Yugang Niu

Robust integral sliding mode control for uncertain stochastic systems with time-varying delay

This paper is concerned with sliding mode control for uncertain stochastic systems with time-varying delay. Both time-varying parameter uncertainties and an unknown nonlinear function may appear in the controlled system. An integral sliding surface is first constructed. Then, by means of linear matrix inequalities (LMIs), a sufficient condition is derived to guarantee the global stochastic stability of the stochastic dynamics in the specified switching surface for all admissible uncertainties. The synthesized sliding mode controller guarantees the reachability of the specified sliding surface. Finally, a simulation example is presented to illustrate the proposed method.

Brief paper: Stabilization of Markovian jump linear system over networks with random communication delay

This paper is concerned with the stabilization problem for a networked control system with Markovian characterization. We consider the case that the random communication delays exist both in the system state and in the mode signal which are modeled as a Markov chain. The resulting closed-loop system is modeled as a Markovian jump linear system with two jumping parameters, and a necessary and sufficient condition on the existence of stabilizing controllers is established. An iterative linear matrix inequality (LMI) approach is employed to calculate a mode-dependent solution. Finally, a numerical example is given to illustrate the effectiveness of the proposed design method.

Adaptive neural control for a class of nonlinearly parametric time-delay systems

In this paper, an adaptive neural controller for a class of time-delay nonlinear systems with unknown nonlinearities is proposed. Based on a wavelet neural network (WNN) online approximation model, a state feedback adaptive controller is obtained by constructing a novel integral-type Lyapunov-Krasovskii functional, which also efficiently overcomes the controller singularity problem. It is shown that the proposed method guarantees the semiglobal boundedness of all signals in the adaptive closed-loop systems. An example is provided to illustrate the application of the approach.

Brief paper: Sliding mode control for Itô stochastic systems with Markovian switching

A speed detector comprises a rotary shaft for rotation with a sewing machine, a ring-shaped permanent magnet uniformly magnetized in a direction parallel to the axis of the rotary shaft, at least one ring-shaped, internally toothed ferromagnetic member or stator and an externally toothed ferromagnetic circular member or rotor which is secured to the rotary shaft inside the stator to form a varying air gap between the opposing teeth. The permanent magnet and the two ferromagnetic members are disposed to form a closed loop magnetic circuit in which a ring-shaped coil is disposed. The air gap and hence the reluctance of the magnetic circuit changes periodically with the revolution of the rotary shaft so that a voltage is generated in the coil which varies at a frequency proportional to the operational speed of the sewing machine.

Output-feedback control design for NCSs subject to quantization and dropout

In this paper, the output-feedback control problem is considered for networked systems involving in signal quantization and data packet dropout. The states of the controlled system are unavailable and the output signals are quantized before being communicated. An estimation method is introduced to cope with the effect of random packet loss that is modelled as a Bernoulli process. The quantized measurement signals are dealt with by utilizing the sector bound method, in which the quantization error is treated as sector-bounded uncertainty. The output-feedback controller is designed which guarantees the closed-loop system is exponentially mean-square stable. The simulation example is given to illustrate the proposed method.

Robust Fuzzy Design for Nonlinear Uncertain Stochastic Systems via Sliding-Mode Control

This paper deals with the sliding-mode control (SMC) problem for nonlinear stochastic time-delay systems by means of fuzzy approach. The Takagi-Sugeno (T-S) fuzzy stochastic time-delay model with parametric uncertainties and unknown nonlinearities is presented. A sufficient condition for the exponential stability in mean square of the sliding motion is also derived. Moreover, it is shown that when the linear matrix inequalities (LMIs) with equality constraint are feasible, the designs of both sliding surface and sliding-mode controller can be easily obtained via convex optimization. A simulation example illustrating the proposed method is given.

Robust observer design for Itô stochastic time-delay systems via sliding mode control

This paper deals with the output feedback sliding mode control for Ito stochastic time-delay systems. The system states are unmeasured, and the uncertainties are unmatched. A sliding mode control scheme is proposed based on the state estimates. By utilizing a novel switching function, the derivative of the switching function is ensured to be finite variation. It is shown that the sliding mode in the estimation space can be attained in finite time. The sufficient condition for the asymptotic stability (in probability) of the overall closed-loop stochastic system is derived. Finally, a simulation example is shown to illustrate the proposed method.

Observer-based sliding mode control for nonlinear state-delayed systems

An observer-based sliding mode control problem is studied for state-delayed systems with unmeasurable states and nonlinear uncertainties. The main advantage of the proposed scheme is that it eliminates the need for state variables to be fully accessible for its control. This is possible through the use of a sliding mode controller, which performs its control by employing state estimates obtained from the sliding mode observer. By means of linear matrix inequalities, a sufficient condition is then given to ensure the asymptotic stability of the overall closed-loop state-delayed system composed of the observer dynamics and the estimation error dynamics. Furthermore, it is shown that the proposed control scheme ensures the reachability of the sliding surfaces in both the state estimate space and the estimation error space.

Adaptive sliding mode control for stochastic Markovian jumping systems with actuator degradation

This paper investigates the problem of sliding mode control for stochastic Markovian jumping systems, in which there may happen actuator degradation. By on-line estimating the loss of effectiveness of actuators, an adaptive sliding mode controller is designed such that the effect of the actuator degradation can be effectively attenuated. Besides, both the reachability of the specified sliding surfaces and the stability of sliding mode dynamics are ensured despite the actuator degradation and Markovian jumping. Finally, theoretical results are supported by numerical simulations.

Design of Sliding Mode Control Subject to Packet Losses

This technical note investigates the design of sliding mode control subject to packet losses. It is assumed that there exists a communication network in the feedback loop, and the dropout of data packet may occur. First, an estimation method is proposed to compensate the packet dropout. Subsequently, a discrete-time integral sliding surface involving dropout probability is introduced and a sliding mode controller is designed. By using the stochastic Lyapunov method, the state trajectories are shown to enter into (in mean square) a neighborhood of the specified sliding surface. Meanwhile, the stability of sliding mode dynamics is also ensured. Finally, numerical simulation example is provided.