamics and uncertain sensor failures. A new unified nominal state‐feedback control law is developed to deal with various sensor failures, which is directly constructed by state sensor outputs. Such a new state‐feedback compensation control law is able to ensure the desired plant‐model matching properties under different failure patterns. Based on the nominal compensation control design, a new adaptive compensation control scheme is proposed, which guarantees closed‐loop signal boundedness and asymptotic output tracking. The new adaptive compensation scheme not only expands the sensor failures types that the system could tolerate but also avoids some signal processing procedures that the traditional fault‐tolerant control techniques are forced to encounter. A complete stability analysis and a representative simulation study are conducted to evaluate the effectiveness of the proposed adaptive compensation control scheme.     

基于模型预测控制的自主水下航行器模糊回坞导引算法

为了解决自主水下航行器(AUV)的水平面自主回收问题,提出了一种基于模型预测控制(MPC)的模糊回坞导引算法。AUV的回坞导引过程被分为两个阶段,分别是回坞准备阶段和回坞阶段。在回坞准备阶段中,航路点导引AUV向着回收站方向运动;而回坞阶段利用模型预测控制在线求解最优的控制输入导引AUV进入回收站。使用模糊控制理论设计回坞导引系统,利用期望的方向矢量场和模糊规则给出期望的航向角。采用REMUS AUV的模型参数进行MATLAB仿真,仿真表明,基于MPC的模糊回坞导引算法是有效的。AUV能够较快地到达回收站,回坞误差为0.12m。     

某飞机起落架未收起故障解析处理

起落架装置是飞机重要的承力兼操作性的部件,在飞机安全起降过程中,担负着及其重要的使命。起落架是飞机起飞、着陆、滑跑、地面移动和停放所必需的支持系统,是飞机主要部件之一,其性能的优劣直接关系到飞机的安全。本文从飞行过程中起落架未收起的故障现象入手,结合起落架收放的工作原理,建立故障树对故障进行分析排查,最终准确定位故障点。通过建立故障树的分析处理方法,深入了解起落架主要组件及功能实现过程,拓宽了技术人员的排故思路,对相关人员有一定的指导意义。     

水下机器人运动的免疫控制方法

由于水下机器人系统的非线性以及所处环境的不确定性、水下机器人进行精确运动控制技术一直是智能水下机器人技术中急于解决而又难以解决的问题.基于生物免疫系统的生理特性,以免疫系统T细胞、B细胞与免疫应答为基础,引入了一种免疫控算法,并在此算法的基础上又提出基于Sigmoid非线性模型的改进型免疫控制器.大量的仿真实验证明,该新型免疫控制模型,对于水下机器人的运动非线性控制器具有设计简单、响应速度快、超调小、鲁棒性好等各种优点.     

无人驾驶汽车转向控制单元设计

无人驾驶汽车转向控制单元控制转向系统工作,是实现无人驾驶的关键技术.本文介绍了一种结构简单、易于实现且工作可靠的无人驾驶汽车转向控制单元设计方案.无人驾驶汽车转向控制单元通过CAN总线接收来自中央控制系统发送的转向指令,并按一定的控制策略控制转向系统工作,实现自动转向.文中给出了转向控制单元硬件电路与控制策略设计思路.对设计的转向控制单元进行了实车试验,结果表明,该单元能够控制转向系统实现准确、快速、平稳转向,满足了无人驾驶汽车转向要求.     

An autonomous decentralized control mechanism for power flow in an open electric energy network

This paper discusses a power flow control mechanism for the “open electric energy network” (OEEN), which has been studied by the authors as a demand-side network suitable for a free market of electricity. The important concept of OEEN is that electric energy is treated like a packet of mail, with information about the sender (power producer) and the receiver (consumer). The control mechanism discussed in this paper is called the electric energy router and includes an energy storage device. The electric energy router controls the storage device in such a way that the “electricity packet” reaches a specified consumer from a specified power producer autonomously and in the distributed manner. This paper shows that optimal control theory can be applied to determine the control action of the electric energy router. The obtained optimal control action minimizes the difference between the load pattern of the consumer and the supply pattern of the router under the inequality constraints of energy storage capacity. A numerical example is given in order to check the validity of optimal control theory application. In order to manufacture a small-scale electric energy router for experiments, its basic structure and power control performance are studied through simulation studies. © 1998 Scripta Technica. Electr Eng Jpn, 121(4): 28–37, 1997     

Adaptive PI secondary control for smart autonomous microgrid systems

In this paper, the authors present a neural‐network‐based distributed secondary control to regulate the output voltage and frequency of a smart autonomous microgrid system. Generally, the secondary controller is implemented in a centralized manner using a fixed‐gain proportional‐plus‐integral controller which may perform well under certain operating conditions only. Also the failure of centralized controller implies no secondary control action for the entire system. The control technique proposed in this paper is a distributed one and makes use of neural network (NN) concept to improve the performance of system. A well‐trained NN supplies the controller with suitable gains according to each operating point. Before training the NN, evolutionary optimization technique, differential evolution, is employed to obtain the optimal gains of controller at each operating load condition which forms the training set for NN. Simulation results show that the proposed controller damps the oscillations caused by load changes, restores the output voltage and frequency of the system to their nominal values, and maintains proper load sharing property of the baseline controller. The performance of the controller is also compared with fixed‐gain controller. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive cooperative control for air-ground systems with actuator saturation under disturbances

In this article, an adaptive cooperative control strategy is proposed for an air-ground system with actuator saturation. The air-ground system with actuator saturation includes a ground vehicle with road bumps and a quadrotor with gust winds. The adaptive cooperative control strategy is composed of four tracking differentiators, four adaptive extended state observers and two adaptive integral SMC laws. Based on Silverman canonical transformation and pole placement, the adaptive extended state observers are designed to estimate disturbances from the road bumps and gust winds. The adaptive integral SMC laws are proposed to achieve cooperation between the ground vehicle and the quadrotor in the air-ground system with actuator saturation. Simulation results are provided to show effectiveness of the adaptive cooperative control strategy by a ground vehicle and a quadrotor.     

Adaptive robust output‐feedback motion control of hydraulic actuators

Most previous advanced motion control of hydraulic actuators used full‐state feedback control techniques. However, in many cases, only position feedback is available, and thus, there are imperious demands for output‐feedback control for hydraulic systems. This paper firstly transforms a hydraulic model into an output feedback–dependent form. Thus, the K‐filter can be employed, which provides exponentially convergent estimates of the unmeasured states. Furthermore, this observer has an extended filter structure so that online parameter adaptation can be utilized. In addition, it is a well‐known fact that any realistic model of a hydraulic system suffers from significant extent of uncertain nonlinearities and parametric uncertainties. This paper constructs an adaptive robust controller with backstepping techniques, which is able to take into account not only the effect of parameter variations coming from various hydraulic parameters but also the effect of hard‐to‐model nonlinearities such as uncompensated friction forces, modeling errors, and external disturbances. Moreover, estimation errors that come from initial state estimates and uncompensated disturbances are dealt with via certain robust feedback at each step of the adaptive robust backstepping design. After that, a detailed stability analysis for the output‐feedback closed‐loop system is scrupulously checked, which shows that all states are bounded and that the controller achieves a guaranteed transient performance and final tracking accuracy in general and asymptotic output tracking in the presence of parametric uncertainties only. Extensive experimental results are obtained for a hydraulic actuator system and verify the high‐performance nature of the proposed output‐feedback control strategy.     

Adaptive control strategy‐based reference model for spacecraft motion trajectory

In aerospace field, the economic realization of a spacecraft is one of the main objectives that should be accomplished by conceiving the optimal propulsion system and the best control algorithms. This paper focuses on the development of a viable adaptive control approach (ACA) for spacecraft motion trajectory (SMT). The proposed strategy involves the nonlinear mathematical model of SMT expressed in the central field, which is linearized by the Taylor expansion, and the second Lyapunov method to offer a high rate and unfailing performance in the functioning. The adaptive control system is composed of the cascade of adaptation loop and feedback control loop. When the spacecraft deviates from its reference trajectory model, the ACA acts on the control system to correct this deviation and follow the optimal reference trajectory. Therefore, when the states of the adjustable model are different from its reference values, then the error signal is provided as an input to the adaptation law, which contains the adaptation algorithm. The output will be the state variable feedback control matrix, which will be used to calculate the new control law vector. The efficiencies of the linearization procedure and the control approach are theoretically investigated through some realistic simulations and tests under MATLAB. The steady‐state errors of control between the reference model and the adjustable model of SMT converge to zero. Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive control of systems with unknown non-smooth non-linearities

In this paper we unify our recent results in adaptive control of systems with unknown non-smooth non-linearities such as dead-zone, backlash and hysteresis characteristics at the input or output of a linear dynamics. Our adaptive inverse approach employs an adaptive controller structure consisting of an adaptive inverse for cancelling the effect of an unknown non-linearity and a fixed (or adaptive) linear control law for a known (or unknown) linear dynamics. Despite the bilinear dependence on the unknown parameters, a linearly parametrized error system is constructed which enables us to design robust adaptive laws for updating the controller parameters to ensure closed loop signal boundedness and improve system tracking performance. © 1997 by John Wiley & Sons, Ltd.     

Adaptive control for coupled lagrangian systems with structured uncertainty in the interconnections

In this paper, an adaptive control scheme for coupled lagrangian systems is proposed. The interconnection terms among subsystems are assumed to have known structure and depend nonlinearly on uncertain parameters. Also, these coupling functions are restricted to those which are concave or convex with respect to the parameters. Two parameter adaptation laws are used to estimate local and interconnection unknown parameters. Both centralized and decentralized controls are designed. Ultimately bounded tracking with arbitrary precision is achieved regardless of ability to share information among subsystem. A numerical simulation, consisting of two pendulums interconnected by a nonlinear spring, is included to illustrate the effectiveness of the proposed schemes. Copyright © 2013 John Wiley & Sons, Ltd.