This article presents an improved iterative learning direct torque control (IL-DTC) to remarkably minimize the torque ripples for a surface-mounted permanent magnet synchronous motor (SPMSM) drive. Unlike the conventional IL-DTC, the proposed IL-DTC significantly attenuates the torque ripples by effectively suppressing the repetitive disturbances using the speed and load torque compensating terms in the improved error dynamics via the improved feedback control terms and iterative learning control terms. Further, it has a simple structure and fast dynamic response due to the direct control of the torque and flux. The stability is verified through the convergence of speed errors to zero as the iteration index goes to infinity. The comparative results via MATLAB/Simulink and a prototype SPMSM test-bed with TI-TMS320F28335-DSP demonstrate the improved control performance (e.g., less torque ripples, faster transient response, smaller overshoot/undershoot, and smaller steady-state error) over the conventional IL-DTC under critical load/speed conditions with severe model parameter uncertainties.

This article investigates an observer-based optimal direct torque control (DTC) strategy for improving the transient and steady-state performance of surface-mounted permanent magnet synchronous motor (SPMSM) drives. Unlike conventional DTC techniques, the proposed method simultaneously controls speed, torque, and flux variables by employing the optimal control theory in the stationary reference frame. This helps achieving a simple structure along with good low-speed operation as the stator flux angle need not be estimated. Further, the feedforward control terms are designed to compensate for system uncertainties. Additionally, an in-depth stability analysis is presented through the Lyapunov theory. Comparative results via a real-time prototype SPMSM test-bed with TI-TMS320F28335 DSP indicate improved performance of the proposed optimal DTC compared to conventional PI DTC, nonlinear optimal DTC, and adaptive DTC, including less computational burden, less torque and flux ripples, more robustness to parameter uncertainty, and improved transient response under very low speed/load step-changes and speed reversal.

This paper presents a robust adaptive PI voltage controller (PIVC) that effectively eliminates the impact of disturbances and distorted model parameters for a three-phase constant voltage constant frequency (CVCF) inverter with an output LC filter. The proposed controller contains an adaptive control stage to enhance its tracking performance by compensating for distorted model parameters and a feedback control stage to stabilize the error dynamics to converge to zero. Unlike a conventional PIVC, the proposed adaptive method automatically updates its gains using the adaptive control stage. The stability of the proposed controller is proven by the Lyapunov stability theory. Even without information regarding the load current, the proposed adaptive PIVC achieves a fast dynamic response, small steady-state error, and low total harmonic distortion under critical load conditions. Experimental results demonstrate the efficacy of the proposed control method on a prototype three-phase CVCF inverter using a TI TMS320F28335 DSP.

This paper proposes a variable structure speed controller (VSSC) that guarantees the robust transient performance against the external disturbances and parameter uncertainties of an interior permanent magnet synchronous motor (IPMSM) drive. Unlike the conventional VSSC applied to the IPMSMs, the proposed nonlinear compensating control term not only assures the robustness against the system uncertainties, but also implements the maximum torque per ampere technique. Furthermore, the convergence and stability of the proposed VSSC are fully proven through the Lyapunov theory by introducing reasonable bounded uncertainties which determine a feasible range for the system dynamics. The effectiveness of the proposed scheme is investigated through the simulation using MATLAB/Simulink and experiment using a prototype IPMSM drive system with a TI TMS320F28335 DSP. Finally, the proposed VSSC can ensure faster and more robust transient response than the conventional proportional-integral speed controller under the dynamic load conditions including the uncertainties.

We develop an evolutionary fuzzy proportional-integral-derivative (PID) controller for a permanent magnet synchronous motor (PMSM). We first consider a fuzzy PID control design problem based on the common control engineering knowledge that good transient performances can be obtained by increasing the P and I gains and decreasing the D gain when the transient error is big. Then we give an evolutionary algorithm (EA) to autotune the control parameters of the fuzzy PID controller. We implement the proposed EA-based fuzzy PID control controller in real time on a Texas Instruments TMS320F28335 floating-point DSP. We also give simulation and experimental results to show the effectiveness of the proposed intelligent digital control system under abrupt load torque variation using a prototype PMSM.

This paper investigates a disturbance observer-based fuzzy adaptive voltage controller for three-phase pulse width modulation (PWM) inverter of a standalone distributed generation (DG) unit in the existence of system uncertainties. The proposed control law includes only a voltage control loop, which has advantages such as a simple control structure and a fast transient response due to the direct control of the output voltage. Next, a disturbance observer is presented to reduce the number of the sensors and improve the control performance. Besides, the proposed strategy is insensitive to any system uncertainties, because it does not require any accurate knowledge about system parameter and load current information. Experimental results on a prototype DG unit with a TMS320F28335 DSP are demonstrated to validate the superior performance of the proposed control scheme over the conventional proportional-derivative (PD) control method and feedback linearization control (FLC) method under sudden load disturbances, system uncertainties, and nonlinear load.

Based on sliding-mode-control theory, we develop a fuzzy controller design method for a class of uncertain time-delay systems that can be represented by Takagi-Sugeno (T-S) fuzzy models. In terms of linear-matrix inequalities (LMIs), we derive a sufficient condition for the existence of stabilizing sliding-mode controllers. We show that the sliding-surface parameter matrix can be characterized in terms of the solution of the LMI-existence condition. Our LMI condition does not require stabilization of the pair of the state and input matrices. Thus, our method can be applied to a broad class of uncertain systems. We also give an LMI-based algorithm to design a switching feedback-control strategy so that a stable sliding motion is induced in finite time. Finally, we give a numerical-design example to show that our method can be better than the previous results.

Based on the variable structure system (VSS) theory, we develop a fuzzy control system design method for a class of uncertain nonlinear multivariable systems that can be represented by a Takagi-Sugeno fuzzy model. We make the first attempt to relax the restrictive assumption that each nominal local system model shares the same input channel, which is required in the traditional VSS-based fuzzy control design methods. As the local controller we use a sliding mode controller with a switching feedback control term. In terms of linear matrix inequalities (LMIs), we derive a sufficient condition for the existence of linear sliding surfaces guaranteeing asymptotic stability of the reduced-order equivalent sliding mode dynamics. We present an LMI characterization of such sliding surfaces. We also give an LMI-based algorithm to design the switching feedback control term so that a stable sliding motion is induced in finite time. Finally, we give a numerical design example.

Based on the variable structure system theory, we develop a nonlinear fuzzy observer-controller design method for a class of uncertain nonlinear systems that can be represented by a Takagi-Sugeno fuzzy model. We use a sliding mode observer and a sliding mode controller as the local state observer and the local controller. In terms of linear matrix inequalities (LMIs), we derive sufficient conditions for the existence of the fuzzy observer and the fuzzy controller. We also derive LMI conditions for the existence of the fuzzy observer and the fuzzy controller guaranteeing the alpha-stability or generalized H2/Hinfinperformance constraints. We show that the observer and the controller can be independently designed, i.e., the separation property holds. Finally, we give simple LMI-based design algorithms, together with an example.

The authors point out that the proofs of Theorems 1 and 2 given in the above paper (Feng, 1995) are not correct and therefore the stability of the adaptive control laws proposed in the above paper is questionable at present.

This authors point out that the proofs of the main results in the above paper by Su-Leung (ibid., vol.9, no.2, p.208-14 (1993)) are not correct. And rigorous proofs through more advanced stability results are presented.>

In the above paper by Su-Leung (IEEE Trans. Robot Automat., vol.9, no.2, p.208-14 (1993)), an adaptive sliding mode control scheme for the trajectory control of robot manipulators is developed. The proof of Theorem 1 in the paper is accomplished by resorting to the Lasalle theorem. It is well known that the Lasalle theorem can be applied to either autonomous systems or periodic nonautonomous systems, but it is not applicable to general nonautonomous systems. The Lasalle theorem is not applicable to the manipulator tracking control system given in the paper because the tracking control system considered in the paper is neither an autonomous system nor a periodic nonautonomous system but it can be classified into general nonautonomous systems. Therefore, the proof of Theorem 1 in the paper is not correct.>