The strong coupling between the components of a modern system and the increasing complexity of the system increase the demand for intelligent control and maintenance of the system become higher and higher. Self-healing control extends the scope of intelligent control, which is an inevitable trend in the development of intelligence for automated systems. Self-healing technology has a wide range of applications, but its theoretical system has not yet been developed. First, the characteristics, functions, definitions, and theoretical framework of self-healing control are clarified by reviewing and summarizing the research status of self-healing technology and self-healing control in various fields. Second, the differences and relationships between self-healing control and control methods, such as fault-tolerant control and adaptive control, are analyzed and discussed. Finally, the development tendency of self-healing control is summarized. The research status of self-healing technology in related fields is analyzed and summarized, and the basic framework of self-healing control is extracted to lay the foundation for the theoretical exploration of self-healing control.

This paper focuses on the guaranteed cost stability analysis of fuzzy-model-based (FMB) control systems. Representing the nonlinear plant using a Takagi–Sugeno (T–S) fuzzy model, a fuzzy controller is employed to close the feedback loop. A weighted linear quadratic cost function is considered as the cost index to measure the performance of the closed-loop fuzzy system in terms of the system states, system outputs, and control signals. The stability of the FMB control system is investigated by the Lyapunov stability theory subject to the minimization of cost index for performance realization. A membership-function-dependent approach using the piecewise-linear membership functions is employed to include the information of membership functions into the stability analysis. Membership-function-dependent stability conditions in terms of linear matrix inequalities are obtained to determine the system stability and feedback gains with the consideration of the system performance measured by the cost function. A simulation example is provided to illustrate the effectiveness and merits of the proposed approach.

The consensus in a multi-agent system (MAS) in which each agent communicates with the others over a wireless network is investigated. For the convenience of calculation, analysis and discussion, the MAS under fixed communication topology with communication constraints including random time delay, packet loss and environmental noise is transformed into an asynchronous dynamical system. Thus, the consensus control of the MAS is equivalent to the $H_{\infty }$ control of an asynchronous dynamical system. The sufficient conditions of robust exponential stability of the MAS with communication constraints are proposed and the corresponding $\gamma$ -suboptimal $H_{\infty }$ consensus controllers are designed in terms of linear matrix inequalities (LMIs). The admissible packet loss probability guaranteeing the robust exponential stability of system is also obtained. Subsequently, the corresponding simulation results are provided to demonstrate the effectiveness of the algorithms, and the impacts of time delay and packet loss on consensus of system are analysed in detail.