The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.

We address the adaptive stabilization and tracking problems for a class of output feedback canonical systems driven by Wiener noises of unknown covariance. Filtered transformation and backstepping techniques are employed in the stochastic control design. We obtain two adaptive controllers that guarantee the global stability in probability for vanishing perturbations or the input-to-state stability in probability for nonvanishing perturbations respectively. The tracking error can converge to a small residual set around the origin in the sense of mean quartic value.Index Terms-Stability in probability, stochastic adaptive stabilization, stochastic disturbance attenuation.

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This paper presents an approach of integrated guidance and control (IGC) design for interception of maneuvering targets (evaders). An IGC model with uncertainties in the pitch plane is formulated, and, by adopting a backstepping scheme, an adaptive nonlinear IGC approach is developed. Theoretical analysis shows that the design approach makes the line-of-sight (LOS) rate be input-to-state stable (ISS) with respect to target maneuvers and missile model uncertainties, and the stability of the missile dynamics can be guaranteed as well. The numerical simulation confirms the effectiveness of the proposed design approach.