In this paper, we propose a general method to simultaneously identify both unknown time delays and unknown model parameters in delayed dynamical systems based on the autosynchronization technique. The design procedure...
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In this paper, we propose a general method to simultaneously identify both unknown time delays and unknown model parameters in delayed dynamical systems based on the autosynchronization technique. The design procedure is presented in detail by constructing a specific Lyapunov function and linearizing the model function with nonlinear parameterization. The obtained result can be directly extended to the identification problem of linearly parameterized dynamical systems. Two Wpical numerical examples confirming the effectiveness of the identification method are given.
In this paper an adaptive control approach for completely non-affine pure-feedback systems with nonlinear parameterization is proposed. By using the parameter separation technique and coupling it effectively with comb...
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In this paper an adaptive control approach for completely non-affine pure-feedback systems with nonlinear parameterization is proposed. By using the parameter separation technique and coupling it effectively with combination of backstepping and time scale separation, a fast dynamical equation is derived from the original subsystem, where the solution is sought to approximate the corresponding ideal virtual/actual control input. In this approach, since designing state predictor to derive adaptation law of unknown parameters is omitted, our design is more accurate and less complex. The closed loop stability and the state regulation of nonlinear parameterization pure-feedback systems are all proved by new theorem in singular perturbation theory. Finally the simulation results are provided to demonstrate the effectiveness of the proposed approach.
This paper addresses the problem of global regulation of nonlinear lower-triangular systems with nonlinear parameterization. The uncertain parameters are assumed to be in an unknown compact set or unbounded. To solve ...
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This paper addresses the problem of global regulation of nonlinear lower-triangular systems with nonlinear parameterization. The uncertain parameters are assumed to be in an unknown compact set or unbounded. To solve this problem, we propose a novel time-varying control design for uncertain lower-triangular systems. The proposed controller guarantees that closed-loop system trajectories are well-defined and bounded. In addition, after a certain finite time, all of the closed-loop trajectories exponentially converge to the origin.
This paper concerns adaptive estimation of dynamic systems which are nonlinearly parameterized. A majority of adaptive algorithms employ a gradient approach to determine the direction of adjustment, which ensures stab...
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This paper concerns adaptive estimation of dynamic systems which are nonlinearly parameterized. A majority of adaptive algorithms employ a gradient approach to determine the direction of adjustment, which ensures stable estimation when parameters occur linearly. These algorithms, however, do not suffice for estimation in systems with nonlinear parameterization. We introduce in this paper a new algorithm for such systems and show that it leads to globally stable estimation by employing a different regression vector and selecting a suitable step size. Both concave/convex parameterizations as well as general nonlinear parameterizations are considered. Stable estimation in the presence of both nonlinear parameters and linear parameters which may appear multiplicatively is established. For the case of concave/convex parameterizations, parameter convergence is shown to result under certain conditions of persistent excitation. (C) 2000 Elsevier Science Ltd. All rights reserved.
This article provides a solution to the problem of global adaptive regulation, for a class of nonlinearly parameterized cascade systems including feedback linearizable and minimum-phase systems with nonlinear paramete...
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This article provides a solution to the problem of global adaptive regulation, for a class of nonlinearly parameterized cascade systems including feedback linearizable and minimum-phase systems with nonlinear parameterization. The solution is derived by using a novel parameter separation technique combined with a feedback domination design. We remove all the restrictive conditions previously imposed on the unknown parameters, such as linear parameterization or convex/concave parameterization conditions, which have been commonly assumed so far in the literature of nonlinear adaptive control. Copyright (C) 2002 John Wiley Sons, Ltd.
In this paper, an adaptive controller is designed for a class of nonholonomic systems in chained form with nonlinear parameterization. The robust adaptive control law is developed using parameter separation, state sca...
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In this paper, an adaptive controller is designed for a class of nonholonomic systems in chained form with nonlinear parameterization. The robust adaptive control law is developed using parameter separation, state scaling and backstepping technique. Global asymptotic regulation of the closed-loop system states is achieved. The proposed control based switching strategy is proposed to overcome the uncontrollability problem associated with x(0)(t(0)) = 0. (C) 2009 Elsevier Ltd. All rights reserved.
The problem of adaptive output-feedback control of nonlinearly parameterized stochastic nonholonomic systems is studied in this paper. Since many unknowns (e.g., unknown control coefficients and unknown nonlinear para...
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The problem of adaptive output-feedback control of nonlinearly parameterized stochastic nonholonomic systems is studied in this paper. Since many unknowns (e.g., unknown control coefficients and unknown nonlinear parameters in systems' nonlinearities) occur into systems, we utilize an adaptive control method, together with a parameter separation technique, to construct an adaptive output feedback controller to regulate the whole systems. During the design procedure, a new form of reduced-order K-filters is given to compensate the unmeasured states of the systems. A switching strategy is proposed explicitly to stabilize the entire systems in the control scheme. Finally, a bilinear model with stochastic disturbances is presented to demonstrate our theoretical results. (C) 2018 Elsevier Ltd. All rights reserved.
This paper investigates the adaptive stabilization of stochastic high-order nonholonomic systems with nonlinear parameterization. An adaptive state feedback controller is designed by using the parameter separation tec...
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This paper investigates the adaptive stabilization of stochastic high-order nonholonomic systems with nonlinear parameterization. An adaptive state feedback controller is designed by using the parameter separation technique and input-state scaling technique, and adding a power integrator backstepping approach. The switching strategy is proposed to eliminate the phenomenon of uncontrollability and to guarantees that the closed-loop system has an almost surely unique solution for any initial state, the equilibrium of interest is globally stable in probability, and the state can almost surely be regulated to the origin. Simulation examples demonstrate the effectiveness of the proposed scheme.
We prove that under an appropriate input-to-state stability condition, it is possible to achieve global adaptive stabilization for a class of nonlinearly parameterized cascade systems, using a C-o partial-state adapti...
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We prove that under an appropriate input-to-state stability condition, it is possible to achieve global adaptive stabilization for a class of nonlinearly parameterized cascade systems, using a C-o partial-state adaptive regulator. This result complements the earlier work on adaptive control of inherently nonlinear uncertain systems with uncontrollable unstable linearization, which cannot be dealt with by any smooth adaptive control scheme.
In this paper, an adaptive control method is presented for a class of first-order systems with nonlinear parameterization. The main features of the scheme are that a novel integral-type Lyapunov function is developed ...
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In this paper, an adaptive control method is presented for a class of first-order systems with nonlinear parameterization. The main features of the scheme are that a novel integral-type Lyapunov function is developed for constructing an asymptotically stable adaptive controller, and output tracking error bounds are provided to evaluate the control performance of the adaptive system. The design procedure and the effectiveness of the proposed controller are illustrated through an example study.
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