Adaptive optimal control without weight transport

Many neural control systems are at least roughly optimized, but how is optimal control learned? There are algorithms for this purpose, but in their current forms, they are not suited for biological neural networks because they rely on a type of communication that is not available in the brain, namely, weight transport-transmitting the strengths, or "weights," of individual synapses to other synapses and neurons. Here we show how optimal control can be learned without weight transport. Our method involves a set of simple mechanisms that can compensate for the absence of weight transport in the brain and so may be useful for neural computation generally.     

Adaptive steering control without using measurements of lateral velocity of vehicles

In this paper, we propose an adaptive steering controller without using measurements of lateral velocity of vehicles. At first, we show a new dynamic expression suitable for the design of a stable adaptive steering controller without using the lateral velocity. Next, we develop an ideal vehicle model. In the designed ideal vehicle model, a good steering performance can be achieved even if the drivers’ steering characteristics vary. Finally, an adaptive steering controller is developed, so that the actual vehicles can track ideal vehicle model and realize good steering performance.     

Attitude control without angular velocity measurement: a passivityapproach

It is well known that the linear feedback of the quaternion of the attitude error and the angular velocity globally stabilizes the attitude of a rigid body. In this note, we show that the angular velocity feedback can be replaced by a nonlinear filter of the quaternion, thus removing the need for direct angular velocity measurement. In contrast to other approaches, this design exploits the inherent passivity of the system; a model-based observer reconstructing the velocity is not needed. An application of the proposed scheme is illustrated for the robot control problem. Simulation results are included to illustrate the theoretical results     

Robust formation control without velocity measurement of the leader robot

In this paper a control problem of leader–follower motion coordination of multiple nonholonomic mobile robots is addressed and subsequently in the proposed scheme, a reference trajectory generated based on the information from the leader is tracked by the follower robots. To alleviate demanded information on the leader, specifically to eliminate the measurement requirement or estimation of the leader's velocity and dynamics, a virtual vehicle is constructed whereby its trajectory converges to the reference trajectory of the follower. Trajectory tracking controller is then designed to allow the follower robot to track the virtual vehicle using neural network approximation, in combination with the backstepping and Lyapunov direct design technique and finally the performance and effectiveness of the controller is verified throughout the experiments.     

Projection-based high accuracy measurement of straight line edges

We present a novel projection-based high accuracy algorithm to determine the parameters of a straight edge in a noisy image. Our algorithm is equivalent to applying a set of very long directional operators over a range of finely quantized angles. This is known to improve both signal-to-noise ratio and localization in the measurement of straight line edges, but was rarely used in practice because of the expense and coefficient restrictions of the operators. The algorithm is implemented by taking a set of projections of the original grey level image, filtering the projections, and analyzing the peaks in projection space to estimate line offset and angle. It also includes a procedure to analyze the peaks in projection space which provides an accuracy better than the quantization in offset and angle parameters. The algorithm was tested on synthetic and a large number of real images and offers very high (subpixel) offset and angular accuracy. The advantages of the algorithm over traditional approaches are improved signal-to-noise ratio and localization accuracy (due to the effective use of very long directional edge operators), no need for expensive edge operators and related hardware, and no need for sophisticated thresholding of the gradient image for finding edges. It is robust in the presence of many types of texture, patterned and bias noise, light intensity, and focus change, and is ideal for use in industrial machine vision, where a large number of parts with straight edges are processed.     

Adaptive repetitive learning control of robotic manipulators without the requirement for initial repositioning

This paper presents adaptive repetitive learning control for trajectory tracking of uncertain robotic manipulators. Through the introduction of a novel Lyapunov-like function, the proposed method only requires the system to start from where it stopped at the last cycle, and avoids the strict requirement for initial repositioning for all the cycles. In addition, it is more applicable, as it only requires the variables to be learned in an iteration-independent manner, rather than satisfying the periodicity requirement in a number of the conventional methods. With the adoption of fully saturated learning, all the signals in the closed loop are guaranteed to be bounded, and the iterative trajectories are proven to follow the profiles of desired trajectories over the entire operation interval. The effectiveness of the proposed method is shown through extensive numerical simulation results.     

Adaptive control of a simple nonlinear system without a prioriinformation on the plant parameters

The authors present an adaptive control scheme for nonlinear systems of the form x=c*^Tf(x)+b*u, where f(x) is Lipschitz, c* is a constant vector, and b* is a constant scalar. The control scheme achieves asymptotical model matching without a priori knowledge of the sign of the b* gain. The adaptive scheme is free from singularities in the sense that the estimate of b*, entering in the denominator of the control law, is bounded away from zero. The singularity has been overcome through a suitable modification of the parameter estimates which is based on standard least squares covariance matrix properties     

Adaptive control allocation

In this work we address the control allocation problem for a nonlinear over-actuated time-varying system where parameters affine in the effector model may be assumed unknown. Instead of optimizing the control allocation at each time instant, a dynamic approach is considered by constructing update-laws that represent asymptotically optimal allocation search and adaptation. Using Lyapunov analysis for cascaded set-stable systems, uniform global/local asymptotic stability is guaranteed for the sets described by the system, the optimal allocation update-law and the adaptive update-law.     

Adaptive deadbeat control

An adaptive algorithm is presented to incorporate deadbeat control as a principle design criterion. Since this algorithm does not require the solution of the diophantine equation at each sampling step, it possesses a computational advantage over the existing deadbeat control approaches, and so is suitable for application to adaptive systems. The meeting of the internal stability requirement enables this algorithm to handle easily any stable or unstable, minimum or non-minimum phase system. By selecting the zero assignment of the sensitivity function the system can be made to track a class of changeable reference signals and exhibit a deadbeat response with minimum settling time. Some constraints on the transfer function make sure that the derived controller is realizable. The non-linear saturated system and the lathe system are simulated to illustrate the validity of the proposed design algorithm.     

Adaptive harmonic control

This paper presents adaptive feedback control at individual harmonics for cancellation of periodic disturbances. It is shown that the original idea, that has been around for a long time, can be developed much further to produce robust and highly adaptable controllers. Frequency selective feedback harmonic cancellation (FHC) is presented. Simulations illustrate the effectiveness of the method.     

Adaptive control of PDEs

This paper presents several recently developed techniques for adaptive control of PDE systems. Three different design methods are employed—the Lyapunov design, the passivity-based design, and the swapping design. The basic ideas for each design are introduced through benchmark plants with constant unknown coefficients. It is then shown how to extend the designs to reaction-advection-diffusion PDEs in 2D. Finally, the PDEs with unknown spatially varying coefficients and with boundary sensing are considered, making the adaptive designs applicable to PDE systems with an infinite relative degree, infinitely many unknown parameters, and open loop unstable.     

欠驱动UUV的空间直线路径跟踪控制

针对欠驱动无人水下航行器(UUV)设计了基于视距导航法的路径跟踪控制方法。采用视距导航法建立欠驱动UUV的路径跟踪误差模型将位置误差控制转换为航速控制、艏向角控制和纵倾角控制,使得路径跟踪问题的输出空间从6个自由度降为3个自由度。对简化的3个自由度设计控制器,并证明了控制器的稳定性。最后以空间平行于x轴的直线为参考路径进行了路径跟踪控制仿真,验证了该方法的有效性。     

Adaptive locally optimal control

The paper is concerned with adaptive control of a dynamic process. It is required to choose the best sequence of control signals with the process parameters unknown. The control algorithms are developed by the ‘ decomposition principle ” and local optimization. The properties of an adaptive closed-loop system aro established ; its performance is estimated and parameter identifiability in tho control process is established.     

Adaptive control of delay system

The result of exact model matching for delay systems developed by the author is extended to the adaptive control of delay systems. Likewise, using results from the adaptive control of systems without delay, the principle of constructing adaptive systems for delay plants is also very simple and clear.     

Adaptive automotive speed control

An adaptive algorithm for adjusting the gains of a vehicle speed control system is presented. By continuously adjusting the proportional-integral control gains, speed control performance can be optimized for each vehicle and operating condition. This helps the design of a single speed control module that does not need additional calibration or sacrifices in performance for certain car lines. It also allows improved performance for changing road conditions not possible with a fixed-gain control or other types of adaptive control. The results of initial vehicle testing confirm the performance improvements and robustness of the adaptive controller     

Adaptive control of linearizable systems

The authors give some initial results on the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback. Parameter adaptation is used as a technique to make robust the exact cancellation of nonlinear terms, which is called for in the linearization technique. The application of the adaptive technique to control of robot manipulators is discussed. Only the continuous-time case is considered; extensions to the discrete-time and sampled-data cases are not obvious     

逆变电源的自适应重复控制方案

克服逆变电源系统参数、负载变化和电源死区效应的影响,设计了一种自适应重复控制方案。自适应方案采用跟踪参考序列的模型参考自适应控制设计方法。不需线性补偿器,既简化了设计,又减少了计算量,适合快速跟踪,并适应系统参数和负载的变化。重复控制作为补偿器,补偿死区效应的影响。     

Adaptive control of web guides

Web guides are mechanisms that are used in roll-to-roll material processing machines to control the lateral position of the material while it is transported over rollers in processing machinery; the flexible, continuous materials are often referred to in the industry as “webs”. The process of controlling the lateral position of webs on rollers is referred to as “web guiding”. With the increasing need to transport and process different types of materials under different operating conditions within the same processing machinery, the existing fixed gain control algorithms do not provide adequate performance under these changing conditions and must be re-tuned often to provide satisfactory guiding performance. A controller that will adapt to parameter changes resulting from changes in the material properties, operating conditions, and size and type of guide mechanisms is desired. This paper discusses the design and implementation of model-based adaptive control strategies for web guides based on the dynamic models which describe the lateral behavior of webs. Extensive experiments are conducted for the designed adaptive control strategies for two types of web guides, namely remotely pivoted guide and offset pivot guide. Practical implementation issues and methods to increase robustness of the adaptive strategies are discussed. Experimental results from the adaptive control strategies will be compared with the existing fixed gain PI controller.     

基于流速修正的单直管CMF密度测量方法

科氏流量计(CMF)可以直接测量流体密度,目前单直管CMF的密度测量均未考虑流体流速的影响,密度测量精度受到限制.本文通过力学建模分析,得出了流体流速对单直管CMF密度测量的影响规律,推导了考虑流速影响的单直管CMF密度测量公式,并利用ANSYS Workbench进行了仿真验证.仿真结果表明:当流体流动时,与不考虑流速影响的单直管CMF密度测量结果相比,本文考虑流速影响得到的密度测量值与实际密度值更加吻合.     

Adaptive pole placement without excitation probing signals

This paper presents an indirect adaptive control scheme for linear systems which may possibly be a nonminimum phase. The control scheme achieves asymptotical pole placement without either introducing persistent excitation probing signals into the systems or assuming any a priori knowledge on the plant parameters. The system order is the only a priori knowledge required on the plant. The adaptive control law is free from singularities in the sense that the estimated plant model is always controllable. The singularities are overcome by a suitable parameter estimates modification which is based upon standard least squares covariance matrix properties. The analysis of the stability and the global convergence of a closed-loop system is given in detail for both discrete-time and continuous-time systems