This paper presents an indirect adaptive fuzzy control scheme for nonlinear uncertain stable plants with unmeasurable states. A discrete-time T-S fuzzy model is employed as a dynamic model of an unknown plant. Based on this model, a feedback linearization controller is designed and applied to both the model and the plant. Parameters of the model are updated on-line to allow for partially unknow...

In the context of aircraft, shimmy is an oscillatory phenomenon of the landing gear mainly due the tire dynamics and the landing gear structural dynamics. This phenomenon, which can result in severe structural damages of the landing gear, is here actively damped by an indirect fuzzy adaptive controller. The difficulties to model the ground/wheel interface require the use of an adaptive controll...

It is well known that in indirect adaptive control algorithms, the system to be controlled is not necessarily identified due to lack of excitation caused by the fact that identification takes place in closed-loop. Whether or not this leads to undesirable behaviour depends on the underlying control criterion. A classification is made of all control criteria for which the closed-loop identificati...

The design of most adaptive control schemes is based on the certainty equivalence approach. According to this approach, a control law that can meet the control objective is first developed assuming the plant parameters are exactly known. Then, an adaptive law for estimating the unknown parameters of a certain plant parameterization in chosen to generate on-line estimates which are then u...

In this letter, stable direct and indirect adaptive controllers are presented that use Takagi–Sugeno (T–S) fuzzy systems, conventional fuzzy systems, or a class of neural networks to provide asymptotic tracking of a reference signal vector for a class of continuous time multi-input multi-output (MIMO) square nonlinear plants with poorly understood dynamics. The direct adaptive scheme allows for...

The overall goal is to reduce spacecraft weight. volume, and cost by online adaptive non-linear control of flexible structural components. The objective of this effort is to develop an adaptive Neural Network (NN) controller for the Ball C-Side 1m x 3m antenna with embedded actuators and the RAMS sensor system. A traditional optimal controller for the major modes is provided perturbations by th...

This paper presents an indirect adaptive control scheme for nominally stabilizable, but possible non-controllable, continuous and timevarying systems with unmodelled dynamics. The control objective is the adaptive stabilization of the system. The scheme includes several estimation algorithms and a supervisor which selects the appropriate estimator keeping it in operation during at least a minim...

This paper presents an indirect adaptive fuzzy control scheme for a class of single-input-single-output (SISO) nonlinear systems. A Takagi-Sugeno (T-S) fuzzy model is employed as a dynamical model of the partially known nonlinear system. Both the structure and the parameters of the T-S model are identified on-line. A T-S model based feedback linearization controller (FLC) is designed and a Lyap...

CINVESTAV-IPN, Ave. IPN No 2508, A.P. 14-470 Mexico D.F., MEXICO Fax: (+52-5)747-70-89; E-mail: [email protected]

This paper presents a new model reference adaptive control method to control motor torque in direct drive reluctance motors in an accurate and ripple-free fashion. It is based on the motor's voltage equation and requires only measurements of motor angle, winding voltages and currents. In addition, we introduce a new optimal torque-to-current conversion which minimizes copper losses. Simulations...