A newly robust controller design for the position control ofpermanent-magnet synchronous motor

A robust controller which is designed by employing variable-structure control and linear-quadratic method is presented for a permanent-magnet synchronous motor (PMSM) position control system. It is to achieve accurate control performance in the presence of plant parameter variation and load disturbance. In addition, it possesses the design flexibility of the conventional state feedback control. It is applied to the position control of a PMSM. Simulation and experimental results show that the proposed approach gives a better position response and is robust to parameter variations and load disturbance     

Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation

This study presents an efficient variational region-based active contour model for segmenting images without priori knowledge about the object or background. In order to handle intensity inhomogeneities and noise, we propose to integrate into the region-based local intensity model a global density distance inspired by the Bhattacharyya flow. The local term based on local information of segmented image allows the model to deal with bias field artifact, which arises in data acquisition processes. The global term, which is based on the density distance between the probability distribution functions of image intensity inside and outside the active contour, provides information for accurate segmentation, keeps the curve from spilling, and addresses noise in the image. Intensive 2D and 3D experiments on many imaging modalities of medical fields such as computed tomography, magnetic resonance imaging, and ultrasound images demonstrate the effectiveness of the model when dealing with images with blurred object boundary, intensity inhomogeneities, and noise.     

Moment-based alignment for shape prior with variational B-spline level set

This paper presents a new shape prior-based implicit active contour model for image segmentation. The paper proposes an energy functional including a data term and a shape prior term. The data term, inspired from the region-based active contour approach, evolves the contour based on the region information of the image to segment. The shape prior term, defined as the distance between the evolving shape and a reference shape, constraints the evolution of the contour with respect to the reference shape. Especially, in this paper, we present shapes via geometric moments, and utilize the shape normalization procedure, which takes into account the affine transformation, to align the evolving shape with the reference one. By this way, we could directly calculate the shape transformation, instead of solving a set of coupled partial differential equations as in the gradient descent approach. In addition, we represent the level-set function in the proposed energy functional as a linear combination of continuous basic functions expressed on a B-spline basic. This allows a fast convergence to the segmentation solution. Experiment results on synthetic, real, and medical images show that the proposed model is able to extract object boundaries even in the presence of clutter and occlusion.     

A novel motor drive design for incremental motion system via sliding-mode control method

This paper proposes a particular motor position control drive design via a novel sliding-mode controller. The newly designed controller is especially suitable for the motor incremental motion control which is specified by a trapezoidal velocity profile. The novel sliding-mode controller is designed in accordance with the trapezoidal velocity profile to guarantee the desired performance. A motor control system associated PC-based incremental motion controller with permanent-magnet synchronous motor is built to verify the control effect. The validity of the novel incremental motion controller with sliding-mode control method is demonstrated by simulation and experimental results.     

Estimating stability regions for mismatched uncertain variable structure systems with bounded controllers

We address the problem of the estimation of stability regions of a class of mismatched uncertain variable structure systems with bounded controllers. The estimation of stability regions such as the practical stability region, the asymptotic stability region, and the exponential stability region are discussed. Moreover, the state transformation used in previous paper is no longer needed so that a new estimation result is directly related to the original system states without state transformation.     

Series expansion approach to the analysis and identification of discrete Hammerstein systems

In this paper, a finite–series expansion method is presented for the analysis and parameter identification of a discrete non-linear system that is described by a Hammerstein model consisting of a memoryless gain of polynomial form followed by a linear discrete system. By expanding the system variables in discrete Legendre orthogonal polynomials (DLOPs) and using the shift and product operational properties of DLOPs, the Hammerstein model is converted into a set of linear equations in the DLOP coefficients of unknown output variables and in the system parameters. This converted set of linear algebraic equations is convenient for finding the DLOP coefficients of unknown variables. Also, it allows one to determine the unknown system parameters using the least-squares method when the system input and output data are available.     

Study on Thermal Decomposition of Composite Propellants containing PCP polymer or PCP-HTPB copolymer as a binder

A modified manometric vacuum stability test (MVST) apparatus as well as a differential thermal analyzer (DTA) and a thermogravimetric analyzer (TGA) were used to study thermal decomposition of a series of propellants. The solid propellants contained polycaprolactone (PCP) prepolymer or PCP-HTPB copolymer as binder, ammonium perchlorate (AP) and a nitramine (RDX or HMX) as oxidants, aluminum as fuel, and bis(2,2-dinitropropyl)acetal/formal (BDNPA/F) as plasticizer. The mixtures were cured with an isocyanate (Desmodur N-100). It is found from MVST examinations that propellants containing PCP polymer are more stable than ones containing PCP-HTPB copolymer. The PCP propellants were still stable after 40 hours heating at 135°C. The thermal decomposition reactions of prepared propellants during dynamic heating were indicated by two major stages of weight loss in the TGA traces.     

Zernike moment and local distribution fitting fuzzy energy-based active contours for image segmentation

This paper presents a new region-based active contour model for extracting the object boundaries in an image, based on techniques of curve evolution. The proposed model introduces an energy functional that involves intensity distributions in local image regions and fuzzy membership functions. The local image intensity distribution information used to guide the motion of the contour, in the paper, is derived by Hueckel operator in the neighborhood of each image point. The parameters of Hueckel operator are estimated by a set of orthogonal Zernike moments before curve evolution. Meanwhile, the fuzzy membership functions are used to measure the association degree of each image pixel to the region outside and inside the contour. To minimize the energy functional, instead of solving the Euler–Lagrange equation of the underlying problem, the paper employs a direct method to compute the energy alterations. As a result, the model can deal with images with intensity inhomogeneity. In addition, the model effectively alleviates the sensitivity to contour initialization. Moreover, the model reduces computational cost, avoids problems associated with choosing time steps as well as allows fast convergence to the segmentation solutions. Experimental results on synthetic, real images and comparisons with other models show the desired performances of the proposed model.     

A new switching surface sliding-mode speed control for inductionmotor drive systems

In this paper, a sliding-mode speed controller based on a new switching surface is proposed for induction motor systems. With this variable structure control switching surface, the exponential stability is guaranteed for the speed servo control and insensitivity to uncertainties and disturbances are obtained as well. Moreover, an adaptive variable structure speed control is studied to relax the need for the bound of disturbance in variable structure control. The insensitivity or robustness of the proposed method for general speed servo systems is maintained, and the dynamic performances are improved as well. Finally, the validity of proposed scheme is demonstrated by computer simulations and experimentations     

Model reference adaptive speed control for induction motor driveusing neural networks

A model reference adaptive speed control scheme using neural networks is presented. The robust observer-based model reference tracking control technique is used to establish the training patterns. Then, the trained neural networks are used as an adaptive speed controller to robustly track a reference model for an induction motor drive