This paper is focused on reliable fuzzy H ∞ controller design for active suspension systems with actuator delay and fault. The Takagi-Sugeno (T-S) fuzzy model approach is adapted in this study with ...the consideration of the sprung and the unsprung mass variation, the actuator delay and fault, and other suspension performances. By the utilization of the parallel-distributed compensation scheme, a reliable fuzzy H ∞ performance analysis criterion is derived for the proposed T-S fuzzy model. Then, a reliable fuzzy H ∞ controller is designed such that the resulting T-S fuzzy system is reliable in the sense that it is asymptotically stable and has the prescribed H ∞ performance under given constraints. The existence condition of the reliable fuzzy H ∞ controller is obtained in terms of linear matrix inequalities (LMIs) Finally, a quarter- vehicle suspension model is used to demonstrate the effectiveness and potential of the proposed design techniques.
This paper is concerned with the stabilization problem for a class of Markovian stochastic jump systems against sensor fault, actuator fault and input disturbances simultaneously. In the proposed ...approach, the original plant is first augmented into a new descriptor system, where the state vector, disturbance vector and fault vector are assembled into the state vector of the new system. Then, a novel augmented sliding mode observer is presented for the augmented system and is utilized to eliminate the effects of sensor faults and disturbances. An observer-based mode-dependent control scheme is developed to stabilize the resulting overall closed-loop jump system. A practical example is given to illustrate the effectiveness of the proposed design methodology.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
This paper investigates the dynamic output feedback control problem for interval type-2 (IT2) fuzzy systems. A switched output feedback controller, which depends on the values of membership ...functions, is constructed. The membership functions of IT2 fuzzy systems contain parameter uncertainties and are different from the type-1 Takagi-Sugeno fuzzy systems. Based on the IT2 fuzzy set theory, the parameter uncertainties can be effectively obtained by upper and lower membership functions. A novel IT2 switched output feedback controller is designed to ensure that the closed-loop system is asymptotically stable with an H∞ performance. Finally, a mass-spring-damping system is proposed to show the feasibility and the merit of the proposed scheme over the other existing ones.
This paper considers the problem of observer-based adaptive neural network (NN) control for a class of single-input single-output strict-feedback nonlinear stochastic systems with unknown time ...delays. Dynamic surface control is used to avoid the so-called explosion of complexity in the backstepping design process. Radial basis function NNs are directly utilized to approximate the unknown and desired control input signals instead of the unknown nonlinear functions. The proposed adaptive NN output feedback controller can guarantee all the signals in the closed-loop system to be mean square semi-globally uniformly ultimately bounded. Simulation results are provided to demonstrate the effectiveness of the proposed methods.
This paper considers the problem of adaptive neural control of nonlower triangular nonlinear systems with unmodeled dynamics and dynamic disturbances. The design difficulties appeared in the ...unmodeled dynamics and nonlower triangular form are handled with a dynamic signal and a variable partition technique for the nonlinear functions of all state variables, respectively. It is shown that the proposed controller is able to ensure the semi-global boundedness of all signals of the resulting closed-loop system. Furthermore, the system output is ensured to converge to a small domain of the given trajectories. The main advantage about this research is that a neural networks-based tracking control method is developed for uncertain nonlinear systems with unmodeled dynamics and nonlower triangular form. Simulation results demonstrate the feasibility of the newly presented design techniques.
This paper investigates the problem of filter design for interval type-2 (IT2) fuzzy systems with D stability constraints based on a new performance index. Attention is focused on solving the H ∞ , L ...2 -L ∞ , passive, and dissipativity fuzzy filter design problems for IT2 fuzzy systems with D stability constraints in a unified frame. Under the new performance index frame, using Lyapunov stability theory, a novel type of IT2 filter is designed such that the filtering error system guarantees the prescribed H ∞ , L 2 -L ∞ , passive, and dissipativity performance levels with D stability constraints. The existence condition of the IT2 filter is expressed as the convex optimization problem, and the filter parameters in the condition can be solved by the standard software. The IT2 fuzzy model and IT2 fuzzy filter do not need to share the same lower and upper membership functions. Finally, a numerical example is provided to show the effectiveness of the proposed results.
In this paper, the problem of fuzzy control for nonlinear networked control systems with packet dropouts and parameter uncertainties is studied based on the interval type-2 fuzzy-model-based ...approach. In the control design, the intermittent data loss existing in the closed-loop system is taken into account. The parameter uncertainties can be represented and captured effectively via the membership functions described by lower and upper membership functions and relative weighting functions. A novel fuzzy state-feedback controller is designed to guarantee the resulting closed-loop system to be stochastically stable with an optimal performance. Furthermore, to make the controller design more flexible, the designed controller does not need to share membership functions and amount of fuzzy rules with the model. Some simulation results are provided to demonstrate the effectiveness of the proposed results.
In this technical note, a new fault detection design scheme is proposed for interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy systems with sensor fault based on a novel fuzzy observer. The parameter ...uncertainties can be captured by the membership functions of the IT2 fuzzy model. The premise variables of the plant are perfectly shared by the fuzzy observer. A stochastic process between the plant and the observer is considered in the system. A fault sensitive performance is established, and then sufficient conditions are obtained for determining the fuzzy observer gains. Finally, simulation results are provided to verify the effectiveness of the presented scheme.
The problem of fuzzy observer-based controller design is investigated for nonlinear networked control systems subject to imperfect communication links and parameter uncertainties. The nonlinear ...networked control systems with parameter uncertainties are modeled through an interval type-2 (IT2) Takagi-Sugeno (T-S) model, in which the uncertainties are handled via lower and upper membership functions. The measurement loss occurs randomly, both in the sensor-to-observer and the controller-to-actuator communication links. Specially, a novel data compensation strategy is adopted in the controller-to-actuator channel. The observer is designed under the unmeasurable premise variables case, and then, the controller is designed with the estimated states. Moreover, the conditions for the existence of the controller can ensure that the resulting closed-loop system is stochastically stable with the predefined disturbance attenuation performance. Two examples are provided to illustrate the effectiveness of the proposed method.
Based on engineered or bacterial nucleases, the development of genome editing technologies has opened up the possibility of directly targeting and modifying genomic sequences in almost all eukaryotic ...cells. Genome editing has extended our ability to elucidate the contribution of genetics to disease by promoting the creation of more accurate cellular and animal models of pathological processes and has begun to show extraordinary potential in a variety of fields, ranging from basic research to applied biotechnology and biomedical research. Recent progress in developing programmable nucleases, such as zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeat (CRISPR)-Cas-associated nucleases, has greatly expedited the progress of gene editing from concept to clinical practice. Here, we review recent advances of the three major genome editing technologies (ZFNs, TALENs, and CRISPR/Cas9) and discuss the applications of their derivative reagents as gene editing tools in various human diseases and potential future therapies, focusing on eukaryotic cells and animal models. Finally, we provide an overview of the clinical trials applying genome editing platforms for disease treatment and some of the challenges in the implementation of this technology.
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