Narrow Results

In this paper, smooth Chua's equation is generalized to a higher order system from a special viewpoint of interconnected systems. Simple conditions for Lagrange stability are established. And a detailed Lagrange stable region analysis is given for the canonical Chua's oscillator. In addition, a new nonlinearly coupled Chua's circuit that appeared in the recent literature is also discussed and a Lagrange stability condition is presented. Several examples are presented to illustrate the results.

In this paper, some decentralized control problems composed of two subsystems are addressed from a special perspective. First, it is pointed out that some subsystems must be unstable to stabilize the overall interconnected system in some special cases. Then, a special kind of decentralized control problem is studied. This kind of problem can be viewed as harmonic control among independent subsystems. Research results show that two unstable systems can generate a stable system through some effective cooperations. And a linear matrix inequality method is provided for decentralized controller design by using the parameter-dependent Lyapunov function method. Two examples are given to illustrate the results.

Automatic generation control (AGC) is a tool which helps the system to maintain the frequency within its targeted value by balancing the active power in the system. In this work, a novel membrane computing inspired Jaya algorithm (MCJA) is proposed and applied to tune the controller parameters for AGC of multi-area interconnected system. The proposed algorithm is designed by incorporating the concept of membrane computing in basic Jaya algorithm (JA). A two area non-reheat thermal plant is considered for AGC in this study. The objective function is designed by considering the integral errors of the frequency deviations of two areas and tie-line power deviation. Several cases with different sets of disturbances are considered to test the efficacy of the proposed controller. To validate the superior performance of the proposed controller, it is compared to particle swarm optimization (PSO), Jaya algorithm (JA) and membrane computing (MC) based controllers. Time-domain simulations are presented to depict better performance of the proposed controller. Additionally, a comparative statistical analysis is carried out to examine the robust and stable nature of the proposed algorithm.