Modified Predictive Control for a Class of Electro-Hydraulic Actuator

Many model predictive control (MPC) algorithms have been proposed in the literature depending on the conditionality of the system matrix and the tuning control parameters. A modified predictive control method is proposed in this paper. The modified predictive method is based on the control matrix formulation combined with optimized move suppression coefficient. Poor dynamics and high nonlinearities are parts of the difficulties in the control of the Electro-Hydraulic Actuator (EHA) functions, which make the proposed matrix an attractive solution. The developed controller is designed based on simulation model of a position control EHA to reduce the overshoot of the system and to achieve better and smoother tracking. The performance of the designed controller achieved quick response and accurate behavior of the tracking compared to the previous study

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 192

This bibliography lists 247 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1979

Steady-State Fuzzy Modeling of Ultrasonic Motor System

Because of the complicated energy conversion process, ultrasonic motor has remarkable nonlinearity. Therefore, it is difficult to achieve accurate speed control of ultrasonic motor. In general, a good model is the foundation of the accurate control effect. Because of the remarkable non-linearity of ultrasonic motor, the model should also be nonlinear. In this paper, the two-input and one-output steady-state model of ultrasonic motor system is worked out using fuzzy reasoning modeling method. Comparison between experimental data and calculated data of the model prove that the model can well simulate the nonlinear relationship among the amplitude of driving voltage, frequency, and rotating speed

Master of Science

thesisNondestructive evaluation (NDE) is a means of assessing the reliability and integrity of a structural component and provides such information as the presence, location, extent, and type of damage in the component. Structural health monitoring (SHM) is a subfield of NDE, and focuses on a continuous monitoring of a structure while in use. SHM has been applied to structures such as bridges, buildings, pipelines, and airplanes with the goal of detecting the presence of damage as a means of determining whether a structure is in need of maintenance. SHM can be posed as a modeling problem, where an accurate model allows for a more reliable prediction of structural behavior. More reliable predictions make it easier to determine if something is out of the ordinary with the structure. Structural models can be designed using analytical or empirical approaches. Most SHM applications use purely analytical models based on finite element analysis and fundamental wave propagation equations to construct behavioral predictions. Purely empirical models exist, but are less common. These often utilize pattern recognition algorithms to recognize features that indicate damage. This thesis uses a method related to the k-means algorithm known as dictionary learning to train a wave propagation model from full wavefield data. These data are gathered from thin metal plates that exhibit complex wavefields dominated by multipath interference. We evaluate our model for its ability to detect damage in structures on which the model was not trained. These structures are similar to the training structure, but variable in material type and thickness. This evaluation will demonstrate how well learned dictionaries can both detect damage in a complex wavefield with multipath interference, and how well the learned model generalizes to structures with slight variations in properties. The damage detection and generalization results achieved using this empirical model are compared to similar results using both an analytical model and a support vector machine model

Modeling and simulating the stick-slip motion of the μWalker, a MEMS-based device for μSPAM

In this paper, the accent is on modeling the stick–slip phenomenon of micro devices, where a case shall be presented from the field of scanning probe microactuators. The case is about the lWalker, an electrostatic stepper motor which can deliver forces up to 1.7 mN and has ranges up to 140 lm. For the sake of a reliable operation, it is very important to control the stick–slip effects at the sliding surfaces. In order to introduce the stick–slip effect, a basic model of a mass, spring and sliding surface is presented, accompanied by simulation results. The total model of the device is then shown, again stressing the stick–slip phenomenon at the two sliding surfaces. Simulations from the model presented fit the measurements and can also predict step sizes as a function of varying inputs. Using a model for predictions is very attractive when looking for a way to decrease development cost and time

A New Classification Technique in Mobile Robot Navigation

This paper presents a novel pattern recognition algorithm that use weightless neural network (WNNs) technique.This technique plays a role of situation classifier to judge the situation around the mobile robot environment and makes control decision in mobile robot navigation. The WNNs technique is choosen due to significant advantages over conventional neural network, such as they can be easily implemented in hardware using standard RAM, faster in training phase and work with small resources. Using a simple classification algorithm, the similar data will be grouped with each other and it will be possible to attach similar data classes to specific local areas in the mobile robot environment. This strategy is demonstrated in simple mobile robot powered by low cost microcontrollers with 512 bytes of RAM and low cost sensors. Experimental result shows, when number of neuron increases the average environmental recognition ratehas risen from 87.6% to 98.5%.The WNNs technique allows the mobile robot to recognize many and different environmental patterns and avoid obstacles in real time. Moreover, by using proposed WNNstechnique mobile robot has successfully reached the goal in dynamic environment compare to fuzzy logic technique and logic function, capable of dealing with uncertainty in sensor reading, achieving good performance in performing control actions with 0.56% error rate in mobile robot speed

Aerospace Medicine and Biology: A continuing bibliography, supplement 191

A bibliographical list of 182 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1979 is presented

Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences