In this work, we focus on a class of nonlinear systems and design an estimator-based economic model predictive control (MPC) system which is capable of optimizing closed-loop performance with respect to general economic considerations taken into account in the construction of the cost function.Workingwith the class of full-state feedback linearizable nonlinear systems, we use a high-gain observ...

State estimation techniques are used for improving the quality of measured signals and for reconstructing unmeasured quantities. In chemical reaction systems, nonlinear estimators are often used to improve the quality of estimated concentrations. These nonlinear estimators, which include the extended Kalman filter, the receding-horizon nonlinear Kalman filter and the moving-horizon estimator, u...

The least median of squares estimator (Rousseeuw, 1984)1 of linear regression parameters is a high breakdown estimator, meaning that, unlike the least squares estimator, it performs reasonably well when up to 50% outliers are present in a data set. Unfortunately, it lacks efficiency under normal errors. This disadvantage can be overcome by using the least median of squares estimator as a starti...

In impulsive orbital maneuvers, a large disturbance torque is generated by the thrust vector misalignment from the center of mass (C.M). The purpose of this paper is to reject the mentioned disturbance and stabilize the spacecraft attitude, based on the combination of a one degree of freedom (1DoF) gimbaled-thruster, two reaction wheels (RWs) and spin-stabilization. In this paper, the disturban...

This paper considers the use of neural networks for nonlinear state estimation, system identification and control. As a case study we use data taken from a nonlinear injection valve for a superheater attemporator at a power plant. One neural network is trained as a nonlinear simulation model of the process, then another network is trained to act as a combined state and parameter estimator for t...

The control problem for a series dc motor is considered. Based on a nonlinear mathematical model of a seriesconnected dc motor, it is shown that the combination of a nonlinear transformation and state feedback (feedback linearization) reduces the nonlinear control design to a linear control design. To demonstrate its effectiveness, an experimental study of this controller is presented. These ex...

A monocular visual-inertial system (VINS), consisting of a camera and a low-cost inertial measurement unit (IMU), forms the minimum sensor suite for metric six degreesof-freedom (DOF) state estimation. However, the lack of direct distance measurement poses significant challenges in terms of IMU processing, estimator initialization, extrinsic calibration, and nonlinear optimization. In this work...

Kalman Filter (KF) is widely used in process industries as state estimator to diagnose the faults either in the sensor, actuator or in the plant because of its recursive nature. But, due to increase in non-linearity and exogenous perturbations in the monitored plant, it is often difficult to use a simple KF as state estimator for nonlinear process monitoring purposes. Thus, the first objective ...

In this paper, the concepts of input/output-to-state stability (IOSS) and state-norm estimators are considered for switched nonlinear systems under average dwell-time switching signals. We show that when the average dwell-time is large enough, a switched system is IOSS if all of its constituent subsystems are IOSS. Moreover, under the same conditions, a non-switched state-norm estimator exists ...