Adaptive disturbance rejection for strict-feedback switched nonlinear systems using multiple Lyapunov functions

Proceeding of the 11th World Congress on Intelligent Control and Automation

2014

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This paper investigates the problem of adaptive fuzzy output-feedback control for a class of switched uncertain nonlinear systems without the measurements of the system states. By utilizing fuzzy logic systems to approximate unknown nonlinear functions, a novel adaptive fuzzy control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched observer is designed to reduce the conservativeness caused by adoption of a common observer for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain semiglobally uniformly ultimately bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin.

“…Obviously, such a switched nonlinear structure (1) is much more general than the switched and non-switched nonlinear structure in [16], [23], [3], [4].…”

Section: A Switched Nonlinear Systemsmentioning

confidence: 99%

Adaptive fuzzy output-feedback control of switched uncertain nonlinear systems

Proceeding of the 11th World Congress on Intelligent Control and Automation

2014

Self Cite

“…In order to solve the problem under study, we improve the classical average dwell time method in this paper. 4) Unlike the existing results in [24]- [26] and [37] where all system functions are known, the system functions considered in this paper are unknown. Also, the proposed result extends the stabilizing results of switched nonlinear systems with known nonlinearities in [25] and [37] to switched uncertain nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, for a special class of switched systems, switched nonlinear systems in strict-feedback form have been studied systematically by the backstepping technique. In [24] and [26], adaptive disturbance rejection and H ∞ control problem for switched nonlinear systems in strictfeedback form and p-normal form are studied on the basis of the multiple Lyapunov functions method, respectively; global stabilization for switched nonlinear systems in strict-feedback form under arbitrary switchings is achieved in [25] and [37]. The abovementioned results are based on the assumption that all system nonlinearities are known.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, many complex system dynamics in real world are too difficult to be explicitly formulated. In such case, the results in [24]- [26] and [37] are not directly applicable. Therefore, for switched uncertain nonlinear systems, it is desirable to use the adaptive control based on universal function approximators [32], [39].…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge, there are no results on adaptive outputfeedback neural control available for switched uncertain nonlinear systems up to now. 2) In order to reduce the conservativeness caused by adoption of a common observer in [25] and a common update law in [26] and [34] for all subsystems, a switched filter is designed to estimate the unmeasurable system states, and different update laws for different subsystems are also designed. Meanwhile, we simultaneously construct adaptive output-feedback controllers of subsystems and give a class of switching signals with average dwell time.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time

IEEE Trans. Neural Netw. Learning Syst.

2015

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255

133

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

Switched adaptive stabilization of switched nonlinearly parameterized cascade systems and its application to a two inverted pendulums

Adaptive Control & Signal

2014

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This paper studies adaptive control of switched nonlinearly parameterized cascade systems. No solvability of the adaptive control problem for subsystems is required. By exploiting the multiple Lyapunov functions method and the parameter separation technique and the tool of adding a power integrator, we develop a new switched adaptive control approach for the explicit construction of adaptive controllers of subsystems and a proper switching law that solves the adaptive stabilization problem. A key feature of the proposed adaptive controllers is its switched property, namely, each subsystem has its individual update law. A two-inverted pendulum as a practical example is also provided to demonstrate the effectiveness of the proposed design method.On the other hand, uncertainties extensively exist in real world systems. For example, such uncertainties often appear in control systems such as those in electrical, friction dynamics, dynamics of magnetic bearing, mechanical, chemical, aeronautical, and biomedical engineering [19][20][21][22]. Adaptive control is an effective methodology, which provides adaptation mechanisms to adjust controllers for systems with parametric, structural, and environmental uncertainties to achieve desired system performance [23][24][25]. For about two decades, hence, adaptive control of non-switched nonlinear systems with parametric uncertainty has been one of the most active subjects in the field of nonlinear control [26,27]. In particular, adaptive control has proven its great capability in compensating for non-switched nonlinearly parameterized systems involving inherent nonlinearity on the basic of a parameter separation technique [28].For switched systems, adaptive control was not studied until recently focusing on switched linear systems [29-32] and piecewise affine systems [33,34]. For switched nonlinear systems with parametric uncertainty, however, few results on adaptive control have appeared by now. In [35], an adaptive neural networks (NN) control scheme for strict-feedback switched nonlinear systems is proposed. By using the CLF method and backstepping, adaptive stabilization for strict-feedback switched nonlinear systems under arbitrary switchings is achieved [36]. On the basis of the MLFs technique, an adaptive disturbance rejection problem for switched nonlinear systems in strictfeedback form with unknown exosystem is studied in [37]. Tamba and Leksono and Long and Zhao [36,37] present some effective methods of the adaptive control problem for switched nonlinear systems in strict-feedback form. It should be observed that the literature mentioned earlier has focused on adaptive control of switched nonlinear systems with linear parameterization, and a common update law is used to estimate all the vector parameters in different subsystems. Most switched nonlinear systems in practice, however, do not possess linear parameterization and a common update law for all subsystems. In addition, nonlinear parameterization can be found in various practical control systems such as machine...