Search

This paper presents a novel delay-dependent dissipative control synthesis technique with a state-feedback structure for input-delayed suspension systems using a tighter bounding technique. By more accurately estimating the derivative of the LKF, we focus on reducing the conservatism of the state-feedback control synthesis for suspension systems with strict design constraints. New LMI conditions for a desired state-feedback controller are developed by employing a generalized free-weighting-matrix (GFWM) method. By solving the LMIs, the proposed controller for active suspension systems is obtained such that the closed-loop systems have asymptotic stability with guaranteed $(\mathcal {Q},\mathcal {S},\mathcal {R})$ -dissipative performances, while also satisfying the design constraint conditions. Numerical simulations effectively confirm the benefits of the proposed control synthesis technique for the design of state-feedback control.

In this paper, a new method is proposed for the real-time estimation of the full parameters of a permanent magnet synchronous motor (PMSM) that is based on the stator current ripple model. By introducing the stator current ripple model together with the known two state equations for the $d$ - and $q$ -axes currents, we resolve the rank deficiency problem, thus enabling real-time full parameter estimation even in the steady state. A signal processing technique for removing adverse effects from noises and uncertainties existing in the stator current ripple measurement is also presented. The efficacy of the proposed method is verified by simulation on a 15-kW PMSM, and both the proposed and conventional methods are compared.

This study presents an advanced current control of permanent magnet synchronous motor (PMSM) aiming for improved transient performance over a wide speed range. While the conventional current control scheme based on proportional-integral controllers often shows a degraded transient performance in high-speed operation where the control inputs are almost saturated, the proposed scheme uses a proportional current controller in combination with a disturbance observer, by which the current error converges to zero in an exponential way. This desirable property preserves the transient performance even under the input constraint. A systematic way to determine the optimal control gain considering parameter uncertainties is also provided. A simulation study verifies the efficacy of the proposed scheme using a 20 kW PMSM model in comparison with the conventional current control scheme.

In this study, a fast and accurate optimal torque control scheme for interior permanent magnet synchronous motors (IPMSMs) is presented, which enables computing the optimal current references for maximum torque per ampere (MTPA) and flux weakening (FW) operations. Instead of analytically solving the optimal torque control problem that involves computationally expensive quartic equations, a numerical optimization technique is introduced to simplify the problem and solve it in iterations with reduced computation burden. Under the reasonable assumption of a slowly varying torque reference, linearizing the IPMSM torque equation helps to derive the solutions for the MTPA and FW operations in simpler forms. Unlike conventional numerical methods, convergence to the exact solution is ensured. A simulation using a 7.5-kW IPMSM model in MATLAB verifies the effectiveness of the proposed method by comparing it with the conventional methods in terms of solution accuracy and computational efficiency.

This study proposes a proportional-type position controller for the DC motor with the performance recovery property. The proposed method has two merits. First, the disturbance observers are designed so as to make up for the model-plant mismatches. Second, based on the classical cascade structure, a proportional-type position controller is developed via the feedback linearizing technique with the guarantees of the performance recovery and offset-free properties. The efficacy of the proposed method is evaluated by the simulations using the Simscape toolbox and level-2 S-function in MATLAB/Simulink.

This paper describes an offset-free model predictive control (MPC) algorithm using a disturbance observer (DOB) to control the active/reactive powers of a three-phase AC/DC converter. The DOB is designed to estimate the unknown disturbances of the AC/DC converter following the standard Luenberger observer design procedure. The proposed MPC minimizes a one-step-ahead cost index penalizing the predicted tracking error by performing a simple membership test without any use of numerical methods. A systematic way for choosing the weights of the cost index, which guarantees the global stability of the closed-loop system, is proposed. Use of the DOB eliminates the offset tracking errors in the real implementation.

This paper presents an one-step ahead model predictive control (MPC) to control the output voltage and the power factor of a three phase AC/DC converter, considering the nonlinearity of the converter model. The proposed MPC minimizes an one-step ahead cost function by performing a simple membership test without any use of numerical methods at each time step and it ensures the global convergence in the presence of input constraints. The cost index is designed so that the output voltage tracking and maximum power factor regulation are obtained by minimizing it at each time step. Moreover, the use of the proportional-and-integral (PI) controller in the outer-loop is made to remove the offset error. It is shown that the closed-loop performance is satisfactory under the load resistance changes through the simulations using PSIM software.

In this paper, we propose a simple model predictive controller (MPC) combined with a disturbance observer (DOB) for regulating the torque of a permanent magnet synchronous motor (PMSM) without steady state error. Specifically, a DOB is devised for estimating the unknown disturbance caused by a plant-model mismatch using a Luenberger observer. The proposed MPC minimizes a cost function at each time step in the receding horizon manner. It is possible to obtain the online optimal solutions without relying on a numeric algorithm using the specific property of the input matrix of PMSM. Thereafter, it is proven that the proposed MPC scheme ensures global asymptotic stability of the closed-loop system in the presence of input constraints and that the integrator in the DOB eliminates any offset error. Through the experiments, it is shown that the proposed MPC scheme provides satisfactory torque control performance.

This paper presents a dual-loop inverter voltage control strategy for uninterruptible power supply (UPS) utilizing an one-step ahead model predictive control in the inner-loop. The proposed MPC optimizes the cost function of the error state through a simple online membership test; any numerical method is not necessary. Moreover, any off-line optimization is not required. It is shown that the proposed MPC makes the closed-loop system globally asymptotically stable in the presence of input constraints. Following the conventional dual-loop strategy, the PI controller is used in the outer-loop to regulate the output voltage. The effectiveness of the proposed MPC scheme is experimentally shown under an unexpected load changes.

This paper proposes a simple model predictive inner-loop current controller for regulating the output voltage of a three-phase voltage-source AC/DC converter under the two-loop strategy. The solution of the MPC can be given analytically by minimizing an energy function of the tracking error, and its global stability is guaranteed in the presence of the input constraint. For the outer-loop, a PI controller is utilized to regulate the output voltage without offset error. The simulation results show that the current and the output voltage regulation are achieved in a satisfactory manner despite the load and the parameter changes.

Using a nonlinear converter model, a numerical on-line optimization free model predictive control (MPC) is proposed for a converter to regulate the capacitor voltage. The MPC is given analytically by minimizing an energy function of the tracking error with its global exponential stability under input constraints. The outer-loop PI controller is adopted to eliminate an offset errors caused by a plant-model mismatch.

In this paper, a two-loop control scheme is presented for the direct torque control (DTC) of the permanent magnet synchronous motor (PMSM). The contribution of this paper is twofold. The Drst is to propose an inner-loop model predictive controller (MPC) with the stability analysis. SpeciDcally, the inner-loop MPC is given analytically by minimizing an cost function of the tracking error, and its global asymptotic stability is ensured under the inherent input constraint. In the second, the outer-loop PI controllers are adopted to eliminate the steady state error. The simulation results present that the torque of PMSM shapely tracks the reference in a satisfactory manner while the d-axis current is rapidly regulated to zero.

Hybrid photovoltaic (HPV) cells were developed onto a flexible microlens array (MLA) in order to improve their efficiencies. The active layer of the developed HPVs was composed of blend of organic PV materials and heavy metal-free CuInS 2 quantum dots. The polymer MLA, which was replicated from isotropically etched quartz, was employed for a flexible substrate simultaneously dispersing the incident sunlight into the active layer efficiently. In illumination test, the developed HPVs integrated with the MLA exhibited highly enhanced J SC of 6.07 mA/cm2 and corresponding PCE of 1.45 %, which was 30 % improved efficiency than that of the control PVs.

Nonlinear adaptive speed and d-axis current control schemes based on adaptive state feedback and backstepping technique are proposed for a permanent magnet synchronous motor(PMSM). In the controller design, adaptive state feedback and backstepping control approach using the parameter dependant Lyapunov function is adopted to derive the control scheme, which is robust to the all parameter uncertainties and the load torque disturbance, force the whole control system to have the output strictly passivity. Moreover, because of using a parameter dependant Lyapunov function, proposed controller has no singularity problem. Simulation results clearly show that the proposed control scheme can regulate the speed and the d-axis current reference under all parameter uncertainties and the load torque disturbance.