Xinmin Wang

Robust Fault-Tolerant Control using on-line control re-allocation with application to aircraft

This paper investigates the design problem of robust Fault-Tolerant Control (FTC) by using on-line control re-allocation for a class of uncertain systems and its application to flight tracking control. The design procedure consists of two parts: robust fault-tolerant baseline controller design, and realization of a control re-allocation scheme. The baseline controller is obtained by an iterative LMI method, which not only stabilizes the uncertain system but also provides sufficient robustness to allow for an effective operation of the Fault Detection and Diagnosis (FDD) subsystem in the event of actuator failures. The re-allocation scheme redesigns an optimal control law without requiring reconfiguration of the baseline controller, and compensates for actuator saturation via Cascaded Generalized Inverse (CGI) method. Simulation results show the effectiveness of the proposed approach.

Research and application on improved BP neural network algorithm

As the iterations are much, and the adjustment speed is slow, the improvements are made to the standard BP neural network algorithm. The momentum term of the weight adjustment rule is improved, make the weight adjustment speed more quicker and the weight adjustment process more smoother. The simulation of a concrete example shows that the iterations of the improved BP neural network algorithm can be calculated and compared. Finally, choosing a certain type of airplane as the controlled object, the improved BP neural network algorithm is used to design the control law for control command tracking, the simulation results show that the improved BP neural network algorithm can realize quicker convergence rate and better tracking accuracy.

Fault-tolerant control for a class of uncertain systems with actuator faults

This paper is concerned with the problem of fault tolerant H8 controller design for polytopic uncertain systems against actuator faults. The type of fault mode describes as a more general and practical continuous fault model. A sufficient condition for the existence of fault tolerant controller is given by parameter-dependent Lyapunov function approach, which guarantees the closed loop system is stable and satisfies H8 performance index in both normal and fault cases. In the framework of Linear Matrix Inequality (LMI) method, an iterative algorithm is developed to reduce conservativeness of the design procedure. The effectiveness of the proposed design is shown through a flight control example.

An LMI approach to mixed H 1 /H ∞ robust fault-tolerant control design with uncertainties

This paper studies mixed H1/H∞ robust fault-tolerant control for a class of uncertain systems and its application to flight tracking control. A sufficient condition is derived by introducing some important auxiliary variables, which guarantees that the uncertain closed-loop system is robustly stable and satisfies the mixed H1/H∞ constraint in both normal and fault cases. In the framework of Linear Matrix Inequality (LMI) approach, a multi-objective optimization problem is solved with much less conservative via an iterative algorithm. Simulation results obtained with a nonlinear fighter aircraft model show the effectiveness of the proposed method.

Research on the coverage path planning of UAVs for polygon areas

This paper proposes an improved method of exact cellular decomposition to plan the coverage path in polygon area. Firstly, the problem of Coverage Path Planning (CPP) in the convex polygon area is transformed to the width calculation of the convex polygon, and the strategy of flying along the vertical direction of width is presented to reach the least number of turns. Secondly, a convex decomposition algorithm of minimum width sum based on the greedy recursive method is presented to decompose the concave area into some convex subregions. Finally, a subregion connection algorithm based on minimum traversal of undirected graph is proposed to connect the coverage paths of the subregions. The simulation shows that the proposed method is feasible and effective.

H ∞ state feedback control for UAV maneuver trajectory tracking

In this paper a trajectory tracking system for UAV is studied. The system consists of a flight control system and a guidance law. In inner loop, robust H∞ control theory is used to design the flight control system. In outer loop, the navigation control commands are produced by the deviation of the real position data of UAV and the preset flight path. The attitude commands are calculated from navigation control commands and are fed into the inner loop as input signals. Simulation results are presented to illustrate the performance of the trajectory tracking control system. The results show the effectiveness and practicability of the control method.??

A Life-detection System for Special Rescuing Robots

In this paper, a new sensitive microwave life-detection system which can be carried by special rescuing robots has been constructed. The system can be used for rescuing, anti-terrorist and law-enforcement purposes. The schematic diagram of microwave transmitting/receiving (T/R) system with automatic cancellation subsystem and signal processing system are presented. The design is recited in detail. Experiments have been conducted to verify the effectiveness of this system. The recorded signal frequency spectrums for heartbeat and respiration of a man behind an obstacle (wall) are presented

System Identification Method for Small Unmanned Helicopter Based on Improved Particle Swarm Optimization

This paper proposes a novel method for Small Unmanned Helicopter (SUH) system identification based on Improved Particle Swarm Optimization (IPSO). In the proposed IPSO, every particle will do a local search as a “self-check” before updating the global velocity and position. Then, the global best particle is created by a certain number of elitist particles in order to get a rapid rate of convergence during calculation. Thus both the diversity and convergence speed can be taken into consideration during a search. Formulated by the first principles derivation, a state-space model is built for the analysis of dynamic modes of an experimental SUH. The helicopter is equipped with an Attitude Heading Reference System (AHRS) and the corresponding data storage modules, which are used for flight test data measurement and recording. After data collection and reconstruction, the input and output data are utilized to determine the corresponding aerodynamic parameters of the state-space model. The predictive accuracy and fidelity of the identified model are verified by making a time-domain comparison between the responses from the simulation model and the responses from actual flight experiments. The results show that the characteristics of the experimental SUH can be determined accurately using the identified model and the new method can be used for SUH system identification with high efficiency and reliability.

Neural network adaptive inversion control law design for a supermaneuverable aircraft

A discrete time neural network adaptive inversion controller design for a supermaneuverable aircraft nonlinear model is presented. The singular perturbation theory is used to separate the nonlinear dynamics into fast and slow sub-systems; The dynamic inversion is applied to design the control laws for the two sub-systems separately; The neural network adaptive control is based on the dynamic inversion, and the inversion error of system is compensated by the off-line neural network. To evaluate the control performance, the maneuver generator is designed to simulate the pilot inputs. The simulation results show that the designed control law can ensure the stability of the closed-loop system, and tracks the inputs well. The design takes into account the multi input multi output nature of the model. Nonlinear simulation results are given to prove the effectiveness of the controller.

An improved LMI approach for Static Output Feedback Fault-Tolerant Control with application to flight tracking control

This paper proposes an improved Linear Matrix Inequality (LMI) approach for the synthesis of Static Output Feedback (SOF) Fault-Tolerant Control (FTC). A novel slack variable is introduced into the matrix inequalities, which provides an additional degree of freedom to compute the numerical solution. Subsequently, an improved iterative algorithm is developed to obtain an optimal SOF gain with less conservativeness. In this paper, designs of the SOF gain are shown in the framework of tracking control. The nonlinear simulations of the ADMIRE aircraft are included to demonstrate the effectiveness of the proposed method.