H_(∞) state estimation for Markov jump neural networks with transition probabilities subject to the persistent dwell-time switching rule

We investigate the problem of H_(∞) state estimation for discrete-time Markov jump neural networks. The transition probabilities of the Markov chain are assumed to be piecewise time-varying, and the persistent dwell-time switching rule,as a more general switching rule, is adopted to describe this variation characteristic. Afterwards, based on the classical Lyapunov stability theory, a Lyapunov function is established, in which the information about the Markov jump feature of the system mode and the persistent dwell-time switching of the transition probabilities is considered simultaneously.Furthermore, via using the stochastic analysis method and some advanced matrix transformation techniques, some sufficient conditions are obtained such that the estimation error system is mean-square exponentially stable with an H_(∞) performance level, from which the specific form of the estimator can be obtained. Finally, the rationality and effectiveness of the obtained results are verified by a numerical example.

Design of two-layer switching rule for stabilization of switched linear systems with mismatched switching

A two-layer switching architecture and a two-layer switching rule for stabilization of switched linear control systems are proposed, under which the mismatched switching between switched systems and their candidate hybrid controllers can be allowed. In the low layer, a state-dependent switching rule with a dwell time constraint to exponentially stabilize switched linear systems is given; in the high layer, supervisory conditions on the mismatched switching frequency and the mismatched switching ratio are presented, under which the closed-loop switched system is still exponentially stable in case of the candidate controller switches delay with respect to the subsystems. Different from the traditional switching rule, the two-layer switching architecture and switching rule have robustness, which in some extend permit mismatched switching between switched subsystems and their candidate controllers.

ROBUST EXPONENTIAL STABILITY OF SWITCHED DELAY INTERCONNECTED SYSTEMS UNDER ARBITRARY SWITCHING

The problem of robust exponential stability for a class of switched nonlineardynamical systems with uncertainties and unbounded delay is addressed. On the assump-tion that the interconnected functions of the studied systems satisfy the Lipschitz condition,by resorting to vector Lyapunov approach and M-matrix theory, the sufficient conditions toensure the robust exponential stability of the switched interconnected systems under arbi-trary switching are obtained. The proposed method, which neither require the individualsubsystems to share a Common Lyapunov Function （CLF）, nor need to involve the values ofindividual Lyapunov functions at each switching time, provide a new way of thinking to studythe stability of arbitrary switching. In addition, the proposed criteria are explicit, and it isconvenient for practical applications. Finally, two numerical examples are given to illustratethe correctness and effectiveness of the proposed theories.

Time-varying output feedback H∞control for switched systems based on mixed switching

This article investigates time-varying dynamic output feedbackH∞control problem for discretetime switched systems by using a time-varying Lyapunov function.Aswitching rule that depends on available information provided by measured output and time simultaneously is designed for the system with all unstable subsystems.Conditions for l2-gain performance and time-varying controller synthesis are obtained under this switching rule.It provides a more general framework of analyzing discrete-time switched linear systems as it contains the min-switching as special cases when dwell time is not enforced.Finally,an example shows the effectiveness of the proposed method.

Interval Type-2 Fuzzy Passive Filtering for Nonlinear Singularly Perturbed PDT-Switched Systems and Its Application

The problem of designing a passive filter for nonlinear switched singularly perturbed systems with parameter uncertainties is explored in this paper.Firstly,the multiple-time-scale phenomenon is settled effectively by introducing a singular perturbation parameter in the plant.Secondly,the interval type-2 fuzzy set theory is employed where parameter uncertainties are expressed in membership functions rather than the system matrices.It is worth noting that interval type-2 fuzzy sets of the devised filter are different from the plant,which makes the design of the filter more flexible.Thirdly,the persistent dwell-time switching rule,as a kind of time-dependent switching rules,is used to manage the switchings among nonlinear singularly perturbed subsystems,and this rule is more general than dwell-time and average dwell-time switching rules.Next,sufficient conditions are provided for guaranteeing that the filtering error system is globally uniformly exponentially stable with a passive performance.Furthermore,on the basis of the linear matrix inequalities,the explicit expression of the designed filter can be obtained.Finally,a tunnel diode electronic circuit is rendered as an example to confirm the correctness and the validity of the developed filter.

Robust Exponential Stability of Switched Interval Interconnected Systems with Unbounded Delay

In this paper, a class of switched interval interconnected systems with unbounded delay were investigated. On the assumption that the interconnected functions of the systems satisfied the global Lipschitz condition, by using vector Lyapunov methods and M-matrix theory, the integrodifferential inequalities with unbounded delay were constructed. By the stability analysis of the integrodifferential inequalities, the sufficient conditions to ensure the robust exponential stability of the interval interconnected systems were obtained. By using average dwell time approach, conditions for guaranteeing the robust exponential stability of the switched delay interval interconnected systems were derived.Finally, two numerical examples were given to illustrate the correction and effectiveness of the proposed theory.

Multiple model predictive control of perching maneuver based on guardian maps

Considering the strong nonlinearity of Unmanned Aerial Vehicles(UAVs)resulting from high Angle of Attack(AOA)and fast maneuvering,we present a multi-model predictive control strategy for UAV maneuvering,which has a small amount of online calculation.Firstly,we divide the maneuver envelope of UAV into several sub-regions on the basis of the gap metric theory.A novel algorithm is then developed to determine the ploytopic model for each sub-region.According to this,a Robust Model Predictive Control based on the Idea of Comprehensive optimization(ICE-RMPC)is proposed.The control law is designed offline and optimized online to reduce the computational expense.Then,the ICE-RMPC method is applied to design the controllers of sub-regions.In addition,to guarantee the stability of whole closed-loop system,a multi-model switching control strategy based on guardian maps is put forward.Finally,the tracking performance of proposed control strategy is demonstrated by an illustrative example.