Presence Of Measurement Disturbances Research Articles

Mobile Robot Control Based on 3D Visual Servoing: A New Approach Combining Pose Estimation by Neural Network and Differential Flatness

This paper deals with 3D visual servoing applied to mobile robots in the presence of measurement disturbances, caused in particular by target occlusion. We propose a new approach based on the flatness concept. In 3D visual servoing, the task is performed out of image coordinate space and targets may leave the camera field of view during navigation (servoing). Forced to navigate blindly during one or more periods of time, the robot will use our new open-loop control algorithm inspired by the flatness concept. The 3D visual servoing method is performed using robot pose estimation. This estimation generally contains some errors. The exact position of the robot is therefore not guaranteed, and robust feedback control is necessary to reject these errors in the input. To solve this problem, we propose a new pose estimation method that uses neural networks. We reduce the complexity of the architecture of the neural networks used (the number of variables to estimate) by proving that the location and the orientation of the robot can be ensured by using a single point in the image coordinate space for mobile robots with two degrees of freedom. To show the efficiency of the proposed algorithm, we use the RVCTOOLS MATLAB toolbox.

Parameter‐dependent observer‐based feedback compensator design of a space‐time‐varying PDE with application to a class of steelmaking processes

AbstractThis article deals with the problem of observer‐based feedback compensator design for a linear reaction–advection–diffusion equation subject to a time‐varying diffusion coefficient, a time‐varying advection coefficient, and a space‐time‐varying reaction coefficient. To solve such a problem, these coefficients are written in parametric forms under their boundedness assumptions. By considering these parametric forms of the coefficients and the distribution functions for control actuation and non‐collocated measurement, a parameter‐dependent observer‐based feedback compensator is constructed such that the resulting closed‐loop coupled equation exponentially converges to a bounded set of the equilibrium profile in the spatial norm. With the aid of the Lyapunov technique and variants of Poincaré–Wirtinger's inequality, a sufficient condition for the existence of such feedback compensator is presented in the form of convex constraints. Finally, extensive simulation results for a numerical example and a class of steelmaking processes are presented to support the proposed design method. For the collocated measurement case, both theoretical and simulation results show that the proposed observer‐based feedback compensator can provide a better control performance than the static feedback compensator in the presence of measurement disturbances.

Boundary control design for conservation laws in the presence of measurement disturbances

Boundary feedback control design for systems of linear hyperbolic conservation laws in the presence of boundary measurements affected by disturbances is studied. The design of the controller is performed to achieve input-to-state stability (ISS) with respect to measurement disturbances with a minimal gain. The closed-loop system is analyzed as an abstract dynamical system with inputs. Sufficient conditions in the form of dissipation functional inequalities are given to establish an ISS bound for the closed-loop system. The control design problem is turned into an optimization problem over matrix inequality constraints. Semidefinite programming techniques are adopted to devise systematic control design algorithms reducing the effect of measurement disturbances. The effectiveness of the approach is extensively shown in several numerical examples.

Design of Optimal Low-Order Feedforward Controllers

Design rules for optimal feedforward controllers with lead-lag structure in the presence of measurable disturbances are presented. The design rules are based on stable first-order models with time delays, FOTD, and are optimal in the sense of minimizing the integrated***squared error. The rules are derived for an open-loop setting, considering a step disturbance. This paper also discusses a general feedforward structure, which enables decoupling in the design of feedback and feedforward controllers, and justifies the open-loop setting.

On‐line optimization of batch processes in the presence of measurable disturbances

AbstractFeedforwar/state feedback laws are developed for on‐line optimization of batch reactors in the presence of measurable disturbances. The degrees of singularity with respect to manipulated input and disturbance input are used to characterize the nature of the feedforward/state feedback laws. Explicit synthesis formulas are derived that relate the optimal manipulated input to the system states and the measurable disturbance. It is shown that when the degree of singularity with respect to the manipulated input is infinite, the end‐point optimization problem reduces to a regulation problem in the presence of disturbances. For finite degrees of singularity, the optimal feedforward/state feedback law is, in general, dynamic. The proposed methodology is illustrated through several end‐point optimization problems in batch reactors.

A Comparison of the Power of Rasch Total and Between-Item Fit Statistics to Detect Measurement Disturbances

This study investigates the properties of the total and between fit statistics commonly used in Rasch model calibration and analysis programs to assess the fit of items to various Rasch models. There are two aspects of the study: an examination of the distributional properties of the item between fit statistics when the data fit the dichotomous model and a comparison of the power of the item between and total fit statistics to detect various types of simulated measurement disturbances in dichotomous data. The results indicate that the distributional properties of the between fit statistic are approximate unit normals and stable over a wide variety of testing conditions. In the presence of measurement disturbances, the between fit statistic appears to be more sensitive to systematic measurement disturbances and the total fit statistic is more sensitive to random measurement disturbances.

Nonlinear predictive control of periodically forced chemical reactors

AbstractA nonlinear model‐predictive control strategy is developed to maintain the superior‐to‐steady‐state performance of a periodically forced chemical reactor. The performance of the predictive controller is investigated in the presence of measurement disturbances and parametric uncertainty. It is also shown that statistically inferred input‐output models can be a substitute whenever detailed fundamental models are not available. A nonlinear autoregressive polynomial model based on observed plant data is built and incorporated into the control scheme. The catalytic oxidation of ethylene in a periodically‐forced, continuous stirred‐tank reactor is considered as the test case.

A Comparison of Two Methods of Decomposing Item Difficulties

This paper compares two methods of estimating component difficulties for dichotomous test data. Simulated data are used to study the effects of sample size, collinearity, a measurement disturbance, and multidimensionality on the estimation of component difficulties. The two methods of estimation used in this study were conditional maximum likelihood estimation of parameters specified by the linear logistic test model (LLTM) and estimated Rasch item difficulties regressed on component frequencies. The results of the analysis indicate that both methods produce similar results in all comparisons. Neither of the methods worked well in the presence of an incorrectly specified structure or collinearity in the component frequencies. However, both methods appear to be fairly robust in the presence of measurement disturbances as long as there is a large number of cases (n = 1,000). For the case of fitting data with uncorrelated component frequencies, 30 cases were sufficient to recover the generating parameters accurately.

Yield curve equation of continuous equilibrium sorption of adsorbates by adsorbent beds

Design rules for optimal feedforward controllers with lead-lag structure in the presence of measurable disturbances are presented. The design rules are based on stable first-order models with time delays, FOTD, and are optimal in the sense of minimizing the integrated***squared error. The rules are derived for an open-loop setting, considering a step disturbance. This paper also discusses a general feedforward structure, which enables decoupling in the design of feedback and feedforward controllers, and justifies the open-loop setting.