This paper presents an iterative learning identification scheme for a class of parabolic distributed parameter systems with unknown curved surfaces. The identification design method is proposed on the basis of the ite...
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This paper presents an iterative learning identification scheme for a class of parabolic distributed parameter systems with unknown curved surfaces. The identification design method is proposed on the basis of the iterative learning concept. Initially, a new nonlinear learning identification law based on vector-plot analysis is developed to estimate the curved surface with spatial-temporal varying iteratively. Subsequently, through theoretical analysis, the sufficient convergence conditions for identification error in the sense of norm is manifested. Furthermore, a high-order P-type learning law is applied to identifying the curved surface in order to compare the convergent rate with the aforesaid identification law. Finally, simulation results on a specific numerical example and the temperature profile of a catalytic rod confirm that the proposed learning identification laws is effective.
This paper investigates robust quantized output feedback control of nonlinear Markovian jump distributed parameter systems (MJDPSs) with incomplete transition rates. Considering the digital communication channel in pr...
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This paper investigates robust quantized output feedback control of nonlinear Markovian jump distributed parameter systems (MJDPSs) with incomplete transition rates. Considering the digital communication channel in practical applications, the data of measured output and control input is quantized before transmission, by mode-dependent quantizer. Furthermore, a randomly occurring communication fault phenomenon is noticed in stability analysis, and is described by Bernoulli distributed white sequences. Based on Takagi-Sugeno (T-S) fuzzy model and dynamic parallel distributed compensate principle, a novel output feedback controller is developed. The conditions, to ensure that the MJDPSs are stochastically stable with mixed L-2-L-infinity/H-infinity performance, are given in terms of linear matrix inequalities (LMIs), and controller gains can be obtained by LMI toolbox. Finally, an example is provided to illustrate the effectiveness of the proposed method. (C) 2019 Elsevier Inc. All rights reserved.
The previously developed technology of multi-objective optimization of deterministic systems with distributed parabolic parameters can be applied in typical situations with interval uncertainties of parametric charact...
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The previously developed technology of multi-objective optimization of deterministic systems with distributed parabolic parameters can be applied in typical situations with interval uncertainties of parametric characteristics of controlled plants. Minimax problems of mathematical programming are formed in accordance with a control strategy based on the principle of the best guaranteed result of a expanded set of arguments, which includes all permissible realizations of uncertain factors, in the case of estimating a given accuracy of approximation to a required finite system state in uniform metric. These problems are solved by an alternance method that uses the Chebyshev properties of desired extermals and fundamental laws of the problem domain. This paper also presents an example of multi-objective optimization of temperature modes of induction heating of metallic semifinished products before plastic deformation operations in technological complexes for pressure treatment of metal, which is of independent interest.
This paper considers the iterative learning control (ILC) problem for a class of uncertain linear distributed parameter systems with time delay. A P-type ILC scheme is presented for distributed parameter systems. Then...
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ISBN:
(纸本)9781728105215
This paper considers the iterative learning control (ILC) problem for a class of uncertain linear distributed parameter systems with time delay. A P-type ILC scheme is presented for distributed parameter systems. Then, using a Lyapunov-like approach, we derive sufficient conditions for tracking error convergence in the sense of L-2 norm in terms of linear matrix inequalities based on rigorous analysis, which can also guarantee the monotonic convergence of the input error in some given norm. The results of numerical simulations are presented to illustrate the effectiveness of the proposed ILC approach.
The basic structure of an engineering approach for the control of distributed parameter systems will be presented in the scope of this tutorial. This method is based on numerical models of technological and manufactur...
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ISBN:
(纸本)9781728137582
The basic structure of an engineering approach for the control of distributed parameter systems will be presented in the scope of this tutorial. This method is based on numerical models of technological and manufacturing processes, represented as lumped input and distributedparameter output systems. Decomposition of dynamics and control synthesis into temporal and spatial components will be introduced along with distributedparameter open loop control and feedback control loops. Moreover, the basic software support called DPS Blockset for Simulink, a third-party software product of The MathWorks Company will be demonstrated along with some results of control of secondary cooling in continuous casting of steel.
This paper presents a new model-based fault detection and estimation framework for a class of multi-input and multi-output (MIMO) nonlinear distributed parameter systems (DPS) described by partial differential equatio...
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ISBN:
(纸本)9781538683576
This paper presents a new model-based fault detection and estimation framework for a class of multi-input and multi-output (MIMO) nonlinear distributed parameter systems (DPS) described by partial differential equations (PDE) with actuator and sensor faults. The fault functions cover both abrupt and incipient faults. A Luenberger type observer is used to monitor the health of the DPS as a detection observer on the basis of the nonlinear PDE representation of the system with measured output vector. By taking the difference between measured and estimated outputs from this observer, a residual signal is generated for fault detection. If the detection residual exceeds a predefined threshold, a fault will be claimed to be active. Once an actuator or a sensor fault is detected and the fault type is identified, an appropriate fault parameter update law is developed to learn the fault dynamics online with the help of an additional output measurement. Eventually, the proposed detection and estimation framework is demonstrated on a nonlinear process.
The paper considers the problem of gramians computation for linear parabolic distributedparameters systems like the heat flow in a rod. The solution of the described partial differential equation is derived by applyi...
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ISBN:
(数字)9781728193083
ISBN:
(纸本)9781728193090
The paper considers the problem of gramians computation for linear parabolic distributedparameters systems like the heat flow in a rod. The solution of the described partial differential equation is derived by applying the approach of time-space separation and by using the spectral method. By analogy to the finite dimensional case, it is shown that the derived solution consists of two parts. The first part is due to the initial conditions and participates in forming the observability gramian of the system. The second part is due to the system input and takes part in computing the reachability gramian. Different cases for problem definition in terms of different boundary conditions are given, showing how in such cases, the presented method can be used for gramians computation.
This paper is motivated by economic aspects of fixed initial and operating costs for control of spatially distributedsystems. In particular, the paper investigates the possibility of a large number of inexpensive act...
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ISBN:
(数字)9781538682661
ISBN:
(纸本)9781538682678
This paper is motivated by economic aspects of fixed initial and operating costs for control of spatially distributedsystems. In particular, the paper investigates the possibility of a large number of inexpensive actuating and sensing devices, as an alternative to (a reduced number of) expensive high capacity devices. While such an alternative reduces the fixed initial costs associated with actuators and sensors, it may also lead to increased operating costs resulting from communication requirements between the now-networked actuator-sensor-control units. To simplify the controller architecture, a proportional controller is assumed that amounts to a static output feedback controller. In a network of n actuator-sensor pairs, an all-to-all communication topology results in a fully populated static output feedback matrix with as much as n(n-1) communication links. In addition to a traditional performance index used to obtain the static output feedback gain matrix, this paper proposes a mixed index wherein both the traditional performance index and the number of communication links (representing operating costs associated with information exchange links), are taken into account. As an example, the proposed scheme is applied to a parabolic partial differential equation having four actuator-sensor pairs. The resulting optimization produces a sparse static gain matrix with a communication topology that has half the graph edges of the fully connected case and with essentially the same performance.
Aiming at a class of linear second-order hyperbolic distributed parameter systems (DPSs), we consider a P-type iterative learning control (ILC) scheme based on high-order internal models (HOIMs) to track the iteration...
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ISBN:
(数字)9781728162461
ISBN:
(纸本)9781665419352
Aiming at a class of linear second-order hyperbolic distributed parameter systems (DPSs), we consider a P-type iterative learning control (ILC) scheme based on high-order internal models (HOIMs) to track the iteration-varying reference trajectories, where reference trajectories in the iteration axis are generated by a HOIM formula. By virtue of contraction mapping principle, it is proved that the actual output trajectory of the system can realize the perfect tracking of the expected trajectory on L 2 space along the iteration axis. Finally, numerical simulation cases verify the validity of the designed algorithm.
This paper considers the sampled-data observer design problem of space-varying distributed parameter systems (DPSs). By utilizing a Lyapunov functional, a sampled-data observer design is developed by spatial linear ma...
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ISBN:
(数字)9789881563903
ISBN:
(纸本)9781728165233
This paper considers the sampled-data observer design problem of space-varying distributed parameter systems (DPSs). By utilizing a Lyapunov functional, a sampled-data observer design is developed by spatial linear matrix inequalities (SLMIs) to guarantee the exponential stability for the estimation error DPS. Furthermore, to solve SLMIs, the sampled-data observer design for space-varying DPSs is formulated as an LMI feasibility problem. Lastly, simulation results of a numerical example are provided to illustrate the effectiveness of the proposed method.
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