In this paper a robust nonlinear model predictive controller based on state estimation for rigid n-link robot is designed. The control law is based on prediction model, which is carried out via Taylor series expansion. The optimal control is computed directly from the minimization of receding horizon cost function. There is no need to an online optimization. A disturbance observer is designed t...

In this paper, the problem of synthesis of a multiple observer for a class of uncertain nonlinear system represented by a Takagi-Sugeno multiple model is studied. The measure’s uncertainties are considered as unknown outputs. To conceive the observer a mathematical transformation is considered to conceive an augmented system in which the unknown output appear as an unknown input. Convergence co...

Normal industrial PD control of robot has two drawbacks, it needs joint velocity sensors; it cannot guarantee zero steady state error. In this paper we make two modifications to overcome these problems. High-gain observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate gravity and friction. We give a new proof for high-gain observer, which explains a ...

The purpose of this work is to design an exact fuzzy observer for a bioprocess switching between two different metabolic states. A continuous baker’s yeast culture is divided in two sub-models: a respiro-fermentative with ethanol production and a respirative with ethanol consumption. An exact fuzzy observer model using sector nonlinearity was built for both nonlinear models; the observer gains ...

This paper presents an effective technique for both synchronization and secure communication. In particular, an adaptive sliding mode observer is developed and practically implemented. Only one component of the state vector of the transmitter, that satisfies the observability matching condition, is sent to the receiver via a public channel, which is a sliding mode observer. This observer is abl...

Abstract: This paper investigates the problem of robust observer design for a class of nonlinear stochastic systems with state delays and time-varying normbounded parameter uncertainties. The nonlinearities are assumed to satisfy the global Lipschitz conditions and appear in both the state and measured output equations. The purpose is to design a nonlinear observer ensuring mean square asymptot...

We report an experiment designed to provide a qualitative contrast between knowledge-limited versions of mixed-state and variable-resources (VR) models of visual change detection. The key data pattern is that observers often respond “same” on big-change trials, while simultaneously being able to discriminate between same and small-change trials. The mixed-state model provides a natural account ...

In this paper, new observer design approaches are presented for TakagiSugeno (T-S) fuzzy models with measurement output noises. In order to decouple the measurement noise, an augmented fuzzy descriptor model is first constructed. Then a fuzzy descriptor proportional and derivative (PD) observer is developed. When the fuzzy subsystems have the same output matrices, another fuzzy descriptor obser...

We study the problem of estimating the state of a linear time-invariant plant in a distributed fashion over networks allowing only intermittent transmission of information. By attaching to each node an observer that employs information received from its neighbors in an intermittent fashion, we propose a distributed state observer that guarantees global asymptotic stability of the zero estimatio...

This paper proposes a state estimation methodology for invariant systems on Lie groups where outputs of the system are measured with delay. The proposed method is based on a cascade of an observer and a predictor. The observer uses delayed measurements and provides estimates of delayed states. The predictor uses those estimates together with the current inputs of the system to compensate for th...