Adaptive Consensus Tracking for Fractional-Order Linear Time Invariant Swarm Systems

This paper presents an adaptive controller to achieve consensus tracking for the fractional-order linear time invariant swarm systems in which the matrices describing the agent dynamics and the interactive dynamics between agents are unknown. This controller consists of two parts: an adaptive stabilizer and an adaptive tracker. The adaptive stabilizer guarantees the asymptotic swarm stability of the considered swarm system. Also, the adaptive tracker enforces the system agents to track a desired trajectory while achieving consensus. Numerical simulation results are presented to show the effectiveness of the proposed controller.

A FRACTIONAL ORDER UNIVERSAL HIGH GAIN ADAPTIVE STABILIZER

In this paper, a fractional order universal high gain adaptive stabilizer is proposed which guarantees the Lp stability of fractional order multiple–input and multiple–output (MIMO) systems with finite control effort. The boundedness of the control gain for the fractional order universal adaptive strategy is discussed for fractional order MIMO systems, and an upper bound of the control gain is presented for fractional order single-input and single-output (SISO) systems. Some advantages of the discussed fractional order universal adaptive stabilizer are demonstrated in numerical simulations, such as the overshoots of system outputs can be efficiently reduced by decreasing the fractional order of the universal adaptive stabilizer without significantly increasing the system gains.

Design of Globally Adaptive Stabilizer for Underwater Navigator

In this paper, the problem of adaptive stabilization of an underwater navigator with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method and parameter projection techniques, a direct adaptive controller is designed to complete the globally adaptive stability of the navigator. Simulations are provided to illustrate the effectiveness of our proposed method.