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Porous Ti6Al4V was attempted to be produced by using the protein forming method. This study characterizes slurry compositions and processing parameters aimed to obtain porous Ti6Al4V with open porosity, an interconnected porous networks and controllable pore size. Laboratory egg white powder was used as a binding and a foaming agent. A porous Ti6Al4V green body was produced through a gelling process at 80°C and a drying process at 120°C. A good strength porous Ti6Al4V specimen is available after a protein burnout process in an air atmosphere and a sintering process in a vacuum environment. Optical microscopy was performed on the porous Ti6Al4V specimens after each processing step to inspect their porous structure. Carbon and oxygen contents were also analyzed in the specimens during intermediate processing steps. Optimal temperature for protein burnout process is identified to be between 400°C to 450°C for an egg white concentration in the range of 6vol% - 24vol%. Pore sizes approximately 200–700 μm were observed after the sintering process. These experimental results demonstrate prospects on fabricating porous titanium and other metals using the protein forming method.

In this paper, we propose the conceptual use of fuzzy clustering techniques as iterative spatial methods to estimate a posteriori statistics in place of the weighted averaging scheme of the Unscented Kalman filter. Specifically, instead of a linearization methodology involving the statistical linear regression of the process and measurement functions through some deterministically chosen set of test points (sigma points) contained within the “uncertainty region” around the state estimate, we present a variant of the Unscented transformation involving fuzzy clustering techniques which will be applied to the test points yielding “degrees of membership” in which Gaussian shapes can be “fit” using a least squares scheme. Implementation into the Kalman methodology will be shown along with simple state and parameter estimation examples.

Graphical abstract, The reaction mechanism of DNA topoisomerase II (TOP2) involves a covalent double-strand break intermediate in which the enzyme is coupled to DNA via a 5′-phosphotyrosyl bond. This normally transient enzyme-bridged break is stabilised by drugs such as mitoxantrone, mAMSA, etoposide, doxorubicin, epirubicin and idarubicin, which are referred to as TOP2 poisons. Removal of topoisomerase II by the proteasome is involved in the repair of these lesions. In K562 cells, inhibiting the proteasome with MG132 significantly potentiated the growth inhibition by these six drugs that target topoisomerase II, and the highest level of potentiation was observed with mitoxantrone. Mitoxantrone also showed the greatest potentiation by MG132 in three Nalm 6 cell lines with differing levels of TOP2A or TOP2B. Mitoxantrone was also potentiated by the clinically used proteasome inhibitor PS341 (Velcade). We have also shown that proteasome inhibition with MG132 in K562 cells reduces the rate of removal of mitoxantrone or etoposide stabilised topoisomerase complexes from DNA, suggesting a possible mechanism for the potentiation of topoisomerase II drugs by proteasomal inhibition.

The TOP2 poison etoposide has been implicated in the generation of secondary malignancies during cancer treatment. Structural similarities between TOP2 isoforms challenge the rational design of isoform-specific poisons to further delineate these processes. Herein, we describe the synthesis and biological evaluation of a focused library of etoposide analogues, with the identification of two novel small molecules exhibiting TOP2B-dependent toxicity. Our findings pave the way toward studying isoform-specific cellular processes by means of small molecule intervention.

Knock detection occupies a very important role in the ignition control of a Spark Ignition (S.I.) engine. Production-grade knock detection schemes must be computationally efficient and comprise a set of parameters which require calibration during Engine Control Unit (ECU) development. This is typically achieved empirically, whereby a calibration engineer induces knock on the ECU and monitors the detection performance to manually adjust the tunable parameters. In this paper, we propose automatic, on-line calibration of a production-grade, frequency-domain knock detection system. Compared to the conventional method of manual calibration, this method allows for on-line tuning of the parameters based on scientific optimization schemes. It thus enables the implementation of specific objective functions which can meet desired criteria.

The pole placement (PP) technique for design of a linear state feedback control system requires specification of all the closed-loop pole locations even though only a few poles dominate the system's transient response characteristics. The linear quadratic regulator (LQR) method, on the other hand, optimizes the system transient response and does not directly impose the location of the dominant poles. This paper presents a new optimal linear quadratic pole placement (LQPP) technique that simultaneously assigns some poles to exact desired dominant locations (partial pole placement) and adjusts the rest of the poles to optimize an LQ performance index (parametric optimization). As a result, a designer can fashion his control design to benefit from the PP and LQ techniques. The paper only addresses the LQPP technique for a single-input full-state feedback control system.

This paper presents a novel approach to control the formation of a group of unmanned ground vehicles in an outdoor environment. Using Lyapunov stability analysis, a closed loop control law for a differential-drive vehicle is derived to maintain its target position in the formation. This control law is combined with an optimal control strategy to avoid obstacles. A simple fuzzy logic supervisor balances the weight each algorithm has on the output control signals by gradually allowing the obstacle avoidance to take over the steering as obstacles become close. Simulations have shown this supervised optimal control strategy to be an effective algorithm that seamlessly allows the group of vehicles to temporarily break formation to avoid obstacles.

Emerging technologies in modeling and simulation of dynamic systems provide transportation industry with the challenging opportunity to migrate parts of the design and development process of new vehicles to the virtual environments. This paper presents the application of a full vehicle simulation in a distributed real-time simulation configuration. The purpose of the system is to provide for an easy-to use full-vehicle simulation platform that allows human-in-the-Ioop interactive driving with force and motion feedback, and for hardware-in-the-Ioop prototype evaluation through simulation. The contribution that is highlighted in this paper is the networking configuration for distributed simulation. The user front-end in Matlab/Simulink provides a familiar interface where the designer/ engineer is able to pull up any dynamic signal from the vehicle simulation, and is able to replace any subsystem from a remote unit as well.

The ability to determine an accurate global position of a vehicle has many useful commercial and military applications. The differential global positioning system (DGPS) is one of the practical navigation tools used for this purpose. However, the DGPS has limitations arising from slow updates, signal interference, and limited accuracy. This paper describes how vehicle rate sensors ran be used to help a DGPS overcome these limitations. The theoretical background for the sensor fusion is based on the principle of Kalman filtering and a fuzzy logic scheme. Validity of the method was verified by using experimental data from an actual automobile navigating around an urban area. The results demonstrated that the path of the automobile can be continuously traced with high accuracy and repeatability, in spite of the limitations of the DGPS.

In this paper, a review of mechatronics is presented with emphasis on the desired qualities of university graduates as viewed by industry. A detailed description of a sequence of two new courses on automotive mechatronic systems and a specialized laboratory are discussed. The new coursework has been added to the curriculum towards the degree of systems engineer at Oakland University and will be first offered in Fall '97. The development of the courses and the laboratory has been supported by Ford Motor Company.

A hierarchical intelligent control system paradigm for a vision-based autonomous driving scheme is presented for a leader-following HMMWV. This article shows how fuzzy logic is employed to represent knowledge at the organization level, how to resolve conflicting perceived information at the coordination level, and how to carry out the best action for the vehicle at the execution level. After introducing the methodology, simulation and experimental aspects for realizing and testing the scheme are discussed. ©1997 by John Wiley & Sons, Inc.

An innovation for a standard intermittent windshield wiper is the concept of a smart wiper that automatically turns itself on or off and adjusts its wiping cycle according to the intensity of rain. This article describes the development of a smart automatic windshield wiper system using a fuzzy logic-based conductive rain sensor scheme. Fuzzy logic is used to compensate nonlinearities in the sensor and implement intuitive reasoning for automatic operation of the wiper. An M68HC11-based microcontroller was developed to implement and test the smart wiper concept for a car. The proposed approach can be extended to other applications related to rain detection and system actuation.

This paper describes a fuzzy logic (FL) approach for incorporating an expert knowledge-based Traction Control System (TCS) for a four-wheel drive vehicle. The knowledge base is provided by a survey of existing TCS methods, understanding of the TCS hardware components and tyre adhesion characteristics, evaluation of applicable control methods, computer simulation studies, and feedback information from experienced traction test drivers in the automotive industry. The developed FL-bascd TCS was implemented on a Pentium PC system- level traction controller computer installed on a 4x4 pickup truck. Extensive experiments for traction control was conducted at available test facilities and proving grounds. The system-level fuzzy logic approach readily permits modification of old and incorporation of new ideas. The success of this fuzzy logic-based design approach was demonstrated to the government sponsor and industrial partners.

Accurate knowledge on the true ground speed of a vehicle, if available, can be used to enhance advanced vehicle dynamics control systems such as anti-lock brake systems (ABS) and traction control systems (TCS) control schemes. This article describes a fuzzy rule-based Kalman filtering technique that employs an additional accelerometer to complement the wheel-based speed sensor, and produce a more accurate estimation of the true speed of a vehicle. Application of the fuzzy logic rule-based Kalman filter shows that better estimates of the true speed can be achieved even under significant braking skid and traction slip conditions.

This paper presents the ongoing development of a community based, self-management system for diabetes mellitus, which incorporates web-based, SMS and mobile-terminal functionalities. SMS represents the first stage of our system development as it is widely available on all mobile phones, convenient and becoming increasingly popular. We discuss past findings and the need for such a system, as well as design, implementation and system architecture. Poor self-management of diabetes is associated with progression into more complex health issues, manifesting as a significant public health burden and impacting negatively on an individual's quality of life. This approach recognizes that telehealth systems will play an increasingly pertinent role in health systems worldwide.

In this paper, an optimal control approach is used to solve a two-dimensional path planning problem for a differential drive mobile robot. Two optimal control algorithms are presented and analyzed, which consist of a novel implementation of a linear quadratic tracker (LQT), and a dynamic programming (DP) scheme. The algorithms are applied to the task of GPS navigation with obstacle avoidance. The methods aim to find an optimal path where the tracking error to the GPS target is minimized, while avoiding the obstacles present on the vehicle's map. The LQT algorithm minimizes the tracking error to the goal point, while simultaneously maximizing the distance to obstacles. It also makes use of a fuzzy logic system to adjust the optimization parameters according to different environmental scenarios.

The chapter presents an approach to control the biped humanoid robot to ambulate through human imitation. For this purpose a human body motion capturing system is developed using tri-axis accelerometers (attached to human legs and torso). The tilt angle patterns information from the human is transformed to control and teach various ambulatory skills for humanoid robot bipedalism. Lyapunov stability based model reference adaptive controller (MRAC) technique is implemented to address unpredictable variations of the biped system.

Real-Time Simulation and Animation (RTSA) of dynamic control systems has been shown to significantly enhance the interpretation, understanding and evaluation of system response performance. Texas Instruments' TMS320C30 Digital Signal Processor is demonstrated to play a key role in accelerating the simulation speed and, in turn, increasing the graphics quality. The main feature of the approach we used to evaluate an active suspension system includes a multi-processor hardware structure (a PC and a DSP), software controlled interprocessor communication and shared memory, and the RTSA technique. These are discussed in the paper. In fact, the configuration outlined in this paper provides a platform for a high speed computing system. It is suitable for real-time applications such as signal processing, dynamic control and estimation, as well as graphical simulation.

The paper focuses on the development of techniques for solving control engineering problems by applying heuristic search methods. Two main contributions of the work are: theoretical development of heuristic optimal control and its application to real engineering problems. In the sense that intelligence is an ability which maximizes the possibility of reaching a goal in an uncertain environment, heuristic optimal control is an intelligent control method. The paper provides necessary notation, proofs of the basic theories, and examples of heuristic optimal control.

The Stewart platform (SP) is a parallel closed-kinematic chain robotic mechanism that is capable of providing high structural and positional rigidity. Because of its unique capability, the platforms have been employed in many control engineering applications such as simulator shakers, robotic manipulators, etc. However, a main problem often found in the implementation of a real-time controller for the platform is the lack of an efficient algorithm for solving its highly nonlinear forward kinematic transformation (FKT), where one seeks to find the translational and orientational altitudes of the moveable platform from knowing the lengths of the platform linkages. This article describes two new direct and exact methods for computing the translational and rotational displacements of an SP by employing extra transnational displacement sensors (TDSs), in addition to the existing TDSs for the six links of the SP. The key for the approach lies in knowing where to employ the TDSs for determining positional vectors of strategic platform locations. By taking advantage of a tetrahedral geometry, closed-form solutions for the FKT can then be derived and directly evaluated. The new methods produce accurate solutions with only minimal computation necessary. The advantages and disadvantages of the proposed methods are discussed and compared to an existing method. The exact methods are being investigated for an on-line implementation of a nonlinear adaptive control system and redundancy scheme for a 25-ton Stewart platform-based Crew Station/Turret Motion Base Simulator (CS/TMBS) at the U.S. Army Tank-Automotive Command (TACOM).

A local positioning system (LPS) for tracking mobile robots using a newly developed ultra-wideband (UWB) ranging radio technology is presented in this paper. However, measured ranges from these radios often have uncertain biases and large sporadic errors due to multipath and attenuation effect. A fuzzy neighborhood tracking filtering technique was developed to deal with the range outlier problems. A progressive update trilateration filter technique is introduced. The paper then describes a UWB LPS based on triangulation or trilateration of the ranges, which is fused with other vehicle kinematics/dynamics sensors including a compass, rate gyros and wheel speed sensors. The UWB LPS was applied to navigation and guidance of an experimental autonomous mobile robot. Simulation theoretical and real-time experimental results were validated against the true results of the experiment recorded by video.

This paper addresses challenges in managing complex automotive powertrain control systems by employing a heuristic method to determine complex setpoints. Two main areas of focus are the fuzzy determination of the driver characteristics and the gear selection for discrete automatic transmissions. The driver characterization determines how aggressive or docile a driver is and has a weighted impact on the gear selection. The gear selection process captures transmission performance fundamentals and infuses them with logic to eliminate undesired or physically impossible gears.

Legged Robots have tremendous mobility, but they can also be very inefficient. These inefficiencies can be due to suboptimal control schemes, among other things. If your goal is to get from point A to point B in the least amount of time, your control scheme will be different from if your goal is to get there using the least amount of energy. In this paper, we seek a balance between these extremes by looking at both efficiency and speed. We model a walking robot as a rimless wheel, and, using Pontryagin's Maximum Principle (PMP), we find an "on-off" control for the model, and describe the switching curve between these control extremes.

Using wide-angle or omnidirectional camera lenses to increase a mobile robot's field of view introduces nonlinearity in the image due to the 'fish-eye' effect. This complicates distance perception, and increases image processing overhead. Using multiple cameras avoids the fish-eye complications, but involves using more electrical and processing power to interface them to a computer. Being able to control the orientation of a single camera, both of these disadvantages are minimized while still allowing the robot to preview a wider area. In addition, controlling the orientation allows the robot to optimize its environment perception by only looking where the most useful information can be discovered. In this paper, a technique is presented that creates a two dimensional map of objects of interest surrounding a mobile robot equipped with a panning camera on a telescoping shaft. Before attempting to negotiate a difficult path planning situation, the robot takes snapshots at different camera heights and pan angles and then produces a single map of the surrounding area. Distance perception is performed by making calibration measurements of the camera and applying coordinate transformations to project the camera's findings into the vehicle's coordinate frame. To test the system, obstacles and lines were placed to form a chicane. Several snapshots were taken with different camera orientations, and the information from each were stitched together to yield a very useful map of the surrounding area for the robot to use to plan a path through the chicane.

Many robotics problems do not take the dynamics of the actuators into account in the formulation of the control solutions. The fallacy is in assuming that forces/torques can be instantaneously and accurately generated. In practice, actuator dynamics may be unknown. This paper presents a Model Reference Adaptive Controller (MRAC) for the actuators of a biped robot that mimics a human walking motion. The MRAC self-adjusts so that the actuators produce the desired torques. Lyapunov stability criterion and a rate of convergence analysis is provided. The control scheme for the biped robot is simulated on a sagittal plane to verify the MRAC scheme for the actuators. Next, the paper shows how a neural network (NN) can learn to generate its own walking gaits using successful runs from the adaptive control scheme. In this case, the NN learns to estimate and anticipate the reference commands for the gaits.

Real-time digital simulation and graphic animation limited band-width dynamic control systems can significantly enhance the interpretation and understanding of system responses. This paper outlines an efficient techniques for generating the graphics and the timing in real-time simulation and animation of the dynamic control systems using a high-speed high- performance PC-AT microcomputer. For illustration, the simulation and animation results for the adaptive computer controlled suspension of a combat vehicle and for the gun-turret stabilization and tracking control system for combat vehicle are presented.

In this paper, the controllability of a Mecanum omnidirectional vehicle (ODV) is investigated. An adaptive drive controller is developed that guides the ODV over irregular and unpredictable driving surfaces. Using sensor fusion with appropriate filtering, the ODV gets an accurate perception of the conditions it encounters and then adapts to them to robustly control its motion. Current applications of Mecanum ODVs are designed for use on smooth, regular driving surfaces, and don't actively detect the characteristics of disturbances in the terrain. The intention of this work is to take advantage of the mobility of ODVs in environments where they weren't originally intended to be used. The methods proposed in this paper were implemented in hardware on an ODV. Experimental results did not perform as designed due to incorrect assumptions and over-simplification of the system model. Future work will concentrate on developing more robust control schemes to account for the unknown nonlinear dynamics inherent in the system.

The tuning process of Fuzzy Logic Controllers (FLCs) through trial-and-error is usually a tedious and time-consuming task. The significant amount of computation imposed by current techniques used in self organized FLCs coupled with the need for a shortened development cycle in today's fast manufacturing environment, make existing methods practically obsolete. This paper introduces and demonstrates a methodology to simplify the tuning process of self organized FLC. Through identifying what will be described as core membership functions MFs, limiting the tuning process to core MFs, utilizing knowledge from domain experts, and mathematically derive other important MFs from core MFs once the tuning is completed, it will be demonstrated in this paper that the tuning process of FLCs can be greatly simplified.

In every vehicle collision, the work-energy principle must be satisfied, i.e., the work done in stopping the driver must be equal to the driver's kinetic energy. Existing restraint systems such as airbags and seatbelts are designed to minimize injuries by smoothly absorbing the kinetic energy of the occupant during a crash event. Advanced systems are being developed to tailor their level of restraining to the severity of the crash, weight, size and position of the occupant. Starting with a lumped parameter model and ending with a complete crash simulation environment, this paper introduce and demonstrate the benefits of real time control of a novel adaptive restraint system using intelligent control techniques.

Thousands of people die every year in car accidents. Current restraint systems such as conventional seatbelts and airbags are designed to accommodate several occupant/crash scenarios and lack the capability of varying their output during the impact event. This paper introduces and demonstrates the benefits of real time control of a novel adaptive restraint system. Through applying intelligent control techniques, it will be shown in this paper that occupant injuries during frontal crashes can be minimized to much lower levels than what can be achieved today with conventional restraint systems. Our control system will be designed and tested first using a lumped parameter model and second on a complete crash simulation environment.

Today’s advanced microcomputers offer extremely fast processing speed and vibrant high-resolution color graphics capabilities at affordable cost. By using carefully developed courseware (software used for coursework), these technologies can be used to strengthen engineering course delivery and provide laboratory innovation. This paper describes an interactive computer visualization environment in which real-time simulation and animation (RTSA) is used to significantly enhance control engineering curricula. Presented is the potential impact of the proposed environment on control engineering education with illustrative examples. The roles of this new interactive computer learning experience in control engineering curriculum are two-fold: 1) To provide a new method for delivering classroom material whereby real-world control system engineering concepts are introduced via interative RTSA, and 2) To provide an opportunity innovative laboratory assignments where students can analyze, design and modify control engineering systems via interactive RTSA. Positive acceptance and reactions have been widely received from users and audiences of RTSA programs which were incorporated in research projects and control curricula at Oakland University.

A model reference adaptive control (MRAC) technique for vehicle active suspension subsystems is presented. The MRAC automatically self-tunes the active suspension so that disturbance and vibration of a vehicle is reduced to a level determined by an ideal conceptual suspension reference model. The Lyapunov stability method was used in the design of the MRAC. It is shown that the MRAC suspension can accommodate large variances in sprung load and suspension component characteristics and achieves significant improvements over the passive suspension. Real-time simulation and animation (RTSA) software was developed to provide a visual aid for understanding and interpreting the performance of the MRAC suspension. >

Neural networks are known for their ability to learn and classify patterns based on certain criteria defined within the training process. Fuzzy ARTMAP neural networks are examples of such systems where the output is decided based on the input/output pattern training scheme. In this research, we build a fuzzy ARTMAP like neural network that depends on an adaptive Euclidian distance neighborhood rather than the fuzzy AND neighborhood in deciding the network output. It is a supervised input/output clustering algorithm that calculates the Euclidean distance between input patterns and system stored categories (neurons) to determine the corresponding output even when that input pattern has never been seen. Euclidean ARTMAP neural network or better known as EARTMAP neural network is trained according to a certain algorithm that calculates the Euclidean distance and decides to whether include the new pattern in an already existing category (cluster) and update its position in the clustering map, or to consider it as a new category if it is far enough from all of the existing categories. The new location of a cluster center is found by averaging the location of all of the patterns that belong to the cluster itself. This would help in suppressing the white noise level that accompanies those patterns during training. The above mentioned algorithm is tested in a control experiment and worked as a human like system to track a moving target in the plane. The importance of EARTMAP neural network is its ability to imitate certain systems to give a performance that is close to the original performance with a minimum number of categories.

An ultra-wideband (UWB) inter-radio ranging technology with measurement resolution of +/-0.5 ft and range up to 0.5 kilometer under certain FCC regulation was recently introduced. However, measurement data are extremely erroneous due to stochastic variables in the device and multipath radio wave reflections. This paper presents fuzzy logic tuned double tracking filters as a solution to remove misinformation in the data. The 1st tracker locates the overall center of the data in the presence of the large sporadic noise. A fuzzy logic admits only neighborhood data to a 2nd tracker which takes care of smaller deviation noise. The fuzzy neighborhood filter approach has been successfully applied to clean up the UWB radio ranges. Experimental results are shown.

Susceptibility to tuberculosis (TB) may be affected by host genetic factors. Elevated levels of transforming growth factor-beta 1 (TGF-beta(1)) were found in plasma of patients with active TB compared with those of healthy contacts. To investigate the association of TGF-beta(1) gene polymorphisms (C-509T and T869C) and plasma levels with the risk of TB in Hong Kong Chinese adults, a case-control study was carried out on 174 active TB patients and 174 healthy controls matched for age, gender and smoking. Blood samples from 180 blood donors served as another control group. Genotyping was carried out on genomic DNA using polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP). Plasma TGF-beta(1) was measured by commercially available ELISA kit. We found no differences in the distribution of genotypes or alleles of TGF-beta(1) gene polymorphisms at C-509T and T869C between patients and either group of healthy controls. Patients with TB had elevated plasma TGF-beta(1) levels compared with healthy controls irrespective of their genotypes (p0.001). In conclusion, TGF-beta(1) gene polymorphism at C-509T and T869C is not associated with TB susceptibility in Hong Kong Chinese adults, but elevated plasma TGF-beta(1) levels suggests that this cytokine may play a role in the pathogenesis of tuberculosis.