Adaptive control of bifurcation and chaos in a time-delayed system

In this paper,the stabilization of a continuous time-delayed system is considered.To control the bifurcation and chaos in a time-delayed system,a parameter perturbation control and a hybrid control are proposed.Then,to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes,the adaptive control idea is introduced,i.e.,the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws,respectively.The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem.The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods.They have the advantages of increased stability,adaptability to the changes of the system parameters,control cost saving,and simplicity.Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods.A comparison of the two adaptive control methods is also made in an experimental study.

Adaptive Iterative Learning Control for Nonlinearly Parameterized Systems with Unknown Time-varying Delay and Unknown Control Direction

This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method.

Robust Load Frequency Control for Isolated Microgrids Based on Double-loop Compensation

Frequency is an important indicator for the oper-ation of microgrids.However,the randomness and uncertainty of renewable energy and load variability may lead to frequency undulation.So,a robust load frequency control(LFC)is pro-posed for isolated wind-diesel microgrids considering time delay and parameter uncertainty.The control strategy can suppress frequency fuctuation and optimize frequency dynamic response.First,the double compensation loop,including feedforward control and integral sliding mode control(SMC),is devised to provide anti-disturbance compensation for the diesel generator system and ameliorate the frequency stability of independent microgrids.Secondly,a dynamic fuzzy controller,composed of wind speed and load demand,is designed to provide real-time response reference power for doubly fed induction generator systems(DFIGs),which can promote the effective participation of a wind turbine system for frequency regulation.Then,the proportional differential(PD)parameters of a dynamic fuzzy controller and the frequency adjustment compensation of DFIGs can be obtained by using a particle swarm optimization(PSO)algorithm.Thirdly,load demand is an important index of the robust dynamic load frequency control method;the radial basis function(RBF)neural network observer(NNO)based on the LFC model is presented to obtain more accurate load deviations and improve the control precision of LFC.The performance of the proposed LFC method is tested under different operation cases.Index Terms-Load frequency control,microgrid,neural network observer,sliding mode,time delay and parameter uncertainty.