Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates

In this paper, the problem of continuous gain-scheduled fault detection (FD) is studied for a class of stochastic nonlinear systems which possesses partially known jump rates. Initially, by using gradient linearization approach, the nonlinear stochastic system is described by a series of linear jump models at some selected working points. Subsequently, observer-based residual generator is constructed for each jump linear system. Then, a new observer-design method is proposed for each re-constructed system to design H_∞ observers that minimize the influences of the disturbances, and to formulate a new performance index that increase the sensitivity to faults. Finally, continuous gain-scheduled approach is employed to design continuous FD observers on the whole nonlinear stochastic system. Simulation example is given to show the effectiveness and potential of the developed techniques.     

考虑微观结构噪声与跳跃影响的波动建模

现有的金融高频数据研究,并未充分考虑微观结构噪声对波动建模和预测的影响.以非参数化方法为理论框架,基于高频数据,采用适当方法分离出波动中的微观结构噪声成份,构建了新的跳跃方差和连续样本路径方差,将已实现波动分解为连续样本路径方差、跳跃方差和微观结构噪声方差.同时考虑微观结构噪声和跳跃对波动的影响,对HAR-RV-CJ模型进行改进,提出了HAR-RV-N-CJ模型和LHAR-RV-N-CJ模型.通过上证综指高频数据进行实证,结果表明新模型在模型拟合和预测方面均优于HAR-RV-CJ模型.     

Development of fuzzy state controller and its application to a hydraulic position servo

By combining control theory and fuzzy set theory, a new kind of state controller is proposed. Full order feedback and membership functions, which utilize the experience of experts, are used in the design of the state controller which we call a fuzzy state controller. Hydraulic position servos with a nonsymmetrical cylinder are commonly used in industry. This kind of system is nonlinear in nature and generally difficult to control. For different ending position, moving direction, strokes, and load the system dynamics is totally different. Once the above-mentioned parameters of the system are known, it is relatively straightforward to tune the gains of state controller to obtain good dynamic response. But when these parameters change, especially in case of the load, using the same gains will cause overshoot or even loss of system stability. Adaptive control is not applicable in this case due to the complexity of the algorithm, its rate of convergence, and the fast response characteristic of the system. The fuzzy state controller has been successfully applied to a hydraulic position servo. The system shows excellent robustness against variations of system parameters.     

Dissipative constraint-based control design for singular semi-Markovian jump systems using state decomposition approach

This paper proposes a unified control design for a class of singular semi-Markovian jump systems with a time-varying delay in the state vector by employing the state decomposition approach and dissipative theory. To begin, the addressed system is decomposed into differential–algebraic form with new state vectors, from which a mode-dependent augmented Lyapunov–Krasovskii functional is constructed. The desired stochastic admissibility and dissipative conditions are then obtained, where the auxiliary function-based integral inequality, the generalized free-weighting-matrix approach and the augmented zero equality approach are used in the derivation to achieve less conservative results. In accordance with these conditions, a relationship for determining the mode-dependent gain parameters of the proposed state feedback control is given. As a result, the theoretical findings of this paper lead to better results than some previously published ones, as demonstrated by four numerical examples.     

Dynamic compensator design and H∞ admissibilization for delayed singular jump systems via Moore–Penrose generalized inversion technique

This paper is intended to study output feedback-based $H_{\infty }$ admissibilization for singular Markovian jump time-varying delays systems via Moore–Penrose generalized inversion technique. The main aim is to design singular dynamic compensator based on output feedback control idea and Moore–Penrose generalized inversion technique, such that the time-varying delays singular Markovian jump system realizes not only stochastic stability, but also regularity, impulse-freeness (which are collectively known as stochastic admissibility) and achieves $H_{\infty }$ interference level. Time delay-dependent and mode-dependent L–K candidate functional is constructed, Moore–Penrose generalized inversion technique is utilized, then the improved $H_{\infty }$ admissibilization conditions for singular Markovian jump time-varying delays systems are provided by virtue of linear matrix inequalities. Simulation examples including a direct current motor-controlled inverted pendulum system are employed to confirm the effectiveness and practicability of the addressed singular dynamic compensation technique.     

Dynamic event-triggered control for discrete-time nonlinear Markov jump systems using policy iteration-based adaptive dynamic programming

This paper investigates a dynamic event-triggered optimal control problem of discrete-time (DT) nonlinear Markov jump systems (MJSs) via exploring policy iteration (PI) adaptive dynamic programming (ADP) algorithms. The performance index function (PIF) defined in each subsystem is updated by utilizing an online PI algorithm, and the corresponding control policy is derived via solving the optimal PIF. Then, we adopt neural network (NN) techniques, including an actor network and a critic network, to estimate the iterative PIF and control policy. Moreover, the designed dynamic event-triggered mechanism (DETM) is employed to avoid wasting additional resources when the estimated iterative control policy is updated. Finally, based on the Lyapunov difference method, it is proved that the system stability and the convergence of all signals can be guaranteed under the developed control scheme. A simulation example for DT nonlinear MJSs with two system modes is presented to demonstrate the feasibility of the control design scheme.     

Self-contained two-layer shallow-water theory of strong internal bores

We show that interfacial gravity waves comprising strong hydraulic jumps (bores) can be described by a two-layer hydrostatic shallow-water (SW) approximation without invoking additional front conditions. The theory is based on a new SW momentum equation which is derived in locally conservative form containing a free parameter α. This parameter, which defines the relative contribution of each layer to the pressure at the interface, affects only hydraulic jumps but not continuous waves. The Rankine–Hugoniot jump conditions for the momentum and mass conservation equations are found to be mathematically equivalent to the classical front conditions, which were previously thought to be outside the scope of SW approximation. Dimensional arguments suggest that α depends on the density ratio. For nearly equal densities, both layers are expected to affect interfacial pressure with approximately equal weight coefficients, which corresponds to $\alpha \approx 0$. The front propagation velocity for $\alpha =0$ agrees well with experimental and numerical results in a wide range of bore strengths. A remarkably better agreement with high-accuracy numerical results is achieved by $\alpha =\sqrt{5}-2$, which yields the largest height that a stable gravity current can have.