Controls and Control Theory Commons^™

Application Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Arton Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Art, Silas Kajuna

Tanzania Journal of Engineering and Technology (TJET)

Vibration is one of the techniques employed in the determination of dynamic properties of fruits and vegetables. It entails generation of a mechanical or acoustic vibrational signal which is propagated through the flesh of the agricultural material. A transducer is either attached or held close to the specimen to monitor the propagation of the signal through the specimen. The manner in which the signal is transmitted through the material is analyzed, and the dynamic properties of the specimen which relate to its firmness or its internal being are derived. The technique has been around for the past 30 years or …

Newton Parameter Update Algorithm For Recurrent Neural Networks Applied To Adaptive System Identification And Control, Donald Allen Gates

Electrical & Computer Engineering Theses & Dissertations

This paper shows that the combination of a second-order neural network parameter update algorithm and internal network feedback can be effectively used for adaptive, nonlinear, dynamical system identification and control. Adaptive neural identification and control algorithms are typically utilized for real-time applications where the rate of adaptation is often critical. A fast, adaptive network parameter update algorithm is presented.

Simulation results show that this algorithm is capable of quickly identifying and adapting to changes in system parameters, making it feasible to use for real-time control and fault accommodation applications.

Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results

Validation Of Waimss Incident Duration Estimation Model, Wei Wu, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

This paper presents an effort to validate the traffic incident duration estimation model of WAIMSS (wide area incident management support system). Duration estimation model of WAIMSS predicts the incident duration based on an estimation tree which was calibrated using incident data collected in Northern Virginia. Due to the limited sample size, a full scale test of the distribution, mean and variance of incident duration was performed only for the root node of the estimation tree, white only mean tests were executed at all other nodes whenever a data subset was available. Further studies were also conducted on the model error …

Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

One of the most important issues in Automated Highway System (AHS) deployment is intelligent vehicle control. While the technology to safely maneuver vehicles exists, the problem of making intelligent decisions to improve a single vehicle’s travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of …

Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.

Development Of Object-Based Teleoperator Control For Unstructured Applications, Hyunki Cho

Theses and Dissertations

For multi-fingered end effectors in unstructured applications, the main issues are control in the presence of uncertainties and providing grasp stability and object manipulability. The suggested concept in this thesis is object based teleoperator control which provides an intuitive way to control the robot in terms of the grasped object and reduces the operator's conceptual constraints. The general control law is developed using a hierarchical control structure, i.e., human interface I gross motion control level in teleoperation control and fine motion control/object grasp stability in autonomous control. The gross motion control is required to provide the position/orientation of the Super …

Neural Generalized Predictive Control For Real-Time Control, Donald I. Soloway

Electrical & Computer Engineering Theses & Dissertations

In this thesis a computationally efficient Generalized Predictive Control (GPC) algorithm is presented and implemented. The algorithm is more efficient than others because the number of iterations needed for convergence is significantly lower with Newton-Raphson. The main additional cost with Newton-Raphson algorithm is the calculation of the Hessian. This overhead is not a problem because of the reduced number of iterations, making the algorithm suitable for real-time control. For nonlinear control applications, a neural network is used as a dynamical system predictor leading to a Neural Generalized Predictive Control (NGPC) algorithm which is presented in detail in this thesis. An …

Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo

Electrical & Computer Engineering Faculty Research

We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results.

Text Independent Speaker Verification Using Binary-Pair Partitioned Neural Networks, Claude A. Norton Iii

Electrical & Computer Engineering Theses & Dissertations

A method is presented for the application of binary-pair partitioned neural networks to the task of speaker verification. This technique is based on a previously developed neural network classifier for speaker identification.

The main focus of this research was the development and testing of the algorithms necessary to extend the binary-pair partitioning approach from speaker identification to speaker verification. The method is based on the development of a user profile which is obtained from discriminative data provided by the binary-pair partitioned neural networks.

Experimental results are provided which demonstrate the viability of this approach, using the TIMIT speech corpus for …

Comparison Of System Identification Techniques For The Dexterous Orbital Servicing System (Doss), Allan Terrence Morris

Electrical & Computer Engineering Theses & Dissertations

The major contribution of system identification is the development of analytical models of a system. Many identification techniques can adequately describe the input and output map. One of the challenges of these techniques is to correctly infer from the measured data the characteristics of the individual, contributing components producing a more accurate system model.

In this thesis linear, dynamic, multivariable state-space models for three joints of the Dexterous Orbital Servicing System (DOSS) are identified. DOSS is a representative space station manipulator at the NASA Langley Research Center. The dynamic models of the manipulator will first be estimated by applying nonparametric …

Optimal Mixed-Norm Control Synthesis For Discrete-Time Linear Systems, David R. Jacques

Theses and Dissertations

A mixed-norm approach to control synthesis for discrete time linear systems is developed. Specifically, the problem of minimizing the H₂ norm of a transfer function, subject to a combination of ℓ₁ and-or H_∞ norm constraints on dissimilar but related transfer functions is considered. The uniqueness of the optimal solution is shown, and numerical methods for approximating the optimal solution to within arbitrary accuracy are developed. These methods generally result in high order compensators which can not be implemented in most practical applications. In response to this, a numerical method is developed which solves for suboptimal solutions of …

Next Generation Real-Time Systems: Investigating The Potential Of Partial-Solution Tasks, Robert E. J. Caley

Theses and Dissertations

While the cyclic executive and fixed-priority scheduling strategies have been sufficient to handle traditional real- time requirements. they are insufficient for dealing with the complexities of next-generation real-time systems. New methods of intelligent control must be developed for guaranteeing on-time task completion for real-time systems that are faced with unpredictable and dynamically changing requirements. Implementing real-time processes as partial-solution tasks is one technique that may be beneficial. This type of task. when combined with intelligent control, has the potential for increasing pre-runtime schedulability, system maintainability. and runtime robustness. This research investigates the benefits of partial-solution tasks by experimentally measuring the …

Dynamic Task Scheduling For The Atamm Multicomputer Operating System Using Embedded Firmware On Microcontrollers, Sudhir Sastry

Electrical & Computer Engineering Theses & Dissertations

A dynamic task scheduling strategy for the distributed processing of large grain dataflow algorithms using embedded firmware on an ATAMM testbed consisting of interconnected microcontrollers is presented in this thesis. The ODU/NASA developed Algorithm to Architecture Mapping Model, ATAMM, uses marked graph models to specify data and control flow for the execution of iterative, deterministic large grain dataflow algorithms in a multicomputing environment. The testbed consists of a bank of four 68HC11 microcontrollers that communicate over a token bus. The token bus arbitration scheme used is contention free and well suited for real-time computing applications. The execution of data flow …

Investigation Into Model-Based Fuzzy Logic Control, Michael W. Logan

Theses and Dissertations

This thesis investigates the feasibility of a proposed hybrid linear/Fuzzy controller for nonlinear plants. The proposed controller concept is based on the use of multiple linearizations of a nonlinear plant, which describe the dynamics of perturbations about equilibrium points throughout the desired envelope of operation. A bank of linear compensators is developed, each corresponding to a linearized plant about a different equilibrium. The multiple control signals generated by the bank of compensators are then weighted and summed using Fuzzy Logic to produce a composite control perturbation signal, which is used to drive the nonlinear plant. Experiments were conducted to test …

Design And Implementation Of Fuzzy Logic Controllers. Thesis Final Report, 27 July 1992 - 1 January 1993, Osama A. Abihana, Oscar R. Gonzalez

Electrical & Computer Engineering Faculty Publications

The main objectives of our research are to present a self-contained overview of fuzzy sets and fuzzy logic, develop a methodology for control system design using fuzzy logic controllers, and to design and implement a fuzzy logic controller for a real system. We first present the fundamental concepts of fuzzy sets and fuzzy logic. Fuzzy sets and basic fuzzy operations are defined. In addition, for control systems, it is important to understand the concepts of linguistic values, term sets, fuzzy rule base, inference methods, and defuzzification methods. Second, we introduce a four-step fuzzy logic control system design procedure. The design …

Design Of Multivariable Feedback Control Systems Via Spectral Assignment, Mohsen Marefat

Electrical & Computer Engineering Theses & Dissertations

During the past 15 year s significant advances have been made towards developing viable synthesis- techniques for multivariable feedback control systems. The entire aggregate of this theoretical work has been reviewed and consolidated. Diverse notations have been standardized into a single system. A two-step design philosophy for spectral assignment has been developed which first meets stability and time response requirements by assigning eigenvalues and eigenvector s and then provides for attainment of secondary objectives without significant deviation from the initial assignment. Finally, a computer-aided design package has been created to streamline the process of mathematical calculation and to allow users …