Abstract
In this paper, a method of fault diagnosis (FD) and fault-tolerant tracking control (FTTC) is investigated for non-Gaussian nonlinear stochastic distribution control (SDC) systems with missing measurements. The phenomenon of the randomly occurring missing measurements is described as a Bernoulli process. The missing measurements during transmission are compensated with the data successfully transmitted at the previous moment. The residual signal of the fault diagnosis observer is different from that of the general system. Using the integral of the error of the output probability density function (PDF) as the driving information, the system state and fault can be estimated by an adaptive fault diagnosis observer. Then, a novel fault-tolerant tracking controller is designed based on a discrete-time 2-order sliding mode to make the post-fault PDF still track the target. Two simulated examples are included to illustrate the effectiveness of the theoretical results.
Highlights
Stochastic control is an important research field in control science
Based on the aforementioned discussion, we make the first attempt to address the problem of fault diagnosis and fault-tolerant control for the non-Gaussian stochastic distribution control (SDC) system with missing measurements. e main contents and contributions of this paper can be summarized as follows: (1) In the presence of the randomly occurring missing measurements, a Lipschitz nonlinear SDC model is established. e phenomenon of the randomly occurring missing measurements is described as a Bernoulli process
It can be seen that the postfault output probability density function (PDF) can still follow the desired output PDF, leading to good faulttolerant tracking control results
Summary
Stochastic control is an important research field in control science. At present, research on Gaussian stochastic system control has achieved a lot of theoretical and practical results [1,2,3]. With the increasing demand for system security, the research on fault diagnosis and fault-tolerant control methods for non-Gaussian stochastic distribution systems has attracted more and more attention [14,15,16,17,18]. E fault diagnosis algorithm based on Complexity unknown input observer and sliding mode fault-tolerant controller are proposed in [16] for non-Gaussian uncertain stochastic distribution control systems with PDF approximation error. Based on the aforementioned discussion, we make the first attempt to address the problem of fault diagnosis and fault-tolerant control for the non-Gaussian SDC system with missing measurements.
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