Ton Duc Do

Adaptive PID speed control design for permanent magnet synchronous motor drives

This paper proposes an adaptive proportional-integral-derivative (PID) speed control scheme for permanent magnet synchronous motor (PMSM) drives. The proposed controller consists of three control terms: a decoupling term, a PID term, and a supervisory term. The first control term is employed to compensate for the nonlinear factors, the second term is made to automatically adjust the control gains, and the third one is designed to guarantee the system stability. Different from the offline-tuning PID controllers, the proposed adaptive controller includes adaptive tuning laws to online adjust the control gains based on the gradient descent method. Thus, it can adaptively deal with any system parameter uncertainties in reality. The proposed scheme is not only simple and easy to implement, but also it guarantees an accurate and fast speed tracking. It is proven that the control system is asymptotically stable. To confirm the effectiveness of the proposed algorithm, the comparative experiments between the proposed adaptive PID controller and the conventional PID controller are performed on the PMSM drive. Finally, it is validated that the proposed design scheme accomplishes the superior control performance (faster transient response and smaller steady-state error) compared to the conventional PID method in the presence of parameter uncertainties.

Suboptimal Control Scheme Design for Interior Permanent-Magnet Synchronous Motors: An SDRE-Based Approach

This paper designs a suboptimal speed controller as well as a suboptimal load torque observer based on state-dependent Riccati equation (SDRE) approach for interior permanent-magnet synchronous motor (IPMSM) servo systems. First, dynamic equations of the IPMSMs are transformed to a suitable form that makes an SDRE-based control technique applicable. Moreover, the maximum torque per ampere (MTPA) control is incorporated to improve the torque generation in the constant torque region. The asymptotic stabilities of the proposed controller and load torque observer are fully guaranteed through an extended linear quadratic regulator (LQR) theory. This proposed method is simple to implement because the SDRE solutions are approximated off-line. The proposed observer-based suboptimal control scheme can ensure faster dynamic response, smaller steady-state error, and more robust response than the LQR and proportional-integral (PI) controller under the system parameter variations and load torque disturbances. The effectiveness of the proposed control strategy is verified via experiment.

An Adaptive Voltage Control Strategy of Three-Phase Inverter for Stand-Alone Distributed Generation Systems

This paper proposes an adaptive control method of three-phase inverters for stand-alone distributed generation systems (DGSs). The proposed voltage controller includes two control terms: an adaptive compensating term and a stabilizing term. The adaptive compensating control term is constructed to avoid directly calculating the time derivatives of state variables. Meanwhile, the stabilizing control term is designed to asymptotically stabilize the error dynamics of the system. Also, a fourth-order optimal load current observer is proposed to reduce the number of current sensors and enhance the system reliability and cost effectiveness. The stability of the proposed voltage controller and the proposed load current observer is fully proven by using Lyapunov theory. The proposed control system can establish good voltage regulation such as fast dynamic response, small steady-state error, and low total harmonic distortion under sudden load change, unbalanced load, and nonlinear load. Finally, the validity of the proposed control strategy is verified through simulations and experiments on a prototype DGS test bed with a TMS320F28335 DSP. For a comparative study, the control scheme of feedback linearization for multi-input and multioutput is implemented, and its results are presented in this paper.

SDRE-Based Near Optimal Control System Design for PM Synchronous Motor

This paper presents a nonlinear optimal speed controller based on a state-dependent Riccati equation (SDRE) for permanent magnet synchronous motor (PMSM). An SDRE-based near optimal load torque observer is also proposed to provide the load torque information for the controller. In both designs, the stability is analytically proven, and the Taylor series method is used to find an approximate solution because the SDRE cannot be directly solved. The SDRE-based optimal controller and the observer can ensure better control performance such as no overshoot and fast transient response in speed tracking than the linear conventional controllers such as linear quadratic regulator and proportional-integral controller even under the variations of the model parameters and load torque. The proposed SDRE-based control strategy is implemented on a PMSM testbed using TMS320F28335 DSP. The simulation and experimental results are given to prove the feasibility of the proposed control scheme.

A Three-Phase Inverter for a Standalone Distributed Generation System: Adaptive Voltage Control Design and Stability Analysis

This paper proposes a robust adaptive voltage control of three-phase voltage source inverter for a distributed generation system in a standalone operation. First, the state-space model of the load-side inverter, which considers the uncertainties of system parameters, is established. The proposed adaptive voltage control technique combines an adaption control term and a state feedback control term. The former compensates for system uncertainties, while the latter forces the error dynamics to converge to zero. In addition, the proposed algorithm is easy to implement, but it is very robust to system uncertainties and sudden load disturbances. In this paper, a stability analysis is also carried out to show the robustness of the closed-loop control system. The proposed control strategy guarantees excellent voltage regulation performance (i.e., fast transient response, zero steady-state error, and low THD) under various types of loads such as balanced load, unbalanced load, and nonlinear load. The simulation and experimental results are presented under the parameter uncertainties and are compared to the performances of the corresponding nonadaptive voltage controller to validate the effectiveness of the proposed control scheme.

θ- D Approximation Technique for Nonlinear Optimal Speed Control Design of Surface-Mounted PMSM Drives

This paper proposes nonlinear optimal controller and observer schemes based on a θ-D approximation approach for surface-mounted permanent magnet synchronous motors (PMSMs). By applying the θ-D method in both the controller and observer designs, the unsolvable Hamilton-Jacobi-Bellman equations are switched to an algebraic Riccati equation and state-dependent Lyapunov equations (SDLEs). Then, through selecting the suitable coefficient matrices, the SDLEs become algebraic, so the complex matrix operation technique, i.e., the Kronecker product applied in the previous papers to solve the SDLEs is eliminated. Moreover, the proposed technique not only solves the problem of controlling the large initial states, but also avoids the excessive online computations. By utilizing a more accurate approximation method, the proposed control system achieves superior control performance (e.g., faster transient response, more robustness under the parameter uncertainties and load torque variations) compared to the state-dependent Riccati equation-based control method and conventional PI control method. The proposed observer-based control methodology is tested with an experimental setup of a PMSM servo drive using a Texas Instruments TMS320F28335 DSP. Finally, the experimental results are shown for proving the effectiveness of the proposed control approach.

Nonlinear Optimal DTC Design and Stability Analysis for Interior Permanent Magnet Synchronous Motor Drives

This paper presents a nonlinear optimal direct torque control (DTC) scheme of interior permanent magnet synchronous motors (IPMSMs) based on an offline approximation approach for electric vehicle (EV) applications. First, the DTC problem is reformulated in the stationary reference frame in order to avoid estimating the stator flux angle, which the previous DTC schemes in the rotating stator reference frame require. Thus, the proposed DTC method eliminates the Parks transformation, and consequently, it reduces the computational efforts. Particularly, since the estimated stator flux angle is not accurate in low speed range, the proposed method that does not need this information can significantly improve the control performance. Moreover, a nonlinear optimal DTC algorithm is proposed to deal with the nonlinearity of the IPMSM drive system. In this paper, a simple offline θ-D approximation technique is utilized to appropriately determine the controller gains. Via an IPMSM test bed with a TI TMS320F28335 DSP, the experimental results demonstrate the feasibility of the proposed DTC method by accomplishing better control performances (e.g., more stable in low speed region, much smaller speed and torque ripples, and faster dynamic responses) compared to the conventional proportional-integral DTC scheme under various scenarios with the existence of parameter uncertainties.

Disturbance Observer-Based Fuzzy SMC of WECSs Without Wind Speed Measurement

The main role of control system for wind turbines is tracking the optimal power via regulating the rotor speed of the generator. A high performance controller, which can deal with unmodeled dynamics, uncertainties, and external disturbance, can effectively increase the captured power from the wind. This paper focuses on designing an advanced sliding mode control (SMC) scheme for wind energy conversion systems (WECSs). As the proposed SMC scheme includes a nonlinear disturbance observer (DOB) for estimating aerodynamic torque and wind speed, there is no requirement to measure aerodynamic torque or wind speed. The proposed control scheme considers not only the uncertainties and disturbance but also the random nature of wind speed and intrinsic nonlinear behavior of the WESCs. Via designing sliding surface based on estimated information, the proposed control system can avoid disadvantages associated with the robust control techniques. To totally remove chattering as well as improving other control criteria, a fuzzy-based variable switching gain scheme is introduced. Comparative simulation results are shown to verify the effectiveness and superior performance of the proposed DOB-based fuzzy SMC scheme.

Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle

This paper proposes an image-based visual servo (IBVS) controller for the 3D translational motion of the quadrotor unmanned aerial vehicles (UAV). The main purpose of this paper is to provide asymptotic stability for vision-based tracking control of the quadrotor in the presence of uncertainty in the dynamic model of the system. The aim of the paper also includes the use of flow of image features as the velocity information to compensate for the unreliable linear velocity data measured by accelerometers. For this purpose, the mathematical model of the quadrotor is presented based on the optic flow of image features which provides the possibility of designing a velocity-free IBVS controller with considering the dynamics of the robot. The image features are defined from a suitable combination of perspective image moments without using the model of the object. This property allows the application of the proposed controller in unknown places. The controller is robust with respect to the uncertainties in the translational dynamics of the system associated with the target motion, image depth, and external disturbances. Simulation results and a comparison study are presented which demonstrate the effectiveness of the proposed approach.

Functionalized Magnetic Force Enhances Magnetic Nanoparticle Guidance: From Simulation to Crossing of the Blood–Brain Barrier In Vivo

In recent studies, we introduced the concept of functionalized magnetic force as a method to prevent nanoparticles from sticking to vessel walls caused by extensive simulation and in vitro experiments involving a Y-shaped channel. In this paper, we further investigated the effectiveness of the functionalized magnetic force with a realistic 3-D vessel through simulations. For the simulations, we considered a more realistic continuous injection of particles with different magnetic forces and frequencies. Based on the results from our simulation studies, we performed in vivo mice experiments to evaluate the effectiveness of using a functionalized magnetic force to aid magnetic nanoparticles (MNPs) in crossing the blood-brain barrier (BBB). To implement the functionalized magnetic force, we developed an electromagnetic actuator regulated by a programmable direct current power supply. Our results indicate that a functionalized magnetic field (FMF) can effectively prevent MNPs from sticking, and also guide them across the BBB. We used 770 nm fluorescent carboxyl MNPs in this paper. Following intravenous administration of MNPs into mice, we applied an external magnetic field to mediate transport of the MNPs across the BBB and into the brain. Furthermore, we evaluated the differential effects of FMFs (0.25, 0.5, and 1 Hz) and constant magnetic fields (CMFs) on the transport of MNPs across the BBB. Our results showed that an FMF is more effective than a CMF in the transport and uptake of MNPs across the BBB in mice. In particular, applying an FMF with a 3 A current and 0.5 Hz frequency mediated the greatest transport and uptake of MNPs across the BBB in mice.