Two model-based fault-tolerant control design strategies are presented for a Diesel Engine Generator (DEG) working as a master generation unit in an islanded microgrid consisting of a hybrid wind-diesel-photovoltaic power system with a Battery Storage System (BSS). A Model Predictive Control (MPC) scheme and a Model Reference Adaptive Control (MRAC) scheme have been selected for precise and sta...

In this paper, we develop an adaptive multi controller system to solve the MRAC problem using unfalsified control theory. Switching is done among the candidate controllers based on some suitably defined performance index, which is obtained without actually inserting the candidate controllers in the feedback loop. Though prior knowledge about the nominal plant structure or its parameters is usef...

This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all ...

In this article, a unique and innovative design for addressing the speed synchronization problem in a multi-motor system using Brush less DC (BLDC), motors is presented by utilizing motor back emf equation and rotor position commonly called sensor less technique. In the proposed method, the system is modelled as a consensus problem of leader following multi-agent system (MAS), and a hybrid cont...

Two new output feedback adaptive control schemes based on Model Reference Adaptive Control (MRAC) and adaptive laws for updating the controller parameters are developed for a class of linear multi-input–multi-output (MIMO) systems with state delay. An effective controller structure established on a new error equation parametrization is proposed to achieve tracking with the error tending to zero...

Hebbian associative learning is a common form of neuronal adaptation in the brain and is important for many physiological functions such as motor learning, classical conditioning and operant conditioning. Here we show that a Hebbian associative learning synapse is an ideal neuronal substrate for the simultaneous implementation of high-gain adaptive control (HGAC) and model-reference adaptive co...

In this paper the model reference adaptive control (MRAC) problem of a class of linear time-varying (LTV) plants is considered. The plant parameters are assumed to be smooth, bounded functions of time which satisfy the usual assumptions of MRAC for timeinvariant plants, at each frozen time instant. It is first shown that if the plant parameters are sufficiently slowly varying with time, a contr...

Safety-critical aerospace systems require stringent stabilization or tracking performance that have to be guaranteed in the face of large system uncertainties and abrupt changes on system dynamics. Considering Model Reference Adaptive Control (MRAC) schemes, while aggressive adaptation rates can, theoretically, produce a fast convergence of the tracking error to zero, this is often achieved at ...

variation of frequency and voltage by load changes in a microgrid is a challenge in droop control method. centralized restoration frequency or voltage in a microgrid requires communication link and therefore affects the advantage of decentralized droop control such as reliability, simplicity and inexpensiveness. this paper proposes a decentralized method that restores the frequency of a microgr...

With the developments of industrial automation in recent years, vehicle suspension systems have received a great deal attention industry and academia due to their critical role chassis performance vehicles [1]. The system is expected guarantee vehicle's maneuverability provide satisfactory ride comfort by absorbing vibrations arising from road surface excitations ensuring road-holding ca...