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Peaking free variable structure control of uncertain linear systems based on a high-gain observer

AUTOMATICA 2009年第5期45卷 1156-1164页

作者： Cunha, Jose Paulo V. S. Costa, Ramon R. Lizarralde, Fernando Hsu, Liu Univ Estado Rio De Janeiro Dept Elect & Telecommun Engn BR-20550900 Rio De Janeiro Brazil Univ Fed Rio de Janeiro COPPE BR-21945970 Rio De Janeiro Brazil

An output-feedback model-reference variable structure controller based on a high-gain observer (HGO) is proposed and analyzed. For single-input-single-output (SISO) linear plants with relative degree greater than one, the control law is generated using the HGO signals only to drive the sign function of the variable structure control component while the sign function gain, also called modulation, as well as the other components of the control signal are generated using signals from state variable filters which do not require high gain and are free of peaking. This scheme achieves global exponential stability with respect to a small residual set and does not generate peaking in the control signal. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Variable-structure control Sliding mode High-gain observer model reference control Peaking phenomena Output feedback

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Force control in a pneumatic system using hybrid adaptive neuro-fuzzy model reference control

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MECHATRONICS 2005年第1期15卷 23-41页

作者： Kaitwanidvilai, S Parnichkun, M Asian Inst Technol Sch Adv Technol Pathumthanee 12120 Thailand

The dynamic model of a force control system depends not only on the actuator but also on the manipulated object. Generally the object dynamics are unknown and frequently change, and it therefore is difficult to identify the actual dynamics of the system. Designing a nonadaptive controller to perform well under unknown and variant conditions is not feasible. To enhance the controller performance for the pneumatic system, in this paper, a hybrid adaptive neuro-fuzzy model reference is proposed. The concept of multimode switching is applied to activate either a 'bang-bang' controller or an adaptive neuro-fuzzy model reference controller (ANFMRC). Bang-bang control is applied when the actual output is far away from set point, which results in high error value. In this mode, fast tracking of the output is required. ANFMRC is applied in medium and small error ranges to perform a good response. In this paper, two types of controller;ANFMRC and hybrid ANFMRC are investigated. Simulation and experiment of a force controlled pneumatic system is investigated to evaluate the efficiency of the algorithm. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： force controlled pneumatic system adaptive neuro-fuzzy control model reference control multimode control

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Iterative learning controller synthesis using FIR models for batch processes

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KOREAN JOURNAL OF CHEMICAL ENGINEERING 2009年第6期26卷 1512-1518页

作者： Chen, Junghui Chou, Kuo-Tong Chung Yuan Christian Univ Dept Chem Engn R&D Ctr Membrane Technol Chungli 320 Taiwan

Adaptive iterative learning control based on the measured input-output data is proposed to solve the traditional iterative learning control problem in the batch process. It produces a control law with self-tuning capability by combining a batch-to-batch model estimation procedure with the control design technique. To build the unknown batch operation system, the finite impulse response (FIR) model with the lifted system is constructed for easy construction of a recursive least squares algorithm. It can identify the pattern of the current operation batch. The proposed model reference control method is applied to feedback control of the lifted system. It finds an appropriate control input so that the desired performance of the batch output can track the prescribed finite-time trajectory by iterative trials. Furthermore, on-line tracking control is developed to explore the possible adjustments of the future input trajectories within a batch. This can remove the disturbances in the current batch rather than the next batch trial and keep the product specifications consistent at the end of each batch. To validate the theoretical findings of the proposed strategies, two simulation problems are investigated.

关键词： Batch Process Iterative Learning control model reference control

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model reference Sliding Mode control of Small Helicopter XRB based on Vision

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2008年第3期5卷 235-242页

作者： Wang, Wei Nonami, Kenzo Ohira, Yuta Chiba Univ Grad Sch Sci & Technol Fac Engn Chiba Japan

This paper presents autonomous control for indoor small helicopter X.R.B. In case of natural disaster like earthquake, a MAV (Micro Air Vehicle) which can fly autonomously will be very effective for surveying the site and environment in dangerous area or narrow space, where human cannot access safely. In addition, it will be helpful to prevent secondary disaster. This paper describes vision based autonomous hovering control, guidance con trol for X.R.B by model reference sliding mode con trol.

关键词： MAV Image processing Hovering contorl Guidance control model reference control Sliding mode control

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An Orthogonal ARX Network for Identification and control of Nonlinear Systems

An Orthogonal ARX Network for Identification and Control of ...

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22nd International Symposium on Information Communication and Automation Technologies

作者： Beyhan, Selami Alci, Musa Ege Univ Dept Elect & Elect Engn Izmir Turkey

ISBN: (纸本)9781424442201

This paper presents a new orthogonal neural network (ONN) which is utilized successively for online identification and control of nonlinear discrete-time systems. The proposed network is designed with auto regressive with exogenous (ARX) terms of inputs and outputs, and their orthogonal terms by Chebyshev polynomials. The network is a single layer neural network and computationally efficient with less number of parameters. The identification by the network is performed in stable sense by using Lyapunov stability guaranteed learning rate. Hence, the learning rate depends on the current knowledge of the system instead of using constant learning rate. This learning rate provides fine online optimization. In simulation study, one benchmark nonlinear system is identified and results are compared. Then, one nonlinear functioned system is identified and controlled by model reference control. From results, it is seen that the proposed model has good learning capability for identification and control.

关键词： ONN ARX model Stable Learning and control model reference control

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INVENTORY MANAGEMENT IN HIGH UNCERTAINTY ENVIRONMENT WITH model reference control

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IFAC Proceedings Volumes 2005年第1期38卷 265-270页

作者： Heikki Rasku Hannu Koivisto Institute of Automation and Control Tampere University of Technology P.O.Box 692 Tampere Finland

In this study, the method of model reference control is used to implement a decision support system for inventory management. The inventory is controlled on the basis of minimizing variable costs while satisfying a certain percent of customer demand. Value-at-Risk analysis is used to determine the required safety stock for the controller, so that the uncertainties are buffered into the inventory. The handling of constraints is also investigated in simulations with four different inventory capacity limitations. Results from the simulations show how a model reference control based decision support system, combined with Value-at-Risk based safety stock determination, can operate within strict constraints while still satisfying a certain percentage of customer demand.

关键词： Inventory management model predictive control model reference control uncertainty

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Is normalization necessary for stable model reference adaptive control?

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IEEE TRANSACTIONS ON AUTOMATIC control 2005年第9期50卷 1384-1390页

作者： Barabanov, N Ortega, R Astolfi, A N Dakota State Univ Dept Math Fargo ND 58102 USA CNRS SUP ELEC Lab Signaux & Syst F-91192 Gif Sur Yvette France Univ London Imperial Coll Sci & Technol Dept Elect Engn London SW7 2BT England

One of the longest standing open questions in adaptive control concerns the correctness of the stability claim of the un-normalized model reference scheme proposed by Monopoli in 1974. Although provably correct solutions to the problem now abound, in particular, it is well known that adding a normalization to Monopoli's original scheme ensures global convergence, it is interesting to know whether this technique-driven modification is really necessary or only required to complete the stability proof in the absence of more elaborate arguments. In this note, we construct a counterexample that provides a definite-unfortunately, negative-answer to the claim. Instrumental for the establishment of this result is a technical lemma that shows that, under some conditions on the regressor that may appear in Monopoli's scheme, the parameter error freezes as the adaptation gain goes to infinity. On the lighter side, we also prove that Monopoli's scheme is semiglobally stable, underscoring the relevance of this important contribution.

关键词： adaptive control model reference control nonlinear control stability of adaptive systems

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Robust model reference vibration control of a flexible beam using piezoceramic patches

Robust model reference vibration control of a flexible beam ...

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Joint Conference of the 20th IEEE International Symposium on Intelligent Contol/13th Mediterranean Conference on control and Automation

作者： Gu, HC Song, GB Univ Houston Dept Engn Mech Houston TX 77204 USA

ISBN: (纸本)0780389360

This paper presents a novel approach to active vibration control of flexible beams using piezoceramic smart materials. This approach employs a robust model reference controller which has the abitity to handle model uncertainties. Asymptotic stability of the closed loop system is guarantee as proved by the Lyapunov's direct method. To demonstrate the effectiveness and robustness of the proposed method, experiments, including varying the mass of the flexible beams, are conducted. Experiments show that the robust model reference control achieves rapid vibration suppression even in the presence of uncertain model parameters.

关键词： model reference control piezoceramic materials smart materials vibration control

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Network-based H_∞ output tracking control

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IEEE TRANSACTIONS ON AUTOMATIC control 2008年第3期53卷 655-667页

作者： Gao, Huijun Chen, Tongwen Harbin Inst Technol Space Control & Inertial Technol Res Ctr Harbin 150001 Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2V4 Canada

This paper is concerned with the problem of H-infinity output tracking for network-based control systems. The physical plant and the controller are, respectively, in continuous time And discrete time. By using a sampled-data approach, a new model based on the updating instants of the holder is formulated, and a linear matrix inequality (LMI)-based procedure is proposed for designing state-feedback controllers, which guarantee that the output of the closed-loop networked control system tracks the output of a given reference model well in the H-infinity sense. Both network-induced delays and data packet dropouts have been taken into consideration in the controller design. The network-induced delays are assumed to have both an upper bound and a lower bound, which is more general than those used in the literature. The introduction of the lower bound is shown to be advantageous for reducing conservatism. Moreover, the controller design method is further extended to more general cases, where the system matrices of the physical plant contain parameter uncertainties, represented in either polytopic or norm-bounded frameworks. Finally, an illustrative example is presented to show the usefulness and effectiveness of the proposed H-infinity output tracking design.

关键词： model reference control networked control systems output tracking sampled-data systems

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A stability control by active angle control of front-wheel in a vehicle system

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2008年第3期55卷 1277-1285页

作者： Ohara, Hiroki Murakami, Toshiyuki Keio Univ Dept Syst Design Engn Yokohama Kanagawa 2238522 Japan

Side-slip angle information is required for stabilizing a vehicle. Conventional stability control methods assume that side-slip angle information can be obtained directly from a sensor. However, this is difficult to do in a normal car because an expensive sensor is needed to realize these methods. In this paper, a strategy for stability control based on the estimated side-slip is proposed. First, a novel linear observer that can make the estimated error small compared with the conventional linear observer is designed. Second, the yaw rate following the controller is constructed. To implement this control system in an actual vehicle system, a steering angle controller is designed. Finally, to confirm the effectiveness of the proposed control system, numerical simulation is implemented with the consideration of a gust of wind and vehicle modeling error. Also, running a vehicle experiment on the road is shown.

关键词： active angle control of front-wheel model reference control observer side slip angle stability control of vehicle yaw rate control

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