In this paper, the finite-time stability and stabilization of nonlinear systems with delays is studied, via a Takagi-Sugeno approach. By using a novel Lyapunov-Krasovskii functional and introducing some fuzzy free-wei...
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In this paper, the finite-time stability and stabilization of nonlinear systems with delays is studied, via a Takagi-Sugeno approach. By using a novel Lyapunov-Krasovskii functional and introducing some fuzzy free-weighting matrices, sufficient conditions are derived, for bounded and differentiable time-varying delays in terms of an upper bound of the delay derivatives. Then, we achieve closed-loop stabilization in finite time through an efficient parallel distributed compensation design. The sufficient conditions are formulated as linear matrix inequalities to achieve the desired performance. Finally, the proposed methodology is applied to various case studies, highlighting its significance.
In this paper, we investigate the stability analysis and synthesis problems for both continuous-time and discrete-time fuzzy singularly perturbed systems. For continuous-time case, both the stability analysis and synt...
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In this paper, we investigate the stability analysis and synthesis problems for both continuous-time and discrete-time fuzzy singularly perturbed systems. For continuous-time case, both the stability analysis and synthesis can be parameterized in terms of a set of linear matrix inequalities (LMIs). For discrete-time case, only the analysis problem can be cast in LMIs, while the derived stability conditions for controller design are nonlinear matrix inequalities (NMIs). Furthermore, a two-stage algorithm based on LMI and iterative LMI (ILMI) techniques I'S developed to solve the resulting NMIs and the stabilizing feedback controller gains can be obtained. For both continuous-time and discrete-time cases, the reduced-control law, which is only dependent on the slow variables, is also discussed. Finally, an illustrated example based on the flexible joint inverted pendulum model is given to illustrate the design procedures.
In this paper, the practical covariance control theory is applied to incorporate the concept of variance constrained control for the discrete nonlinear systems using T-S fuzzy models. This paper focuses on the control...
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In this paper, the practical covariance control theory is applied to incorporate the concept of variance constrained control for the discrete nonlinear systems using T-S fuzzy models. This paper focuses on the control problem of finding observed-state feedback gains for the discrete fuzzy controllers, which can achieve the common state covariance assignment. Finally, a numerical example will be used to show the simulation results of the present fuzzy control method and usefulness of the proposed approach.
In this paper, a new systematic approach is presented to further decrease the conservativeness in stability analysis condition and controller design. Non-quadratic Lyapunov function is utilized to derive stability con...
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In this paper, a new systematic approach is presented to further decrease the conservativeness in stability analysis condition and controller design. Non-quadratic Lyapunov function is utilized to derive stability conditions in terms of linear matrix inequalities. Also, the control problem is formulated in a generalized eigenvalue problem. Considering the concept of decay rate and control input constraint, a new systematic procedure is proposed to calculate a maximum bound for the upper bounds of the time derivatives of the membership functions. Moreover, some slack matrices are introduced that help to reduce conservativeness. The number of inequalities is few compared to the existing results in literature, which helps the feasibility in the case of large number of fuzzy rules. Simulation examples and comparison results demonstrate the merits of this method.
The stability analysis and design of the systems, described in Takagi-Sugeno's (TS) fuzzy model, are discussed in this correspondence. Based on the alternating projection method, the stability issue can be extende...
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The stability analysis and design of the systems, described in Takagi-Sugeno's (TS) fuzzy model, are discussed in this correspondence. Based on the alternating projection method, the stability issue can be extended to a prescribed stability region. And the projection algorithm is proposed for assuring the desired stability. By involving the controller, we further introduce the design issues for the closed-1oop system. Some numerical examples are given to demonstrate the validity and feasibility.
This paper deals with the synthesis of fuzzy controller applied to the induction motor with a guaranteed H tracking performance. First, the Takagi-Sugeno fuzzy model is employed to approximate a nonlinear system in th...
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This paper deals with the synthesis of fuzzy controller applied to the induction motor with a guaranteed H tracking performance. First, the Takagi-Sugeno fuzzy model is employed to approximate a nonlinear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy observer-based fuzzy tracking controller is designed to stabilize the induction motor and guaranteed a minimum disturbance attenuation level for the closed-loop system. The rotor flux is unavailable for measurement and it is estimated by a fuzzy observer. An integral action is added to the new parallel distributed compensation fuzzy controller related to the tracking to avoid static errors. The gains of fuzzy control and fuzzy observer are obtained by solving a set of Linear Matrix Inequality. Finally, simulation result is given to demonstrate the controllers effectiveness.
This paper presents a fuzzy controller and observer design for backward movement control of a trailer-truck A nonlinear dynamic model of the trailer-truck is represented by a Takagi-Sugeno fuzzy model. The concept of ...
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This paper presents a fuzzy controller and observer design for backward movement control of a trailer-truck A nonlinear dynamic model of the trailer-truck is represented by a Takagi-Sugeno fuzzy model. The concept of parallel distributed compensation is employed to design a fuzzy controller and a fuzzy observer from the Takagi-Sugeno fuzzy model of the trailer-truck. Stability conditions of the fuzzy control system are derived, using the Lyapunov approach. It is shown that the stability conditions are characterized in terms of linear matrix inequalities (LMIs). Stability of the overall fuzzy control system, including a fuzzy controller and a fuzzy observer is guaranteed by using a convex optimization technique based on LMIs. Simulation and experimental results show that the fuzzy controller and the fuzzy observer effectively achieve backward movement control of the trailer-truck. (C) 1997 Published by Elsevier Science Ltd. All rights reserved.
This work presents stable composite control criteria for multivariable Takagi-Sugeno (T-S) fuzzy systems. On the basis of the linear matrix inequality (LMI) control strategy and parametric optimization, the composite ...
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This work presents stable composite control criteria for multivariable Takagi-Sugeno (T-S) fuzzy systems. On the basis of the linear matrix inequality (LMI) control strategy and parametric optimization, the composite fuzzy control algorithms are derived. Unlike earlier studies of fuzzy-control systems on an LMI framework, this investigation develops a supervisory control approach, such that a fuzzy controller can be synthesized more efficiently. Moreover, a robust control scheme is applied to the T-S fuzzy model with parametric uncertainties. The sufficient conditions are deduced in the form of reduced LMIs and adaptive tuning rules. Finally, numeric simulations are given to validate the proposed approach. (C) 2005 Elsevier Inc. All rights reserved.
Many works in the literature have studied the kinematical and dynamical issues of parallel robots. But it is still difficult to extend the vast control strategies to parallel mechanisms due to the complexity of the mo...
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Many works in the literature have studied the kinematical and dynamical issues of parallel robots. But it is still difficult to extend the vast control strategies to parallel mechanisms due to the complexity of the model-based control. This complexity is mainly caused by the presence of multiple closed kinematic chains, making the system naturally described by a set of differential-algebraic equations. The aim of this work is to control a two-degree-of-freedom parallel manipulator. A mechanical model based on differential-algebraic equations is given. The goal is to use the structural characteristics of the mechanical system to reduce the complexity of the nonlinear model. Therefore, a trajectory tracking control is achieved using the Takagi-Sugeno fuzzy model derived from the differential-algebraic equation forms and its linear matrix inequality constraints formulation. Simulation results show that the proposed approach based on differential-algebraic equations and Takagi-Sugeno fuzzy modeling leads to a better robustness against the structural uncertainties.
This article proposes a systematic analysis for a tracking problem which ensures cooperation amongst a swarm of unmanned aerial vehicles (UAVs), modelled as nonlinear systems with linear and angular velocity constrain...
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This article proposes a systematic analysis for a tracking problem which ensures cooperation amongst a swarm of unmanned aerial vehicles (UAVs), modelled as nonlinear systems with linear and angular velocity constraints, in order to achieve different goals. A distributed Takagi-Sugeno (TS) framework design is adopted for the representation of the nonlinear model of the dynamics of the UAVs. The distributed control law which is introduced is composed of both node and network level information. Firstly, feedback gains are synthesised using a parallel distributed compensation (PDC) control law structure, for a collection of isolated UAVs;ignoring communications among the swarm. Then secondly, based on an alternation-like procedure, the resulting feedback gains are used to determine Lyapunov matrices which are utilised at network level to incorporate into the control law, the relative differences in the states of the vehicles, and to induce cooperative behaviour. Eventually stability is guaranteed for the entire swarm. The control synthesis is performed using tools from linear control theory: in particular the design criteria are posed as linear matrix inequalities (LMIs). An example based on a UAV tracking scenario is included to outline the efficacy of the approach.
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