in this paper, the design and implementation of adaptive speed controller for a sensorless synchronous reluctance motor (synrm) drive system is proposed. a combination of well-known adaptive input-output feedback linearization (aiofl) and adaptive backstepping (abs) techniques are used for speed tracking control of synrm. the aiofl controller is capable of estimating motor two-axis inductances ...

Economists were interested in economic stabilization policies as early as the 1930’s but the formal applications of stability theory from the classical control theory to economic analysis appeared in the early 1950’s when a number of control engineers actively collaborated with economists on economic stability and feedback mechanisms. The theory of optimal control resulting from the contributio...

This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

When the process is highly uncertain, even linear minimum phase systems must sacrifice desirable feedback control benefits to avoid an excessive ‘cost of feedback’, while preserving the robust stability. In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. According to this strategy, the unce...

ph control is a challenging problem due to its highly nonlinear nature. in this paper the performances of two different adaptive global linearizing controllers (glc) are compared. least squares technique has been used for identifying the titration curve. the first controller is a standard glc based on material balances of each species. for implementation of this controller a nonlinear state est...

Adaptive automatic control systems become very frequently of use in technical practice. They are especially applied in automatic control systems of the flying bodies despite of higher expenses like the variable aerodynamic configuration of an aircraft and the application of a computer in autopilot circuits. Model reference adaptive control systems constitute an important group of adaptive syste...

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

abstract: in this work, an optimal control scheme with adaptive weighting coefficients is presented which coordinates different vehicle dynamics control objectives, thus ruling out possible conflicts among them. in a new approach, the weighting coefficients in optimal control are adjusted according to the vehicle state in the phase plane in such a way that a priority is given to each objective ...