Fujiang Jin

A control scheme for a class of uncertain nonlinear systems with state delay and actuator dead-zone

The control problem of a class of uncertain nonlinear systems which is with state delay and actuator dead-zone together is studied in this paper. The controller is derived step by step through a backstepping procedure, where an adaptive fuzzy logic system is employed to approximate the unknown functions encountered. By introducing hyperbolic tangent functions, both the effects of state delay and the actuator dead-zone are compensated by the controller. Different from the existing results for unknown nonlinear delay systems, the proposed scheme can guarantee the desired control objective in the presence of actuator dead-zone. However, unlike the existing dead-zone compensation strategy where the dead-zone is treated as the sum of a linear function and a bounded disturbance-like term, this scheme reduces the bound of the latter by appropriate decomposing. Thus the additional robust control effort used to deal with the disturbance-like term can be saved effectively. It is proved in theory that the closed-loop system is semi-globally uniformly ultimately stable and its output can track the reference signal as closely as possible. Finally, a simulation example is employed to demonstrate the effectiveness of the control scheme.

Control of unknown affine nonlinear systems with symmetric dead-zone

A control method based on adaptive fuzzy approximation is proposed in this paper to realize the tracking control problem for a class of symmetric dead-zone nonlinear systems. By decomposing the dynamics of dead-zone, a control law is derived by imbedding fuzzy approximators into backstepping steps. The proposed method is applicable to high-order nonlinear systems, and the controlled systems are not required to satisfy the matching conditions. The adopted fuzzy approximators are nonlinearly parameterized, which do not require fuzzy basis functions completely known. In order to obtain the adaptive laws, Taylor series expansion is employed to separate the nonlinear unknown parameters. And then the adaptive laws are designed on the basis of Lyapunov Stability. Besides, the adaptive laws are designed to adjust the norm of the unknown parameters, which can reduce the on-line computation burden and improve the control speed. It is proved that all closed-loop signals are guaranteed to converge to a small neighborhood of origin, and the output can track the reference signal with a given precision. An example is given to show the effectiveness of the method.

Steady-state characteristics analysis of induction motor under the condition of asymmetrical faults in stator

In order to separate study the steady-state characteristics of the induction motor when the resistance or inductance asymmetrical fault occurs in the stator winding, a set of differential equations are firstly respectively established to describe the characteristics of the motor under the condition of resistance and inductance asymmetrical fault in stator winding with the application of multi-loop theory. And then the expression of the steady-state current in each circuit of the motor with stator asymmetrical fault was set precisely, which can be substituted into the voltage equations of each circuit subsequently. After these equations were expanded, the differential equations can be converted into a set of linear ones by the principle that coefficients of the corresponding items on both sides are equal to each other. Thus the steady-state current in each circuit, as well as the electromagnetic torque of the motor, can be obtained by solving linear equations mentioned above. Finally, simulations experiments are conducted on a squirrel-cage induction motor to verify the correctness of the whole analysis, also to analyze the influence of resistance and inductance asymmetry ratio on the operation of the motor.

Adaptive tracking control for a class of unknown nonlinear time-delay systems using nonlinearly parameterized fuzzy approximators

A class of strict-feedback nonlinear systems with unknown system functions and time delays are considered in this paper. Nonlinearly parameterized fuzzy systems with adaptive mechanism are employed to approximate the unknown functions in a backstepping procedure. By using Taylor series expansion, the parameters are separated successfully, then adaptive laws can be designed to update them on-line. The advantage of such a design is that the basis functions of the fuzzy approximators are not require known before design. The proposed controller can guarantee the closed-loop stability and good tracking performance.

Backstepping design for unknown nonlinear delay systems using nonlinearly parameterized fuzzy approximator

A class of nonlinear delay systems with unknown dynamics is studied in this paper, and a controller is proposed by employing backstepping design method, which can make the output of the controlled system track the given reference signal. Fuzzy logic systems are used to approximate the unknown nonlinear functions in the design, and both the fuzzy weights and the parameters in the fuzzy basis functions are adjusted online by adaptive mechanism, so that the fuzzy basis functions do not need to be known beforehand. By choosing integrated Lyapunov functions, it is proved that the proposed controller can guarantee the closed-loop stability and the desired output tracking. Furthermore, simulation results demonstrate the correctness of the conclusion.

Backstepping control of unknown nonlinear systems against actuator faults using nonlinearly parameterized fuzzy approximators

In this paper, the problem of fault-tolerant control (FTC) for a class of uncertain nonlinear systems is studied. A novel FTC scheme is proposed to deal with both lock-in-place and loss of effectiveness faults of actuators. By employing fuzzy approximation and on-line adaptive updating, the proposed control scheme can tolerate the faults without detection and diagnosis mechanism. It is proved in theory that the FTC scheme can guarantee the closed-loop stability and desired output tracking performance in spite of all kinds of the faults and external disturbances. A simulation example is also included to show the effectiveness of the scheme.

Soft-sensing method of color measurement in batch dyeing process of knitted cotton with reactive dyes

For the on-line measurement of the fabric color in the batch dyeing process, a novel method is proposed based on soft-sensor. In this method, the concentrations of the dyestuff in a jet dyeing machine are selected as the soft sensors inputs, and the the fabric color is the output. A nonlinear model, which relates the absorbance with the concentrations of the dyestuff, is obtained based on the experiments and the regression analysis method. Using this nonlinear model, the concentrations of the dyestuff during the dyeing process are measured by the extended Kalman filter(EKF). Further, the soft-sensing model is proposed to predict the fabric color by the obtained concentrations of the dyestuff. The numerical results for the soft-sensing method of color measurement in the dyeing process of knitted cotton using reactive dyes are compared to the experimental results, leading to good agreement between theory and experiment. This demonstrates that this soft-sensing model is able to predict the fabric color in the textile industries for the batch dyeing process.

Fault-tolerant control of uncertain MIMO nonlinear systems: An adaptive fuzzy approach

This paper studies the problem of fault-tolerant control of uncertain multiple-input multiple-output (MIMO) nonlinear systems, and presents a fault-tolerant control scheme to deal with both lock-in-place and loss of effectiveness faults of actuators. A class of MIMO nonlinear systems with the block-triangular structure and unknown nonlinearities is considered. By combining the adaptive fuzzy approach with the backstepping technique, the controllers and the adaptive laws for the fault-tolerant scheme are derived. Though there are unknown and time-varying faults in the actuators, the derived controllers can guarantee the stability and desired output tracking of the closed-loop system without the help of fault detection and diagnosis. A simulation example is given to show the effectiveness of the control scheme.

Robust output tracking control of nonlinear systems against actuator faults

The problem of robust output tracking of nonlinear systems is considered in this paper. The systems under consideration are subjected to actuator faults. The main difficulty in system design is that not only the fault information but also the function of the system model are unknown. Based on the universal approximation property of fuzzy system, a novel control scheme is proposed to guarantee the stability and desired output tracking performance of the closed-loop system, though there are unknown nonlinearities and actuator faults. Different from existing works, the fuzzy systems used to approximate the unknown functions are nonlinearly parameterized, which removes the restriction that the fuzzy basis functions must be well known before control design. The effectiveness of the proposed control scheme is verified by a simulation example.