In the field of control, various control methodologies and strategies have been devised, tested and implemented in process control and other such control applications. Favourite examples of controllers are proportional, Integral and derivative in parallel and/ or series combinations so far. Controller tuning is also an important aspect of process control. Speaking on control techniques, there a...

Output-feedback control for trajectory tracking is an important research topic of various engineering systems. In this paper, a novel online hybrid direct/indirect adaptive Petri fuzzy neural network (PFNN) controller with stare observer for uncertain nonlinear multivariable dynamical systems using generalized projection-update laws is presented. This new approach consists of control objectives...

In this paper the position control of a linear induction motor using adaptive fuzzy backstepping design with integral action is proposed. First, the indirect field oriented control for LIM is derived. Then, an integral backstepping design for indirect field oriented control of LIM is proposed to compensate the uncertainties which occur in the control. Finally, the fuzzy integral-backstepping co...

an adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. another key feature of this structure is the fact that, it does not need model of the system. in this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  online training of neurolinearizer is compared to model predictive recurrent training...

In this paper, the modularized adaptive backstepping designs are incorporated into the recently proposed adaptive robust control framework to synthesize indirect adaptive robust controllers that achieve not only good output tracking performance but also better parameter estimation processes to obtain accurate parameter estimates for secondary purposes such as machine health monitoring and progn...

It is difficult to realize adaptive control for some complex nonlinear processes which are operated in different environments and when operation conditions are changed frequently. In this paper we propose an identifier-based adaptive control (or indirect adaptive control). The identifier uses two effective tools: multiple models and neural networks. A hysteresis switching algorithm is applied t...

In this paper, stable indirect adaptive control with recurrent neural networks is presented for multi-input multi-output (MIMO) square non linear plants with unknown dynamics. The control scheme is made of a neural model and a neural controller based on fully connected RTRL networks. On-line weights updating law, closed loop performance, and boundedness of the neural network weights are derived...

Adaptive control for nonlinear time-varying systems is of both theoretical and practical importance. In this paper, we propose an adaptive control methodology for a class of nonlinear systems with a time-varying structure. This class of systems is composed of interpolations of nonlinear subsystems which are input–output feedback linearizable. Both indirect and direct adaptive control methods ar...

We formally verify a direct model-reference adaptive control (MRAC) method that is used to enable flight control in adverse conditions. We use the bounded verification approach and verify the system by introducing templates for both the assumptions and the guarantees, and using the tool QEPCAD to solve the resulting exists-forall formula. We also present results from an analysis performed on in...