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This paper presents a novel approach to design a composite adaptation law for neural networks that uses both the system tracking errors and a prediction error containing parametric information by devising an innovative swapping procedure that uses the recently developed Robust Integral of the Sign of the Error (RISE) feedback method. Semi-global asymptotic tracking is proven for an Euler-Lagrange...
A novel control design is presented for the adaptive control of a general MIMO system with a gradient-based composite adaptive update law. The composite update law is driven by tracking and prediction errors with a fixed adaptation gain. An innovative scheme is developed in a swapping procedure that makes use of the recently developed Robust Integral of the Sign of the Error (RISE) technique to generate...
Zooming type adaptive quantizers have been introduced in the networked control literature as efficient coders for stabilizing open-loop unstable noise-free systems connected over noiseless channels with arbitrary initial conditions. Such quantizers can be regarded as a special class of the Goodman-Gersho adaptive quantizers. In this paper, we provide a stochastic stability result for such quantizers...
Adaptive IIR filter analysis is more complicated than for the FIR case because (a) some algorithm signals are generated by the adaptive filter itself, and (b) the prediction error relates to the adapted parameters via a filtering operation. Averaging analyses of stability address the first issue by linearization about the convergence point, and the second by using passivity of the error operator....
In order to solve assignment problem in inventing mass media context and improve assignment efficiency and system stability, this paper analyzes the transition of Markov chain state and introduces a queues assignment model. The paper proposes an adaptive task assignment method suitable for mass media context invention by studying the key factors affecting system state transition. Experimental results...
This paper presents a new convergence analysis of the least mean fourth (LMF) adaptive algorithm, in the mean square sense. The analysis improves previous results, in that it is valid for non-Gaussian noise distributions and explicitly shows the dependence of algorithm stability on the initial conditions of the weights. Analytical expressions are derived presenting the relationship between the step...
We investigate robust decentralized adaptive controller design for interconnected systems. Motivated by real mechanical systems, we consider a general representation of interconnections when the strength of the interconnections is bounded by a pth-order polynomial in states. This is in contrast to other works which have made simpler assumptions about the strength of the interconnections. The possible...
Pi-coefficients give a quantitative measure of energy exchange properties of a system. To find appropriate pi-coefficents for stability analysis, the so-called max-p problem is formulated. Moreover, this problem is reduced and decomposed into a series of subproblems. A parameter estimation problem is illustrated to show the relaxness of SPR (strictly positive real) condition.
Certain problems of adaptive systems revolve round finding a transfer function q(s) (which is not proper) such that a set of transfer functions q(s)/b(s)-1/2 is strictly positive real for all polynomial b(s) in a certain set. This paper treats this and some related problems.
This paper presents a new methodology for the global stability analysis, and consequently, for the design of robust deterministic and stochastic adaptive control, filtering and prediction. The methodology advocated herein represents a mathematical formalization of the self-stabilization mechanism which is a natural characteristic of every properly designed adaptive system. The effectiveness of the...
This paper considers discrete time adaptive pole assignment control suject to a saturation control constraint. It establishes the closed loop system stability for a class of type-1 plants. In the presence of plant modeling uncertainties and disturbances it shows that the stability is maintained by implementing a simple fixed deadzone in the parameter estimator. If the plant is free from the modeling...
This paper presents some new normalizing signals for the design of robust adaptive control schemes for plants with unmodeled dynamics and bounded disturbances. The stability margin of the unmodeled dynamics is not needed to generate the normalizing signal. The class of unmodeled dynamics admissible ble to robust adaptive control is further enlarged. The modified robust model reference adaptive control...
A decentralized indirect adaptive control scheme that may be applied to both interconnected and overlapping interconnected systems is presented. With the presented scheme indirect adaptive controllers are applied at each control station of a multi-control-station system. The adaptive controller at a given control station is designed for the subsystems connected to that station, and the controlled...
Nonlinear indirect adaptive control is motivated by the fact that, with exact knowledge of the plant parameters, a nonlinear state feedback law and a suitable set of coordinates can be chosen to produce linear input-output behavior. In the case of parameter uncertainty, intuition suggests that parameter estimates which are converging to their true values can be used to asymptotically linearize the...
This paper presents a globally stable adaptive regulator for non-minimum phase systems subject to bounded disturbances. The proposed indirect control scheme does not require persistency of excitation. A least squares identification algorithm with dead zone was used together with a sequence of optimal controls with finite horizon.
The question is examined of when an adaptive control system is robust to modeled dynamics and unknown bonded disturbances. Conditions are presented that insure the existence of such robustness properties, but only locally; i.e., restrictions are placed on the behavior of signals in the ideal, perfectly tuned adaptive system. Local L??-stability is investigated when the tuned signals are assumed to...
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