Abstract:In this paper, we solve the problem of output tracking for linear uncertain systems in the presence of unknown actuator failures using discontinuous projection-based output feedback adaptive robust control (ARC). The faulty actuators are characterized as unknown inputs stuck at unknown values experiencing bounded disturbance and actuators losing effectiveness at unknown instants of time. Many existing techniques to solve this problem use model reference adaptive control (MRAC), which may not be well suited for… Show more
“…We note here that our focus is specifically on the use and evaluation of L 1 adaptive methods. However have been other robust and adaptive techniques, providing for example fault tolerance to actuator faults and allowing for system delays (Gayako & Yao, 2011;Wu & Yang, 2014), which will be considered in future designs.…”
Section: The L 1 Adaptive Controller Architecturementioning
a b s t r a c tIn this paper, the development and implementation of L 1 adaptive control designs for anesthesia delivery to patients in surgical settings is presented. Our main objectives are the design of model-based feedback controllers ensuring that the patient's bispectral index profile tracks a prespecified reference trajectory, and demonstrates robustness to inter-patient variability. Patient models are constructed based on clinical trial data and gray box system identification methods. Controller switching mechanisms and specific safety measures are considered in the design and discussed in the paper. Simulation results are provided, demonstrating the effectiveness of the control methods.
“…We note here that our focus is specifically on the use and evaluation of L 1 adaptive methods. However have been other robust and adaptive techniques, providing for example fault tolerance to actuator faults and allowing for system delays (Gayako & Yao, 2011;Wu & Yang, 2014), which will be considered in future designs.…”
Section: The L 1 Adaptive Controller Architecturementioning
a b s t r a c tIn this paper, the development and implementation of L 1 adaptive control designs for anesthesia delivery to patients in surgical settings is presented. Our main objectives are the design of model-based feedback controllers ensuring that the patient's bispectral index profile tracks a prespecified reference trajectory, and demonstrates robustness to inter-patient variability. Patient models are constructed based on clinical trial data and gray box system identification methods. Controller switching mechanisms and specific safety measures are considered in the design and discussed in the paper. Simulation results are provided, demonstrating the effectiveness of the control methods.
“…Assume the closed-loop FTC system (6) satisfying Assumptions 1-4, and linear matrix inequality (LMI) (11) is feasible. Then the sliding mode FTC law described in equations (12) and (13) with adaptive laws (15) and (16) can ensure that the closed-loop system (6) is asymptotically stable and the H ' performance bound is no larger than g 0 despite actuator failures, unmatched uncertainties, and disturbance effects.…”
Section: Sliding Mode Ftc Law Designmentioning
confidence: 99%
“…Since Theorem 1 implies that Q . 0, a(t) = x T (t)P À1 B 2v = 0, and outputs of the adaptive mechanisms (15) and (16) are all zero, one can see that…”
Section: Sliding Mode Ftc Law Designmentioning
confidence: 99%
“…Considering the adaptive laws given in equation (15), we have À2hml Nm0 k a k + 2g À1 mm 0 _ m 0 = 0 Furthermore, the adaptive laws (16) are adopted, and we can obtain the inequality as follows…”
Section: Sliding Mode Ftc Law Designmentioning
confidence: 99%
“…It is worth noting that adaptive actuator failure compensation control schemes, as one of the effective active methods, have been recently studied to compensate for unknown actuator failures. [9][10][11][12][13][14][15][16][17] On another research front, parameter uncertainties and external disturbances are two further challenges to be addressed in the design of FTC systems. [18][19][20][21][22] Fortunately, the insensitivity and robustness properties of sliding modes to certain types of disturbance and uncertainty 23,24 make it very attractive for FTC design especially in the area of flight control.…”
In this article, a robust adaptive fault-tolerant compensation control problem via sliding mode method is studied for linear systems with actuator faults, disturbances, and parameter uncertainties. Based on a matrix full-rank factorization technique of an input matrix, a new lemma is presented and proved. In terms of this lemma and the information from adaptive mechanism, actuator faults, especially outage of certain actuators, can be compensated for under an actuator redundancy assumption. Without requiring any fault detection and isolation mechanism, a sliding mode fault-tolerant controller is then designed to guarantee the asymptotic stability and disturbance attenuation, where the gain of the nonlinear unit vector term is updated automatically to compensate the effects of actuator faults. Finally, a rocket fairing structural-acoustic model is used to demonstrate the effectiveness of the proposed design method.
This paper is concerned with the fault tolerant synchronization problem for a class of complex interconnected neural networks against sensor faults. As sensor faults may lead to performance degradation or even instability of the whole network, fault tolerant control laws are designed to guarantee the controlled synchronization of the complex interconnected neural networks. On the basis of Lyapunov stability theory and adaptive schemes, three kinds of fault tolerant control laws are designed on the basis of linear matrix inequality technique. One is the passive fault tolerant control law, the other two are adaptive fault tolerant control laws. The latter two methods use the adaptive adjusting mechanism of the coupling coefficients to ensure the synchronization of the networks in the presence of sensor faults. Simulation results are given to verify the effectiveness of the proposed methods.
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