Conventional Adaptive Methods Research Articles

Load adaptive control of single-link flexible arms based on a new modeling technique

A new method for controlling single-link flexible manipulators is proposed. The objective is to control the tip position of a flexible manipulator in the presence of changes in its payload. Particularly, a new adaptive control system has been designed. The proposed control system requires calculating only one parameter, the tip load, instead of all the transfer functions as in conventional adaptive control methods. The tip load identification algorithm is based on the equivalence existing between a manipulator with payload and a manipulator submitted to the action of external forces. Moreover, this equivalence provides a new technique for modeling these systems which simplifies the methods usually applied. This results in a simple control law that needs minimal computing effort and, thus, can be used for real-time control of flexible arms.

Local adaptive slicing

This paper presents a new approach to adaptive slicing that significantly reduces fabrication times. The new approach first identifies the individual parts and features that comprise each layer in a given build, and then slices each independently of one another. This technique improves upon existing adaptive slicing algorithms by eliminating most of the slices that do not effectively enhance the overall part surface quality. Conventional adaptive slicing methods produce unnecessary layers that contribute to increased fabrication times without improving the overall quality of the part surfaces. These unnecessary layers result from fabricating all of the parts and features within the build volume at a given height using a single build layer thickness. Each thickness is commonly derived from the one part or feature existing at that height whose surface geometry requires the thinnest layer to meet a tolerance criterion. The new approach has been implemented on an FDM 1600 rapid prototyping system, and has demonstrated a 17‐37 per cent reduction in fabrication times compared to that of conventional adaptive slicing methods.

Adaptive methods for semi-linear elliptic equations with critical exponents and interior singularities

We consider the effectiveness of adaptive finite element methods for finding the finite element solutions of the parametrised semi-linear elliptic equation Δ u + λ u + u 5 = 0, u > 0, where u ϵ C 2(Ω), for a domain Ω ⊂ R and u = 0 on the boundary of Ω. This equation is important in analysis and it is known that there is a value λ 0 > 0 such that no solutions exist for λ < λ 0 and a singularity forms as λ → λ 0. Furthermore the linear operator L defined by Lφ = Δφ + λφ + 5 u 4φ has a singular inverse in this limit. We demonstrate that conventional adaptive methods (using both static and dynamic regridding) based on usual error estimates fail to give accurate solutions and indeed admit spurious solutions of the differential equation when λ < λ 0. This is directly due to the lack of invertibility of the operator L. In contrast we show that error estimates which take this into account can give answers to any prescribed tolerance.

Adaptive estimation of third-order frequency domain Volterra kernels

Techniques for adaptive estimation of frequency domain Volterra kernels of non-linear systems up to the third order are investigated. A simple adaptive algorithm for identifying the frequency domain Volterra kernels is derived based on the assumption that the input is Gaussian. Compared with the conventional adaptive method based on the recursive least squares (RLS) technique, the proposed method requires substantially less computation and computer memory. The insensitivity of the proposed method to the Gaussianity assumption of the input is also demonstrated via computer simulation and application to experimental data. The results show that the proposed adaptive method is comparable in performance with the conventional RLS-based adaptive method even when the input is non-Gaussian.

Adaptive-Type Predictive Control of Underwater Manipulator.

This paper describes the design of digital control based on predictive control for an underwater manipulator. The discrete time model of the manipulator becomes an uncontrollable system which has nonlinear terms and zero of unstable and/or near by the stability bound zero. Hence, the conventional adaptive control method cannot be directly applied. Kaynak and Hoyer have proposed simple predictive control method. This adaptive control system based on the predictive control method is directly applicable to nonminimum phase systems. However, the stability and convergency of the control system cannot be guaranteed. In this paper, it is shown that the adaptive control system guarantees the stability for most 2nd-order stable systems. Experimental results from a underwater manipulator demonstrate the effectiveness of the adaptive control system.

Adaptive robust control of robot manipulators-theory and experiment

In this paper, a new adaptive robust control scheme for manipulators is proposed that overcomes the drawbacks of conventional adaptive robust control methods. The proposed controller has a simple structure by exploiting the special structure of the manipulator dynamics, and achieves the specified tracking precision without any a priori information on uncertainty. Furthermore, the feedback gain of the proposed method is almost necessary and minimum for the specified precision. To verify the advantages of the method, experimental results are shown for the trajectory control of a 2-DOF direct-drive arm. >

A method for threshold selection in binary images using mean adjacent‐pixel number

AbstractThis paper proposes a method of selecting an appropriate adaptive threshold in binarization (0 or 1) of a gray‐level image. A measure representing compactness of a connected component in an image, “the mean adjacent‐pixel number,” is introduced. The best threshold is determined by taking the maximal of this measure. The method is applied successfully to actual gray‐level images. The results show that appropriate thresholds can be obtained even for difficult images (e.g., a small object in a noisy and low‐contrast image) which are less successful in conventional adaptive methods (e.g., the gray‐level histogram method). Conventional methods using an adaptive threshold generally have a shortcoming in that the amount of computation is proportional to the number of thresholds. This paper also proposes a method to calculate the mean adjacent‐pixel number at a high speed by combining the rank filters and histograms so that the amount of computation becomes independent of the number of thresholds.

On the Development of Equiobservable forms with Application to Adaptive Control

Three types of equiobservable forms are presented for linear time-invariant multivariable systems. These forms are developed using a nonminimal realization of a system and have properties that are useful in the analyis and design of state observation and parameter identific ation problems. By employing the third form, the state equation can be expressed by using filtered values generated from inputs and outputs in an algebraic form, and a new state observer can be obtained. To illustrate tbe application of tbe third form, a multivariable adaptive observer is also discussed. This observer is used to design an two-level adaptive Hight controller for the pitch attitude control system of an aircraft. This approach appears to overcome some of the limitations that are ioberent in the design of tbe Iinear optimal control and conventional adaptive control methods. In particular, the feedback gains of the optimal controller are updated using the estimation provided by the adaptive observer. Tbe firstrlevel of control consists of updated feedforward and optimal controllers. The second-level control is an error servo which provides fine compensation. Extensive simulation studies were carried out and some results are provided for the pitch attitude control of a STOL aircraft under two different flight conditions.