A state estimator for the continuous solid-state polymerization (SSP) reactor of polyethylene terephthalate (PET) is designed in this study. Because of its invalidity in the application to some of the practical examples such as SSP processes, the square-root unscented Kalman filter (SR-UKF) algorithm is improved for the state estimation of arbitrary nonlinear systems with linear measurements. Discussions are given on how to avoid the filter invalidation and accumulating additional error. Orthogonal collocation method has been used to spatially discretize the reactor model described by nonlinear partial differential equations. The reactant concentrations on chosen collocation points are reconstructed from the outlet measurements corrupted with a large noise. Furthermore, the error performance of the developed ISR-UKF is investigated under the influence of various initial parameters, inaccurate measurement noise parameters and model mismatch. Simulation results show that this technique can produce fast convergence and good approximations for the state estimation of SSP reactor. 

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In this paper a minimalist approach to establish obstacle avoidance and course stabilization behavior of an autonomous robot in a region evaluating 2D virtual world is proposed. The robot uses ultrasonic sensor to evade the hindrances and with distance measurements of barriers predict itself the shortest path to travel on through the destination and updating the virtual environment in database. The robot will be communicated with full duplex communication using ZigBee technology with computer interface. The environment around the rover will be visualized in GUI itself. Even robot can be made navigated searching for maximum light intensity in environment. The proposal is intense to aid the defense system and space exploration. It brings sophisticated method of practice by learning through virtual world of environment which can be enhanced even to 3D with technologies available.

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