H∞ filtering of Markov jump linear systems with general transition probabilities and output quantization

A deviation correction strategy based on particle filtering and improved model predictive control for vertical drilling

This paper is concerned with the correction of trajectory deviation in vertical drilling. Note that the accuracy of correction control will be reduced significantly by measurement and process noises, which finally leads to that the inclination angle exceeds beyond a tolerable limit. To deal with such noises and take into account practical constraints, a deviation correction strategy is developed for vertical drilling based on particle filtering and improved model predictive control in this paper. Firstly, the distributions and characters of the measurement and process noises in vertical drilling process are analyzed, and their approximate prior probability distributions are obtained. Based on the analysis, the structure of the deviation correction strategy is provided, including a particle filter and an improved model predictive controller which introduces a flexible constraint and an adjustable weight. The particle filter is effective to reject the measurement noises, and the improved model predictive controller plays an important role in achieving a small inclination of the drilling trajectory. Finally, two groups of simulations are carried out to illustrate the effectiveness of the proposed correction strategy.

Integrated H∞ filtering bumpless transfer control for switched linear systems

The integrated H_∞ filtering bumpless transfer control problem for switched linear systems is studied in this paper. The target is to attain the H_∞ filtering property of the switched linear systems via switchings, while reducing the control bumps induced by switchings. First, a novel description of the bumpless transfer performance is presented, quantifying the suppression level on the control bumps from both relative and absolute viewpoints. Then, a switching logic, a collection of filters and filter-based controllers are jointly designed to attain this target. Further, a criterion which ensures not only the H_∞ filtering property but also the bumpless transfer performance is developed. Finally, an application on a turbofan engine control system model is offered, verifying the efficiency of the developed integrated H_∞ filtering bumpless transfer control strategy.

Robust fault-tolerant control for networked control systems subject to random delays via static-output feedback

This paper focuses on the problem of fault-tolerant controller (FTC) design for uncertain networked control systems (NCSs) with random delays and actuator faults. A new fault model is proposed to represent more class of actuator faults. More precisely, the NCSs with random delays and the possible actuator faults are modeled as a Markovian jump system (MJS) with incomplete transition probabilities (TPs) and then LMI-based sufficient conditions are derived to ensure the stochastic stability of the closed-loop system. The sufficient conditions are constructed to synthesize the mode-dependent static-output feedback (SOF) control laws. Feasibility and reliability of the proposed FTC against actuator faults are indicated through simulation results.

Event-triggered H∞ filtering of discrete-time switched linear systems

In this paper, the event-triggered H_∞ filtering problem for discrete-time switched linear systems is addressed. The filter and the system are connected via a communication network, and the transmitted information of system output and switching signal is determined by an event-triggered transmission scheme, which contains system mode dependent parameters. Consequently, the asynchronous switching between the filter and the system occurs, and the filtering error system is modeled as a switched system with augmented switching signal by using the merging switching signal technique. Then, by the multiple Lyapunov function method, a new sufficient condition is obtained such that the filtering error system is exponentially asymptotically stable and satisfies the weighted H_∞ performance. Finally, the design method for the filter and event-triggered parameters is proposed by solving a set of linear matrix inequalities. Numerical simulations illustrate the effectiveness of the proposed approach.

Sliding mode control for a two-joint coupling nonlinear system based on extended state observer

A two-joint coupling nonlinear system driven by pneumatic artificial muscles is introduced in this paper. A sliding mode controller with extended state observer is proposed to cope with nonlinearities and disturbances for the two-joint coupling nonlinear system. In addition, convergence of the extended state observer is presented and stability analysis of the closed-loop system is also demonstrated with the sliding mode controller. Lastly, some experiments are carried out to show the reality effectiveness of the proposed method.

New results on H∞ filtering for Markov jump systems with uncertain transition rates

In this paper, we study the H_∞ filtering problem for a class of continuous-time Markov jump systems with time-varying uncertainties in transition rates, in which the uncertain transition rates are assumed to be affine parameter-dependent uncertainty models. By converting the affine parameter-dependent uncertainty models for transition rates into time-varying polytopic ones and using the Lyapunov function approach, a sufficient condition on the existence of an H_∞ filter is obtained in terms of a parameter-dependent matrix inequality. Also, the parameter-dependent matrix inequality is converted into a set of parameter-free linear matrix inequalities which can be solved numerically. Illustrative examples are given to demonstrate the effectiveness and advantages of the approach.

Event-based finite-time state estimation for Markovian jump systems with quantizations and randomly occurring nonlinear perturbations

This paper is concerned with finite-time state estimation for Markovian jump systems with quantizations and randomly occurring nonlinearities under event-triggered scheme. The event triggered scheme and the quantization effects are used to reduce the data transmission and ease the network bandwidth burden. The randomly occurring nonlinearities are taken into account, which are governed by a Bernoulli distributed stochastic sequence. Based on stochastic analysis and linear matrix inequality techniques, sufficient conditions of stochastic finite-time boundedness and stochastic H_∞ finite-time boundedness are firstly derived for the existence of the desired estimator. Then, the explicit expression of the gain of the desired estimator are developed in terms of a set of linear matrix inequalities. Finally, a numerical example is employed to demonstrate the usefulness of the theoretical results.