Applied Mechanics and Materials Vols. 284-287

Abstract: This paper proposes a robust control design based-on integral sliding-mode and H2–norm performance criterion to handle a class of time-varying systems with perturbations including non-linearities and disturbances. The stabilization problems for such systems are studied: integral slid-ing-mode is designated to completely nullify the matched perturbations and, in the meantime, elim-inate the reaching phase to the sliding surface, while H2–norm is a robust linear control measured for system on the sliding surface. In addition to the integral sliding mode control, the contribution of the paper is to implement a parameter-dependent Lyapunov function for H2–norm robust linear control that the overall designed system is less conservative for the system with both matched and unmatched perturbations.

Abstract: In this paper, the robust exponential stability problem is investigated for a class of neutral systems with interval time-varying delay and nonlinear perturbations. Based on the Lyapunov-Krasovskii functionals in conjunction with Leibniz-Newton formula, novel LMI-based delay-dependent and delay-independent criteria are proposed to guarantee the robust exponential stability with a convergence rate for our considered systems. Finally, numerical examples are illustrated to show the improved results from using the proposed method.

Abstract: Stabilization and tracking control of nonlinear uncertain underactuated systems are always challenging problems because underacturated systems have fewer independent control actuators than degrees of freedom to be controlled. For a class of second order underactuated mechanical systems, a robust finite time control strategy is developed in this paper. The robust finite time controller is to drive the tracking error to be zero at the fixed final time. In fact, finite time convergence implies nonsmooth or non-Lipschitz continuous autonomous systems with nonuniqueness of solution. In order to prove the stability, we present a generalized Lyapunov stability proof for the second order underactuated mechanical system. By utilizing a Lyapunov stability theorem, we can achieve finite time tracking of desired reference signals for underactuated systems, which is subject to both external disturbances and system uncertainties. The proposed control scheme is demonstrated by actual experiments on a Furuta pendulum system. Based on the experiment results, the finite time convergence of system errors can be assured.

Abstract: Electro-Hydraulic pump-controlled servo systems that have high energy-efficiency can serve as energy-saving system. This paper aims to investigate the servo performance of the electro-hydraulic pump-controlled systems driven by an AC servo motor with variable rotational speed. A constant displacement axial piston pump is used in this research. Thus, the new hydraulic pump-controlled system with an AC motor servo and a constant displacement axial piston pump is investigated for position control of hydraulic servo machines. For that, this paper also develops the control strategy, sign-distance fuzzy sliding mode control, which can simplify the fuzzy rule base through the sliding surface. The developed high response variable rotational speed pump-controlled systems controlled by SD-FSMC are implemented and verified experimentally for positioning control in different stroke and loading conditions.

Abstract: Based on the sliding mode control (SMC) technique, a design of the sliding surface for the dual-excited and steam-valving control of the synchronous generators with matched and mismatched perturbations is proposed in this paper. By utilizing some constant gains designed in the sliding surface function, not only are the mismatched perturbations overcomed during the sliding mode, but also the property of asymptotical stability of the rotor angle and the voltage is achieved at the same time. Simulations have demonstrated that the control scheme is robust against the disturbances.

Abstract: This work concerns the development of a sliding-mode tracking controller for a precision positioning stage. This stage is supported by cross roller guides, therefore, one of the main disturbances during dynamic motion is the friction force. In order to overcome the effect of friction, an integral sliding-mode controller with friction disturbance estimation scheme is designed to control the motion of the stage. Comparing with conventional PID controllers, the experimental results show that with this controller the tracking errors can be reduced significantly.

Abstract: This paper presents a new switching control scheme for an active magnetic bearing (AMB) system using self-tuning fuzzy proportional-integral-derivative (PID) control. The research process consists of three stages. First, four types of self-tuning fuzzy PID-type controllers (FPIDCs) consisting of two most commonly used fuzzy inference systems: Mamdani and Takagi-Sugeno types, and two efficient parameter adaptive methods: function tuner and relative rate observer, are used to control a highly nonlinear AMB system, respectively. Hence, there are two kinds of FPIDCs can be obtained by comparing experimental results of these tests: one has the fastest transient response and the other has the minimum steady-state error. Next, the switching-type self-tuning FPIDC is proposed by combining the two kinds of FPIDCs. Namely, the AMB system is dominated by the scheme with the fastest transient response when the rotor is at rest and by the one with the best steady-state performance when the rotor is in rotation. Finally, experimental results demonstrate that the proposed switching-type self-tuning FPIDC performs better overall performance than the other self-tuning FPIDCs, particularly when controlling an AMB system.

Abstract: This paper presents an adaptive pseudo reduced-order Takagi-Sugeno (T-S) fuzzy flux estimator for the induction motor direct field orientation control system. The estimator gain can be obtained by solving a set of linear matrix inequalities (LMIs) to estimate the rotor flux accurately. It is well known that, because of changes in temperature, variations of stator and rotor resistances affect the accuracy of rotor flux estimation. To resolve this problem, a cerebellar model articulation proportional integral controller (CMAPIC) is proposed to estimate the stator and rotor resistances during temperature variations. These estimated quantities, including stator and rotor resistances, are taken as the T-S fuzzy flux estimator inputs, so that the flux estimation is uninfluenced by these parameter variations. Thus the estimators enhance the robustness of the system. Moreover, this work uses a cerebellar model articulation controller to estimate the rotor speed, which is fed back to the adaptive supervisory fuzzy cerebellar model articulation speed controller (ASFCMAC) to achieve the speed sensor-less control.

Abstract: A controller synthesis algorithm is developed in this paper. The algorithm employs the genetic algorithm for parameter optimization and Taguchi method for the planning of trails in applying the genetic algorithms. The resulting two-phase algorithm explores the orthogonal array in Taguchi method to conduct a series of experiments so that key parameters pertaining to the control factors, noise factors, and quality factors can be determined. In the first phase, a matrix-type experiment is conducted to determine the configuration for parameter optimization. The second phase then applies parameter optimization method to determine the controller parameter that leads to robust performance. The combined two-phase approach is effective and efficient in controller synthesis. The proposed algorithm is applied to a control-design benchmark problem. The resulting design is shown to have a superior performance to other existing controllers.

Abstract: A recurrent wavelet neural network (RWNN) controller is proposed to control output voltages for a permanent magnet synchronous motor (PMSM) direct drive three-phase permanent magnet synchronous generator (PMSG) system at stand-alone power application in this paper. First, the field-oriented mechanism is implemented for the control of the PMSG system. Then, a rectifier (AC/DC power converter) and an inverter (DC/AC power converter) are developed to convert the electric power generated by a three-phase PMSG system. Moreover, two online trained RWNNs using backpropagation learning algorithm are developed as the regulating controllers for both the DC-link voltage of the rectifier and the AC line voltage of the inverter. Finally, to show the effectiveness of the proposed controller, comparative studies with PI controller are demonstrated by experimental results.