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Jamshidi, M.

Publications and source records attributed to Jamshidi, M..

Determining flexor-tendon repair techniques via soft computing

An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.

Therapy, Computer-Assisted/methods

Fuzzy Control of Flexible-Link Manipulators: A Review

Several recent research efforts are reviewed here which have applied fuzzy logic in control of flexible-link manipulators. A flexible robot is a distributed parameter system represented by complex nonlinear dynamics, its actuator and the control parameters are non-colocated, and lastly, unstructured/unknown parameters play a significant role in model dynamics of a flexible robot operating in the real world. As a result, control of flexible robots is considered a promising area for application of intelligent control methodologies such as fuzzy logic, genetic algorithms, and neural networks.

Akbarzadeh-T, M.-R.

NASA University Research Centers Technical Advances in Education, Aeronautics, Space, Autonomy, Earth and Environment

This first volume of the Autonomous Control Engineering (ACE) Center Press Series on NASA University Research Center's (URC's) Advanced Technologies on Space Exploration and National Service constitute a report on the research papers and presentations delivered by NASA Installations and industry and Report of the NASA's fourteen URC's held at the First National Conference in Albuquerque, New Mexico from February 16-19, 1997.

Jamshidi, M.

Decentralized adaptive control

A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.

Oh, B. J.

Linear multivariable control of two-link robots

Several simple multivariable controllers such as proportional (P), proportional-derivative (PD), proportional-integral (PI), and proportional-integral-derivative (PID) are investigated and designed for stabilization and regulation of a two-link planar robot. A new multivariable controller is introduced in this article to achieve command matching. The multivariable controllers are designed on the basis of a linearized model of the robot dynamics. Numerous simulation results are presented to evaluate the performance of the multivariable controllers for the two-link planar robot.

Seraji, H.

An Overview of Latest Model Reduction and Control Methods of Large Flexible Space Structures

The latest trends and theoretical developments involved with the modeling and control of Large Flexible Space Structures (LFSS) are described. The paper addresses first the basic problems, characteristics, and difficulties inherent in modeling and control of LFSS. Major sources of difficulties and errors are the stiffness and damping operators of the dynamic model. Extensions of Linear Quadratic Gaussian (LQG) theory as applied to LFSS are presented, including frequency-shaped cost functionals and perturbation methods. The minimum data/maximum entropy approach which uses a stochastic design model to overcome difficulties found in the LQG-based methods is described. Latest trends in system theory including balanced realization and singular-value analysis are used to determine reduced order controllers and models. Ad hoc methods such as component cost analysis and modal cost analysis are discussed in context with the closed-loop reduction problem of controller order versus performance. The minimum data/maximum entropy approach also addresses controller order versus performance. Those areas of control science and large scale systems that appear to have an important role in understanding and solving LFSS modeling and control are also identified.

Santiago, J. M.

Control systems

Computationally feasible methods of large scale systems design applied to minimax algorithms and games strategies

Chen, C. I.