This work designed an anticipatory ILC schemes for a class of batch processes, where only the final system output is measurable and the control input is constant in each operations. This approach has the anticipatory ...
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This work designed an anticipatory ILC schemes for a class of batch processes, where only the final system output is measurable and the control input is constant in each operations. This approach has the anticipatory characteristics and the simplicity for implementation. The control input saturation is taken into account and tracking error convergence results are established with rigorous proofs. Simulation results are provided to show the effectiveness of this scheme.
A strictly positive real control problem for delta operator systems in a low frequency range is presented by using the generalized Kalman–Yakubovic˘–Popov lemma. The objective of the strictly positive real control p...
A strictly positive real control problem for delta operator systems in a low frequency range is presented by using the generalized Kalman–Yakubovic˘–Popov lemma. The objective of the strictly positive real control problem is to design a controller such that the transfer function is strictly positive real and the resulting closed-loop system is stable. Sufficient conditions for the low frequency strictly positive real controller of the closed-loop delta operator systems are presented in terms of solutions to a set of linear matrix inequalities. A numerical example is given to illustrate the effectiveness and potential for the developed techniques.
A gradient-based algorithm for the on-line continuous estimation of the commensurate order in linear fractional order processes is presented.A key aspect of the proposed methodology is the use of appropriate variable-...
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A gradient-based algorithm for the on-line continuous estimation of the commensurate order in linear fractional order processes is presented.A key aspect of the proposed methodology is the use of appropriate variable-order fractional filters
From the view of combination of stereo vision and robot control, an active stereo vision for object tracking and location system is built to work on flexible manufacturing system. A method based on local HSV image and...
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From the view of combination of stereo vision and robot control, an active stereo vision for object tracking and location system is built to work on flexible manufacturing system. A method based on local HSV image and shape of object to recognize object is used for robot tracking. After the color segment, use the knowledge of shape of objects to recognize objects. And a technique for camera calibration based on plane square is proposed. It only requires the camera to observe a square at two (or more) different unknown orientations. Use the result of object recognize and camera calibration the robot can position and track the object. At the last of the paper, the results of object tracking experiments prove that the method is correct.
This paper presents the analysis, modeling, identification and predictive control of an anaerobic digestion process. The widely adopted anaerobic digestion model ADM1 is used to describe the anaerobic digestion of pri...
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This paper presents the analysis, modeling, identification and predictive control of an anaerobic digestion process. The widely adopted anaerobic digestion model ADM1 is used to describe the anaerobic digestion of primary and secondary wastewater sludge. Their feed flow rates constitute two model inputs, which are considered as manipulated variables, while the biogas production rate and its methane content constitute two model outputs (controlled variables). The general control objective is to manipulate the inputs within the operation limits such that a maximum methane production is ensured at all times. A comparison between open-loop and closed-loop control reveals the net advantage of predictive control for optimal rate regulation.
For a freeway traffic system with strict repeatable pattern, iterative learning control (ILC) has been successfully applied to local ramp metering for a macroscopic freeway environment by formulating the original ramp...
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For a freeway traffic system with strict repeatable pattern, iterative learning control (ILC) has been successfully applied to local ramp metering for a macroscopic freeway environment by formulating the original ramp metering problem as an output tracking, disturbance rejection, and error compensation problem. In this paper, we address the freeway traffic ramp-metering system under a nonstrict repeatable pattern. ILC-based ramp metering and ILC add-on to ALINEA strategies are modified to deal with the presence of iteration-dependent parameters, iteration-dependent desired trajectory, and input constraints. Theoretical analysis and extensive simulations are used to verify the effectiveness of the proposed approaches.
This paper aims to integrate the fuzzy control with adaptive dynamic programming (ADP) scheme, to provide an optimized fuzzy control performance, together with faster convergence of ADP for the help of the fuzzy prior...
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ISBN:
(纸本)9781467314886
This paper aims to integrate the fuzzy control with adaptive dynamic programming (ADP) scheme, to provide an optimized fuzzy control performance, together with faster convergence of ADP for the help of the fuzzy prior knowledge. ADP usually consists of two neural networks, one is the Actor as the controller, the other is the Critic as the performance evaluator. A fuzzy controller applied in many fields can be used instead as the Actor to speed up the learning convergence, because of its simplicity and prior information on fuzzy membership and rules. The parameters of the fuzzy rules are learned by ADP scheme to approach optimal control performance. The feature of fuzzy controller makes the system steady and robust to system states and uncertainties. Simulations on under-actuated systems, a cart-pole plant and a pendubot plant, are implemented. It is verified that the proposed scheme is capable of balancing under-actuated systems and has a wider control zone.
This paper considers the distributed quadratic stabilization problems of uncertain continuous-time linear multiagent systems with undirected communication topologies. It is assumed that the agents have identical nomin...
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This paper considers the distributed quadratic stabilization problems of uncertain continuous-time linear multiagent systems with undirected communication topologies. It is assumed that the agents have identical nominal dynamics while subject to different norm-bounded parameter uncertainties, leading to weakly heterogeneous multi-agent systems. A distributed controller is proposed, based on the relative states of neighboring agents and a subset of absolute states of the agents. It is shown that the distributed quadratic stabilization problem under such a controller is equivalent to the H∞ control problems of a set of decoupled linear systems having the same dimensions as a single agent. A two-step algorithm is presented to construct the distributed robust controller, which does not involve any conservatism and meanwhile decouples the feedback gain design from the communication topology. Furthermore, the distributed quadratic H∞ control problem of uncertain linear multi-agent systems with external disturbances is discussed, which can be reduced to the scaled H∞ control problems of a set of independent systems whose dimensions are equal to that of a single agent.
Design and integration of industrial automationsystems require cooperation of different engineering disciplines and various engineering tools during both design and run time. The scope of this paper is to bridge the ...
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Design and integration of industrial automationsystems require cooperation of different engineering disciplines and various engineering tools during both design and run time. The scope of this paper is to bridge the gap between design-time description and runtime integration in a semi-automated way. Furthermore, we address the problem of integrating legacy systems with no access to original engineering data. It is assumed that an interface between a real industrial system and software automation tools is OPC Unified Architecture (UA) and we propose to derive the plant knowledge from the OPC UA tag list. Since it is not possible to solve this task in general, we require the tag list to adopt the naming convention of IEC 81346, which is widespread in large-scale systems. This tag list is parsed and the engineering knowledge is derived and stored in the engineering Knowledge Base. Consequently, the plant knowledge is mapped to knowledge related to software automation tools, such as simulators. The proposed methodology is evaluated on a real-life example dealing with a laboratory tank model.
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