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This paper develops a new model reference adaptive control approach for uncertain systems with gain scheduled reference models in a multi-input multi-output (MIMO) setting. Specifically, adaptive state feedback for output tracking control problem of MIMO nonlinear systems is studied and gain scheduled reference model system is used for generating desired state trajectories. Using convex optimization...
Particle filters are well-known as powerful tools for accomplishing state and parameter estimation and their propagation prediction in nonlinear dynamical systems. Their ability to include system model parameters as part of the system state vector is among one of the key factors for their use in prognostics. Estimation of system parameters along with the states produces an updated model that can be...
The paper proposes a suboptimal adaptive control for a nonlinear stochastic system subject to functional uncertainty. The problem of a real-time identification of the unknown nonlinear system is tackled by using the Gaussian process based non-parametric model. The covariance function of the Gaussian process is chosen in such a way that allows deriving the control law in a closed form. The control...
This paper proposes a solution to the aircraft control problem during landing phases in presence of microburst wind shear. This work addresses the design of an adaptive controller which, exploiting the wind estimation provided by suitable filters, improves the flight safety and is able to accomplish the final approach phase even in presence of wind shear. The adaptive controller has been designed...
On-line learning allows to adapt to changing nonstationary environments. But typically with on-line learning a hypothesis of the data relation is adapted based on a stream of single local training examples, continuously changing the global input-output relation. Hence with these single examples the whole hypothesis is revised incrementally, which might be harmful to the overall predictive quality...
In this paper an attempt of designing the direct self- learning/evolving fuzzy controller is presented. The controller is comprised of several local-controllers each valid in a certain part of input-output space. The input-output space is partitioned by on-line clustering and evolving mechanisms taken from eFuMo method. The controller gains are adapted using the fuzzy model reference adaptive control...
This paper suggests a Particle Swarm Optimization (PSO) approach to the optimal tuning of fuzzy models for Anti-lock Braking Systems (ABSs). A set of ten local state-space models of the ABS is first obtained by the linearization of the nonlinear state-space model of the ABS process at ten operating points. The initial Takagi-Sugeno (T-S) fuzzy models are next obtained by the modal equivalence principle,...
In this paper, a real-time state feedback Model Reference Adaptive Control strategy is developed for stabilization of a 3DOF Hover electromechanical system, and its disturbance rejection properties are analyzed.
Performance of constrained movements in multiple directions of a workspace simultaneously and in presence of uncertainty is a great challenge for robots. Achieving such tasks by employing control policies which are fully determined a priori and do not take into account the system uncertainty can cause undesired stress on the robot end-effector or the environment and result in poor performance. Instead,...
Although evolving models have found different applications in real world systems, they have not been developed significantly for nonlinear control systems. In this paper, Evolving Linear Models (ELMs) are proposed for self tuning regulation of a main class of nonlinear time varying control systems. First, the structure of ELMs is introduced and then it is shown that nonlinear time varying control...
We present in this paper a preliminary result on learning-based adaptive trajectory tracking control for nonlinear systems. We propose, for the class of nonlinear systems with parametric uncertainties which can be rendered integral Input-to-State stable w.r.t. the parameter estimation errors input, that it is possible to merge together the integral Input-to-State stabilizing feedback controller and...
As for parameters fluctuating, uncertainties caused by external disturbance and friction, the nonlinearity of the flight simulator turntable servo system, a discrete model reference sliding mode control theme combining with adaptive method and decoupled disturbance compensator is presented, and the globally asymptotically stability of the system is proved. The simulation results verified that the...
In this paper a finite impulse response (FIR) filter for online adaptive modeling of satellite attitude control systems is proposed, and a recursive least squares (RLS) algorithm is used to adjust the adaptive FIR filter coefficients for minimizing the output error between the monitored system and the FIR filter. The fault information can be obtained through the analysis of the adaptive FIR filter...
The paper investigates the second-order leader-following consensus problem of nonlinear multi-agent systems via adaptive pinning control. Based on graph theory and the neighbor-based coupling rule, the adaptive pinning control strategy is proposed, the consensus condition is derived in terms of linear matrix inequalities. It is worth noting that this paper addresses that what kind of agents and how...
The paper deals with the vector control of an induction motor with a rotor time constant adaptation. The adaptation of the rotor time constant is required for a correct activity of a current model of the induction motor. It is necessary to estimate this parameter in order to maintain it equal to its rated value programmed in the decoupling controller. The estimation of the rotor time constant is performed...
This work introduces a simple method and implementation algorithm for quick-change detection based on process measurements, adaptive modelling and identification, which will be called model-based quick-change detection (M-QCD). The idea of the method is to select a proper model for process identification purposes, and to continuously estimate the parameters of this model. A change in process implies...
Most modern hypervisors offer powerful resource control primitives such as reservations, limits, and shares for individual virtual machines (VMs). These primitives provide a means to dynamic vertical scaling of VMs in order for the virtual applications to meet their respective service level objectives (SLOs). VMware DRS offers an additional resource abstraction of a resource pool (RP) as a logical...
In the current article is presented the new control of static compensator (STATCOM) for compensation of voltage asymmetry in power system, which is not based on measurement of the current of asymmetrical load. In this way it is not necessary to know the sources of asymmetry and their currents. In suggested control as input signals are used the deviations of each phase voltage from nominal value. So...
In this article an adaptive controller is developed in order to estimate the inertia tensor, the mass and the wind parameters (considering wind as a parameter in the input) for the underactuated quad-rotor mini-aircraft. Experimental tests are performed in an educational platform. The proposed control scheme uses the parameter estimation issued from gradient type algorithm. Finally simulations and...
Multi-MW wind power converter's reliability is a key issue for the whole wind power generation system. Due to wind power fluctuation, IGBT's handling power is fluctuating largely and rapidly, which will cause a large junction temperature variation of IGBT. Thermal stress is the main factor affecting IGBT's lifetime. In this paper, the adaptive thermal control is proposed to improve IGBT's lifetime...
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