Showing papers by "Kang-Zhi Liu published in 2014"
TL;DR: The proposed MPC-based approach reduces the torque ripple with a small number of switching operations in inverters by comparing the proposed approach with conventional DTC.
Abstract: The direct torque control (DTC) of ac motors leads to a faster torque response with a small number of switching operations in inverters when compared with a conventional approach such as vector control. DTC exhibits a hybrid nature in the sense that the system is composed of continuous variables of torque and flux and involves discrete switching in the inverter. The output of the inverter is limited to the finite discrete values at each instance of sampling. Model predictive control (MPC) is applied to the system so that an optimal switching sequence is derived subject to the given constraints. The proposed MPC-based approach reduces the torque ripple with a small number of switching operations. The effectiveness of the proposed MPDTC approach is verified through simulations and experiments by comparing the proposed approach with conventional DTC.
24 citations
TL;DR: This paper addresses the stabilization problem of linear systems subject to input saturation with a new approach which involves a partial differential matrix inequality (PDMI) and reveals that any linear observer can be used to realize the output feedback stabilization.
8 citations
14 Mar 2014
TL;DR: A designing state estimator method in discrete-time systems with the quantized output is proposed and the effectiveness of the proposed method is illustrated with experiments.
Abstract: Recently, by development of communication techniques, control via communication is expected to take important part in networked control systems (NCSs) and so on. The main problem of the NCSs is that data are transmitted via a communication channel which has a constraint of capacity by converting a continuous signal into a discrete signal by using quantizer to compress the amount of information. Therefore, the discrete signal has a margin of error called quantization error. In the quantized feedback control systems, we use an observer to estimate a state if the state is not available, and use the estimated state in feedback control. In such cases, the system may be unstable and degraded the performance since the states estimation is not performed properly due to the quantization error. Hence, an state estimator must be designed with taking into account the effect of quantization error. In this paper, we propose a designing state estimator method in discrete-time systems with the quantized output. The effectiveness of the proposed method is illustrated with experiments.
7 citations
TL;DR: In this article, a nonlinear current control configuration with hysteresis compensation using the adaptive multilayer neural network is proposed for the next-generation fine stage of the wafer scanner.
Abstract: The next-generation fine stage of the wafer scanner needs a suitable actuator to meet the requirements of high speed, high acceleration, and high precision. The voice coil actuator is no longer the best choice because of its large size and the heat dissipation is difficult to solve. The reluctance actuator can provide a big force based on a unique property of small volume and low current, making it a very suitable candidate. But the strong nonlinearity such as the hysteresis between the current and force limits the reluctance actuator applications in nanometer positioning. This paper proposes a nonlinear current control configuration with hysteresis compensation using the adaptive multilayer neural network. Simulation results show that the hysteresis compensator is effective in overcoming the hysteresis and is promising in precision control applications.
4 citations
14 Mar 2014
TL;DR: A model predictive control (MPC) based approach for NCS is proposed and the delay is described as stochastic models in order to taking them into account for generating input to actuator.
Abstract: In recent years, networked control system (NCS) has been receiving much attention due to shared networkc channels with improved communication device. In NCS, data-dropout and delay are unavoidable. In practical systems, some constraints have to be considered independent of communication. A desired performance in NCS may not be achieved if the closed-loop is not designed without taking consideration of the data-dropout and delay. Therefore, the delay and/or the data-dropout in the network have to be considered in designing NCS. This paper proposes a model predictive control (MPC) based approach for NCS. The delay is described as stochastic models in order to taking them into account for generating input to actuator. The effectiveness of the proposed approach is verified by applying to an inverted pendulum.
3 citations
14 Mar 2014
TL;DR: In this article, a quantized feedback control system with a variable discrete quantizer is proposed, where both input and a parameter of the quantizer are optimized online with the help of model predictive control (MPC).
Abstract: Networked control systems (NCSs) have been receiving much attention in order to improve control performance in the field of in remote robot operation, surgery and some operations. In the NCSs, it is important to quantize necessary signals for control over a limited network channel for the sake of prevention from transmitting a large amount of data. This paper addresses a quantized feedback control system with a variable discrete quantizer. In the system, both input and a parameter of the quantizer are optimized online with the help of model predictive control (MPC). In our approach, constraints on input/output, the parameter of the quantizer and other physical and/or logical constraints can be explicitly taken into account while guaranteeing optimality. The optimization problem is reduced to a mixed integer quadratic programming. Experimental results are demonstrated to verify the effectiveness of the proposed method.
3 citations
TL;DR: In this article, a nonlinear control method is proposed for the stage having paired reluctance linear actuator with hysteresis using the direct adaptive neural network, which is used as a learning machine of nonlinearity.
Abstract: Reluctance linear actuator, which has a unique property of small volume, low current and can produce great force, is a very promising actuator for the fine stage of the next-generation lithographic scanner. But the strong nonlinearities including the hysteresis, between the current and output force limits the reluctance linear actuator applications in nanometer positioning. In this paper, a new nonlinear control method is proposed for the stage having paired reluctance linear actuator with hysteresis using the direct adaptive neural network, which is used as a learning machine of nonlinearity. The feature of this method lies in that the nonlinear compensator in conventional methods, which computed the current reference from that of the input and output force is not used. This naturally overcomes the robustness issue with respect to parameter uncertainty. Simulation results show that the proposed method is effective in overcoming the nonlinearity between the input current and output force and promising in precision stage control.
01 Oct 2014
TL;DR: This paper addresses an extension of the quantized feedback control system in order to consider the tracking control performance as well as the stabilization of the system.
Abstract: Networked control systems (NCSs) have been receiving much attention in the field of remote robot operation, surgery and some operations. In the NCSs, data needs to be quantized since it is transmitted over a limited network channel. In earlier works, we considered an NCS with a variable discrete quantizer. In the system, both input and a parameter of the quantizer are optimized online with the help of model predictive control (MPC) so that the system is stabilized. However, the method is not applied to the tracking control, directly. This paper addresses an extension of the quantized feedback control system in order to consider the tracking control performance as well as the stabilization of the system. In the system, the center of the quantization is considered as a variable to be optimized. The optimization problem is reduced to a mixed integer quadratic programming so that the tracking control can be realized online. Experimental results are demonstrated to verify the effectiveness of the proposed method.
18 May 2014
TL;DR: This paper presents a model predictive-based current control for PMSMs that can be strictly treated as a discrete voltage vector so that the output saturation of the inverter is avoided.
Abstract: This paper presents a model predictive-based current control for PMSMs. In our approach, a reference voltage to an inverter can be strictly treated as a discrete voltage vector so that the output saturation of the inverter is avoided. Various constraints can be also taken into consideration in our approach. Both tolerance ranges for control variables and number of switching operations are incorporated into a single objective function in order to consider a trade-off between current ripple and switching operations. The effectiveness of the proposed method is verified through simulations and experiments.
28 Jul 2014
TL;DR: A robust control method is proposed for an engine bench system where the resonance frequency and disturbance frequency overlap and the disturbance torque is amplified and the shaft has a danger of rupture.
Abstract: An engine bench is a two-mass-spring system consisting of a dynamo and an engine connected by a shaft. The shaft has a property of nonlinear spring, and the two-mass-spring system is subject to periodic disturbance stemming from the combustion of engine. This paper focuses on the case where the resonance frequency and disturbance frequency overlap. In such case, the disturbance torque is amplified and the shaft has a danger of rupture. We propose a robust control method for this system. An H
∞
controller is designed and its effectiveness is verified through analysis of the frequency response of closed loop system and time-domain simulations.