A set of objects of interest is to be sequentially inspected by a Micro Aerial Vehicle (MAV) equipped with a camera. Upon arriving at an object of interest, an image of the object is sent to a human operator, who, upo...
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ISBN:
(纸本)9783540743545
A set of objects of interest is to be sequentially inspected by a Micro Aerial Vehicle (MAV) equipped with a camera. Upon arriving at an object of interest, an image of the object is sent to a human operator, who, upon inspecting the image, sends his feedback to the MAV. The feedback from the operator may consist of the pose angle of the object and whether he has seen any distinguishing features of the object. Upon receiving the feedback, the MAV uses this information to decide whether it should perform a secondary inspection of the object of interest or continue to the next object. A secondary inspection has a reward (or value or information gain) that is dependent on the operator's feedback. There is an associated cost of reinspection and it depends on the delay of the operator's feedback. It seems reasonable to let the MAV loiter for a while near the most recently inspected object of interest so that it expends a small amount of endurance from the reserve after receiving the feedback from the operator. The objective is to increase the information and hence, the total expected reward about the set of objects of interest. Since the endurance of the MAVs is limited, the loiter time near each object of interest must be carefully determined. This paper addresses the determination of the optimal loiter time through the use of Stochastic dynamic programming. Numerical results are presented that show the optimal loiter time is a function of the maximum expected operator delay.
In this chapter, we present the scenario approach, an innovative technology for solving convex optimization problems with an infinite number of constraints. This technology relies on random sampling of constraints, an...
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ISBN:
(纸本)9783540707004
In this chapter, we present the scenario approach, an innovative technology for solving convex optimization problems with an infinite number of constraints. This technology relies on random sampling of constraints, and provides a powerful means for solving a variety of design problems in systems and control. Specifically, the virtues of this approach are here illustrated by focusing on optimal control design in presence of input saturation constraints.
In this paper we present a nonlinear predictive control strategy for the supervision of networked control systems subject to coordination constraints. Such a system paradigm, referred hereafter to as constrained dynam...
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ISBN:
(纸本)9783540726982
In this paper we present a nonlinear predictive control strategy for the supervision of networked control systems subject to coordination constraints. Such a system paradigm, referred hereafter to as constrained dynamic network, is characterized by a set of spatially distributed dynamic systems, connected via communication channels, with possible dynamical coupling and constraints amongst them which need to be controlled and coordinated in order to accomplish their overall objective. The significance of the method is that it is capable of ensuring no constraints violation and loss of stability regardless of any, possibly unbounded, time-delay occurrence. An application to the coordination of. two autonomous vehicles under input-saturation and formation accuracy constraints is presented.
We study the evolution of distributed multi-agent search systems where the autonomous agents may cooperate among each other, and/or with a human operator, in order to achieve the system's objective. The cooperatio...
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ISBN:
(纸本)9783540743545
We study the evolution of distributed multi-agent search systems where the autonomous agents may cooperate among each other, and/or with a human operator, in order to achieve the system's objective. The cooperation is facilitated by means of information sharing among the autonomous agents and/or human operator, which has the purpose of improving the effectiveness of the autonomous agents. The evolution of cooperative systems is modeled using discrete-state, continuous-time Markov chains, and a technique for measuring and quantification of cooperation within such systems is proposed.
In recent years, continuous chromatographic processes have been established as an efficient separation technology in industry, especially when temperature sensitive components or species with similar thermodynamic pro...
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ISBN:
(纸本)9783540726982
In recent years, continuous chromatographic processes have been established as an efficient separation technology in industry, especially when temperature sensitive components or species with similar thermodynamic properties are involved. In SMB processes, a counter-current movement of the liquid and the solid phases is achieved by periodically switching the inlet and the outlet ports in a closed loop of chromatographic columns. The integration of reaction and separation in one single plant is a promising approach to overcome chemical or thermodynamic equilibria and to increase process efficiency. Reactive chromatographic SMB processes in which the columns are packed with catalyst and adsorbent have been proposed and demonstrated successfully. However, a full integration often is not efficient because in the columns in the separating zones, the catalyst is not used or even counterproductive. By placing reactors between the separation columns at specific positions around the feed port, a more efficient process, the Hashimoto SMB process, is established. In this contribution, a non-linear predictive control concept for the Hashimoto SMB process is presented. The controller computes optimal control variables (flow rates and the switching time) to optimize an economic objective over a moving horizon. The purity requirements of the product streams are implemented as constraints and not as controlled variables. The optimization-based controller is combined with a scheme to estimate selected model parameters in order to reduce the influence of the inevitable model errors. Simulative results are presented for the example of the racemization of Troger's base.
We introduce stochastic differential algebraic equations for physical modelling of equilibrium based process systems and present a continuous-discrete paradigm for filtering and prediction in such systems. This paradi...
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ISBN:
(纸本)9783540726982
We introduce stochastic differential algebraic equations for physical modelling of equilibrium based process systems and present a continuous-discrete paradigm for filtering and prediction in such systems. This paradigm is ideally suited for state estimation in nonlinear predictive control as it allows systematic decomposition of the model into predictable and non-predictable dynamics. Rigorous filtering and prediction of the continuous-discrete stochastic differential algebraic system requires solution of Kolmogorov's forward equation. For non-trivial models, this is mathematically intractable. Instead, a suboptimal approximation for the filtering and prediction problem is presented. This approximation is a modified extended Kalman filter for continuous discrete systems. The modified extended Kalman filter for continuous-discrete differential algebraic systems is implemented numerically efficient by application of an ESDIRK algorithm for simultaneous integration of the mean-covariance pair in the extended Kalman filter [1, 2]. The proposed method requires approximately two orders of magnitude less floating point operations than implementations using standard software. Numerical robustness maintaining symmetry and positive semi-definiteness of the involved covariance matrices is assured by propagation of the matrix square root of these covariances rather than the covariance matrices themselves.
In many practical situations in process industry, the measurements of process quality variables, such as product concentrations, are available at different sampling rates and than other measured variables and also at ...
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Closed formation control for multiple unmanned ground vehicles (UGVs) is studied in this chapter. The leading-following strategy with a virtual leader is applied to coordinate the whole formation group so that only lo...
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ISBN:
(纸本)9783540743545
Closed formation control for multiple unmanned ground vehicles (UGVs) is studied in this chapter. The leading-following strategy with a virtual leader is applied to coordinate the whole formation group so that only local information is sufficient for every UGV to maintain close formation. Error-shaping memory-based control is designed for formation path tracking. The salient feature of this approach lies in its simplicity in design and implementation, and no need for detailed information on external disturbances and uncertainties. The performance of the proposed method is verified via real-time experiment on various formation operations.
This chapter outlines our research efforts toward developing a cooperative target localization method based on multiple autonomous unmanned aerial vehicles (UAVs) that axe outfitted with heterogeneous sensors. The cur...
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ISBN:
(纸本)9783540743545
This chapter outlines our research efforts toward developing a cooperative target localization method based on multiple autonomous unmanned aerial vehicles (UAVs) that axe outfitted with heterogeneous sensors. The current focus of the research includes (1) optimizing the UAV trajectories to place them at desired locations at desired times to capture target locations, (2) cooperative sensor scheduling, and (3) intelligent fusing of multiple sensor measurements to accurately estimate the position and velocity of a target. The focus of this paper is the sensor-fusion task. One might consider addressing this problem using some form of Kalman filter. However, a complicating factor in the present application is that sensor readings arrive out-of-sequence to the sensor-fusion process. For example, there is non-deterministic latency in the inter- and intra-UAV communication channels. We address this problem by developing an out-of-order sigma-point Kalman filter ((OSPKF)-S-3).
This paper investigates vision based robot control based on a receding horizon control strategy. The stability of the receding horizon control scheme is guaranteed by using the terminal cost derived from an energy fun...
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ISBN:
(纸本)9783540726982
This paper investigates vision based robot control based on a receding horizon control strategy. The stability of the receding horizon control scheme is guaranteed by using the terminal cost derived from an energy function of the visual feedback system. By applying the proposed control scheme to a two-link direct drive manipulator with a CCD camera, it is shown that the stabilizing receding horizon control nicely works for a planar visual feedback system. Furthermore, actual nonlinear experimental results are assessed with respect to the stability and the performance.
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