In this paper, a new approach for stochastic logarithmic variable structure control has been proposed to create a compromise between reaching phase duration and response rate of the stochastic suspension system. The asymptotic stability with probability one for the closed-loop suspension system has been analyzed by Lyapunov method. Some practical considerations in proving theorems are uncertain parameter variations, environmental matched disturbances, actuator degradation, stochastic environmental mismatched disturbances, which is a representative of the change in road profile with time, and unmodeled dynamics. Finally, by regulating a specific parameter, the simulation results corroborate the advantage of the proposed controller in managing and reducing the sensitivity of the closed-loop system. Also, compared with other sliding surfaces of past researches, the designed sliding variable minimizes a certain performance function and therefore provides better performance for the closed-loop system, which is also verified in the simulation results.
This paper presents the mean square consensus of multi-agent systems in the presence of actuator faults and stochastic disturbances. The dynamics of agents are considered to be heterogeneous. In addition, the information exchange between agents is modeled by a directed graph. The actuator faults are assumed as bias fault and loss of effectiveness fault. Using the adaptive control method and neural networks, a distributed controller is designed for the consensus problem of heterogeneous multi-agent systems with actuator faults and stochastic disturbances. Also, by applying Lyapunov theory, it is proved that the distributed controller guarantees the mean square consensus of heterogeneous multi-agent systems in the presence of bias faults, loss of effectiveness faults, and stochastic disturbances. Eventually, two numerical simulations are provided to show the ability of the distributed controller in the consensus problem.
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