Cheng-Chew Lim

State estimation and sliding mode control for semi-Markovian jump systems with mismatched uncertainties

This paper is concerned with the state estimation and sliding mode control problems for phase-type semi-Markovian jump systems. Using a supplementary variable technique and a plant transformation, a finite phase-type semi-Markov process has been transformed into a finite Markov chain, which is called its associated Markov chain. As a result, phase-type semi-Markovian jump systems can be equivalently expressed as its associated Markovian jump systems. A sliding surface is then constructed and a sliding mode controller is synthesized to ensure that the associated Markovian jump systems satisfy the reaching condition. Moreover, an observer-based sliding mode control problem is investigated. Sufficient conditions are established for the solvability of the desired observer. Two numerical examples are presented to show the effectiveness of the proposed design techniques.

Segmentation of the face and hands in sign language video sequences using color and motion cues

We present a hand and face segmentation methodology using color and motion cues for the content-based representation of sign language video sequences. The methodology consists of three stages: skin-color segmentation; change detection; face and hand segmentation mask generation. In skin-color segmentation, a universal color-model is derived and image pixels are classified as skin or nonskin based on their Mahalanobis distance. We derive a segmentation threshold for the classifier. The aim of change detection is to localize moving objects in a video sequences. The change detection technique is based on the F test and block-based motion estimation. Finally, the results from skin-color segmentation and change detection are analyzed to segment the face and hands. The performance of the algorithm is illustrated by simulations carried out on standard test sequences.

Quantized Control Design for Cognitive Radio Networks Modeled as Nonlinear Semi-Markovian Jump Systems

This paper is concerned with the quantized control design problem for a class of semi-Markovian jump systems with repeated scalar nonlinearities. A semi-Markovian system of this kind has been transformed into an associated Markovian system via a supplementary variable technique and a plant transformation. A sufficient condition for associated Markovian jump systems is developed. This condition guarantees that the corresponding closed-loop systems are stochastically stable and have a prescribed H∞ performance. The existence conditions for full- and reduced-order dynamic output feedback controllers are proposed, and the cone complementarity linearization procedure is employed to cast the controller design problem into a sequential minimization one, which can be solved efficiently with existing optimization techniques. Finally, an application to cognitive-radio systems demonstrates the efficiency of the new design method developed.

Neural Network-Based Passive Filtering for Delayed Neutral-Type Semi-Markovian Jump Systems

This paper investigates the problem of exponential passive filtering for a class of stochastic neutral-type neural networks with both semi-Markovian jump parameters and mixed time delays. Our aim is to estimate the states by designing a Luenberger-type observer, such that the filter error dynamics are mean-square exponentially stable with an expected decay rate and an attenuation level. Sufficient conditions for the existence of passive filters are obtained, and a convex optimization algorithm for the filter design is given. In addition, a cone complementarity linearization procedure is employed to cast the nonconvex feasibility problem into a sequential minimization problem, which can be readily solved by the existing optimization techniques. Numerical examples are given to demonstrate the effectiveness of the proposed techniques.

Network-Based Event-Triggered Control for Singular Systems With Quantizations

This paper investigates the problem of event-triggered H∞ control for a networked singular system with both state and input subject to quantizations. First, a discrete event-triggered scheme, which activates only at each sampling instance, is presented. Next, two new sector bound conditions of quantizers are proposed to provide a more intuitive stability analysis and controller design. Then, network conditions, quantizations, and the event-triggered scheme are modeled as a time-delay system. With this model, the criteria are derived for H∞ performance analysis, and codesigning methods are developed for the event trigger and the quantized state feedback controller. An inverted pendulum controlled through the network is given to demonstrate the effectiveness and potential of the new design techniques.

Adaptive Neural Fault-Tolerant Control of a 3-DOF Model Helicopter System

In this paper, an adaptive neural fault-tolerant control scheme is proposed for the three degrees of freedom model helicopter, subject to system uncertainties, unknown external disturbances, and actuator faults. To tackle system uncertainty and nonlinear actuator faults, a neural network disturbance observer is developed based on the radial basis function neural network. The unknown external disturbance and the unknown neural network approximation errors are treated as a compound disturbance that is estimated by another nonlinear disturbance observer. A disturbance observer-based adaptive neural fault-tolerant control scheme is then developed to track the desired system output in the presence of system uncertainty, external disturbance, and actuator faults. The stability of the whole closed-loop system is analyzed using the Lyapunov method, which guarantees the convergence of all closed-loop signals. Finally, the simulation results are presented to illustrate the effectiveness of the new control design techniques.

Robust Constrained Control for MIMO Nonlinear Systems Based on Disturbance Observer

In this note, a robust constrained control scheme is proposed for multi-input and multi-output (MIMO) cascade nonlinear systems with unknown external disturbance and input saturation. To efficiently observe unknown external disturbance, a novel sliding mode disturbance observer (SMDO) with finite time convergence performance is presented. A robust constrained control scheme is developed for MIMO nonlinear systems based on backstepping control techniques and the disturbance estimate of the SMDO. With the first-order sliding mode differentiator introduced to compute the derivatives of virtual control laws, the computational burden in backstepping control is reduced for a MIMO cascade nonlinear system. Numerical simulation results are presented to show the effectiveness of the proposed robust constrained control scheme.

Fault Detection Filtering for Nonhomogeneous Markovian Jump Systems via a Fuzzy Approach

This paper investigates the problem of the fault detection filter design for nonhomogeneous Markovian jump systems by a Takagi–Sugeno fuzzy approach. Attention is focused on the construction of a fault detection filter to ensure the estimation error dynamic stochastically stable, and the prescribed performance requirement can be satisfied. The designed fuzzy model-based fault detection filter can guarantee the sensitivity of the residual signal to faults and the robustness of the external disturbances. By using the cone complementarity linearization algorithm, the existence conditions for the design of fault detection filters are provided. Meanwhile, the error between the residual signal and the fault signal is made as small as possible. Finally, a practical application is given to illustrate the effectiveness of the proposed technique.

Novel Neural Networks-Based Fault Tolerant Control Scheme With Fault Alarm

In this paper, the problem of adaptive active fault-tolerant control for a class of nonlinear systems with unknown actuator fault is investigated. The actuator fault is assumed to have no traditional affine appearance of the system state variables and control input. The useful property of the basis function of the radial basis function neural network (NN), which will be used in the design of the fault tolerant controller, is explored. Based on the analysis of the design of normal and passive fault tolerant controllers, by using the implicit function theorem, a novel NN-based active fault-tolerant control scheme with fault alarm is proposed. Comparing with results in the literature, the fault-tolerant control scheme can minimize the time delay between fault occurrence and accommodation that is called the time delay due to fault diagnosis, and reduce the adverse effect on system performance. In addition, the FTC scheme has the advantages of a passive fault-tolerant control scheme as well as the traditional active fault-tolerant control schemes properties. Furthermore, the fault-tolerant control scheme requires no additional fault detection and isolation model which is necessary in the traditional active fault-tolerant control scheme. Finally, simulation results are presented to demonstrate the efficiency of the developed techniques.

Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System

This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.