Coordinated nonlinear robust control of TCSC and excitation for multi-machine systems

An advanced nonlinear robust control scheme is proposed for multi-machine power systems equipped with thyristor-controlled series compensation (TCSC). First, a decentralized nonlinear robust control approach based on the feedback linearization and H∞ theory is introduced to eliminate the nonlinearities and interconnections of the studied system, and to attenuate the exogenous disturbances that enter the system. Then, a system model is built up, which has considered all the generators‘ and TCSC‘s dynamics, and the effects of uncertainties such as disturbances. Next, a decentralized nonlinear robust coordinated control law is developed based on this model. Simulation results on a six-machine power system show that the transient stability of the power system is obviously improved and the power transfer capacity of long distance transmission lines is enhanced regardless of fault locations and system operation points. In addition, the control law has engineering practicality since all the variables in the expression of he control strategy can be measured locally.     

Decentralized robust control of multiple static var compensators via Hamiltonian function method

Using the energy-based Hamiltonian function method, this paper investigates the decentralized robust nonlinear control of multiple static var compensators (SVCs) in multimachine multiload power systems. First, the uncertain nonlinear differential algebraic equation model is constructed for the power system. Then, the dissipative Hamiltonian realization of the system is completed by means of variable transformation and prefeedback control. Finally, based on the obtained dissipative Hamiltonian realization, a decentralized robust nonlinear controller is put forward. The proposed controller can effectively utilize the internal structure and the energy balance property of the power system. Simulation results verify the effectiveness of the control scheme.     

Predictive current control of multi-pulse flexible-topology thyristor AC-DC converter

This paper proposes a novel multi-pulse flexible-topology thyristor rectifier(FTTR) that can operate over a large voltage range while maintaining a low total harmonic distortion(THD) in the input current.The proposed multi-pulse FTTR has two operating modes:parallel mode and series mode.Irrespective of the mode in which it operates,the multi-pulse FTTR maintains the same pulses in the load current.To mitigate the harmonic injection into the AC mains,the topology-switching mechanism is then proposed.In addition,predictive current control is employed to achieve fast current response in both the transience and the transitions between modes.To verify the effectiveness of the multi-pulse FTTR as well as the control scheme,performance analysis based on an 18-pulse FTTR is investigated in detail,including fault tolerance evaluation,current THD analysis based on IEEE standard,and potential applications.Finally,a simulation model and the corresponding laboratory setup are developed.The results from both simulation and experiments demonstrate the feasibility of the proposed multi-pulse FTTR as well as the control scheme.     

Robust and Non-fragile H_∞ Control for a Class of Uncertain Jump Linear Systems

This paper describes the synthesis of robust and non-fragile H∞ state feedback controllers for a class of uncertain jump linear systems with Markovian jumping parameters and state multiplicative noises. Under the assumption of a complete access to the norm-bounds of the system uncertainties and controller gain variations, sufficient conditions on the existence of robust stochastic stability and γ-disturbance attenuation H∞ property are presented. A key feature of this scheme is that the gain matrices of controller are only based on It, the observed projection of the current regime rt.     

一类具有Markov跳跃参数的不确定线性跳跃系统鲁棒非脆弱H∞控制问题研究

This paper describes the synthesis of robust and non-fragile H∞ state feedback controllers for a class of uncertain jump linear systems with Markovian jumping parameters and state multiplicative noises. Under the assumption of a complete access to the norm-bounds of the system uncertainties and controller gain variations, sufficient conditions on the existence of robust stochastic stability and γ-disturbanee attenuation H∞ property are presented. A key feature of this scheme is that the gain matrices of controller are only based on lt, the observed projection of the current regime rt.     

A leakage current suppression technique for cascade SRAM array in 55 nm CMOS technology

Sub-threshold leakage is a major issue for low power circuits design, especially for SRAM design in SoC. Sub-threshold leakage can be decreased by scaling down supply voltage. However, this may dramatically increase the circuit delay. In this paper, we propose a novel 6 T SRAM array structure with a switch module which operates in the near threshold region to reduce the leakage current. In order to verify our proposed leakage reduction scheme, we designed and simulated an 8192 kB SRAM array based on a 16 KB single port SRAM cell memory model in 55 nm process. Several 6 T SRAM Array instances are implemented in 55-nm 1P6M CMOS technology to measure the standby current of the proposed scheme as well. With the proposed technique~ we achieved 28.3% reduction for leakage current compared to traditional 6 T SRAM array, in standby mode where gate leakage is dominant. The total penalty is 2% area increase and 1% speed reduction.     

Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model （GFHM）. Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.     

An adaptive series control for an interior permanent magnet synchronous motor with actuator compensation

An adaptive series speed control system for an interior permanent magnet synchronous motor (IPMSM) drive is presented in this paper. This control system consists of a current and a speed control loop, and it is intended to improve the drive’s speed tracking performance as well as to compensate for voltage distortions caused by non-ideal characteristics of the drive’s actuator, which is a voltage source inverter (VSI). To achieve these goals, a simple model that captures these characteristics of the VSI is developed and embedded in the motor’s electrical model. Then, based on the resulting model, an adaptive proportional-integral (PI) control for the current loops is designed, allowing for state regulation and actuator compensation. Additionally, to improve the drive’s speed tracking performance, a proportional-model-reference adaptive controller (MRAC) is designed for the speed loop. Techniques from machine learning are used for designing the MRAC to effectively address nonlinearities and uncertainties in the speed dynamic. Finally, simulation results are presented to illustrate the outstanding performance of the proposed multi-loop controller.     

基于鲁棒控制理论的多模型分层切换控制

A new hierarchical switching control system of multiple models based on robust control theory is designed for some plant with large uncertainties. The model set and controller set are designed by robust control theory and the characteristics of robust control system are taken into account. A new kind of switching index function by estimating uncertainty is designed. Furthermore,stability of the closed system is analyzed by the small gain theorem in the sense of exponentially weighted L2 norm. And simulation is done on a plant with both parameter uncertainty and unmodeled dynamics. Both theoretical analysis and simulation results show that this new hierarchical switching control system can control the plant with large uncertainties effectively and has good performance of tracking and stability.     

A nonsmooth IMC method for mechanical systems with backlash

This paper proposes a discrete-time nonsmooth internal model control （NSIMC） approach for mechanical transmission systems described by so-called sandwich system with backlash. In this method, a dynamic compensator is introduced to compensate for the effect of the input linear subsystem. Thus, the sandwich systems with backlash can be simplified as a pseudo-Hammerstein system with backlash. The corresponding NSIMC strategy is designed to control this system. The design procedure of the controller is presented based on the analysis on the robust stability by considering the model errors involved with the effect of backlash as well as the compensated error of the input linear subsystem. Moreover, as the model is switched among the different operating zones, the robust filters are proposed to guarantee the robust stability and satisfactory control performance of the system.     

Robust integral sliding mode control for uncertainsystems with multiple time delays

This paper proposes a robust integral sliding mode (RISM) manifold and the corresponding stabilization control law for uncertain systems with multiple time-varying time delays based on the techniques of linear matrix inequalities (LMI). The sufficient condition for the existence of the RISM manifold is given in terms of LMI, and then, the sliding mode control (SMC) law that can keep the system state on the RISM manifold from the initial time moment is developed. The efficiency and feasibility of the results are illustrated by a numerical example.     

Backstepping Control of Speed Sensorless Permanent Magnet Synchronous Motor Based on Slide Model Observer

This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor(PMSM) in d-q frame and its space-state equation are established. The slide model control method is used to estimate the electromotive force of PMSM under static frame, while the position of rotor and its actual speed are estimated by using phase loop lock(PLL) method. Next,using Lyapunov stability theorem, the asymptotical stability condition of the slide model observer is presented. Furthermore, based on the backstepping control theory, the PMSM rotor speed and current tracking backstepping controllers are designed, because such controllers display excellent speed tracking and anti-disturbance performance. Finally, Matlab simulation results show that the slide model observer can not only estimate the rotor position and speed of the PMSM accurately, but also ensure the asymptotical stability of the system and effective adjustment of rotor speed and current.     

Human control model in teleoperation rendezvous

This paper proposes a human control model in teleoperation rendezvous on the basis of human information processing （perception, judgment, inference, decision and response）. A predictive display model is introduced to provide the human operator with predictive information of relative motion. By use of this information, the longitudinal and lateral control models for the operator are presented based on phase plane control method and fuzzy control method, and human handling qualities are analyzed. The integration of these two models represents the human control model. Such a model can be used to simulate the control process of the human operator, which teleoperates the rendezvous with the aid of predictive display. Experiments with human in the loop are carried out based on the semi-Physical simulation system to verify this human control model. The results show that this human control model can emulate human operators＇ performance effectively, and provides an excellent way for the analysis, evaluation and design of the teleoperation rendezvous system.     

Modeling and robust discrete LQ repetitive control of electrically driven robots

Discrete linear quadratic control has been efciently applied to linear systems as an optimal control.However,a robotic system is highly nonlinear,heavily coupled and uncertain.To overcome the problem,the robotic system can be modeled as a linear discrete-time time-varying system in performing repetitive tasks.This modeling motivates us to develop an optimal repetitive control.The contribution of this paper is twofold.For the frst time,it presents discrete linear quadratic repetitive control for electrically driven robots using the mentioned model.The proposed control approach is based on the voltage control strategy.Second,uncertainty is efectively compensated by employing a robust time-delay controller.The uncertainty can include parametric uncertainty,unmodeled dynamics and external disturbances.To highlight its ability in overcoming the uncertainty,the dynamic equation of an articulated robot is introduced and used for the simulation,modeling and control purposes.Stability analysis verifes the proposed control approach and simulation results show its efectiveness.     

Guaranteed transient performance based control with input saturation for near space vehicles

This paper describes the design of guaranteed transient performance based attitude control for the near space vehicle(NSV)with control input saturation using the backstepping method.To improve the robust controllability of the NSV,the parameter adaptive method is used to tackle the integrated effect of unknown time-varying disturbance and control input saturation.Based on the backstepping technique and parameter estimated outputs,a robust attitude control scheme is proposed for the NSV with input saturation.A novel robust attitude control scheme is then proposed based on a prescribed performance bound(PPB)which characterizes the convergence rate and maximum overshoot of the attitude tracking error.The closed-loop system stability under both the developed robust attitude control schemes is proved using Lyapunov’s method and uniformly asymptotical convergence of all closed-loop signals is guaranteed.Finally,simulation results are given to show the effectiveness of both the proposed robust constrained attitude control schemes.     

Model reference adaptive impedance control for physical human-robot interaction

This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.     

Active resilient defense control against false data injection attacks in smart grids

The emerging of false data injection attacks (FDIAs) can fool the traditional detection methods by injecting false data, which has brought huge risks to the security of smart grids. For this reason, a resilient active defense control scheme based on interval observer detection is proposed in this paper to protect smart grids. The proposed active defense highlights the integration of detection and defense against FDIAs in smart girds. First, a dynamic physical grid model under FDIAs is modeled, in which model uncertainty and parameter uncertainty are taken into account. Then, an interval observer-based detection method against FDIAs is proposed, where a detection criteria using interval residual is put forward. Corresponding to the detection results, the resilient defense controller is triggered to defense the FDIAs if the system states are affected by FDIAs. Linear matrix inequality (LMI) approach is applied to design the resilient controller with H_{{\infty }} performance. The system with the resilient defense controller can be robust to FDIAs and the gain of the resilient controller has a certain gain margin. Our active resilient defense approach can be built in real time and show accurate and quick respond to the injected FDIAs. The effectiveness of the proposed defense scheme is verified by the simulation results on an IEEE 30-bus grid system.     

An adaptive control with optimal disturbances rejection

This paper provides a way to optimize the overall disturbances rejection performance of the adaptive control system in the presence of unknown external disturbances.Especially,the updatable non-empty admissible model set,which is consistent to the a priori knowledge of the plant parameter and the online measurements,is computed.With the overall system performance as the criteria,the nominal model is optimally chosen within the admissible model set.The optimal nominal model is subsequently used to synthesize the optimal closed-loop controller based on the 1 design methodology.Combining the above two aspects,an optimal adaptive control scheme is proposed.Because of the consistency of the identification criteria and control object,the adaptive control scheme proposed in this paper can achieve the overall optimal disturbances rejection performance,and the effect of the interplay between the identification and control of the adaptive system can be handled effectively.In addition,the computable optimal performance is also provided.     

Robust current and speed control of a permanent magnet synchronous motor using SMC and ADRC

A second-order ordinary differential equation model is originally constructed for the phase q current system of a permanent magnet synchronous motor (PMSM). The phase q current model contains the effect of a counter electromotive force (CEMF), which introduces nonlinearity to the system. In order to compensate the nonlinearity and system uncertainties, a traditional sliding mode controller (SMC) combined with a low-pass filter (also known as a modified SMC) is designed on the phase q current model. The low-pass filter overcomes chattering effects in control efforts, and hence improves the performance of the controller. The phase q current control system is proved to be stable using Lyapunov approach. In addition, an alternative active disturbance rejection controller (ADRC) with a reduced-order extended state observer (ESO) is applied to control the speed output of PMSM. Both SMC and ADRC are simulated on the PMSM system. The simulation results demonstrate the effectiveness of these two controllers in successfully driving the current and speed outputs to desired values despite load disturbances and system uncertainties.     

Current control for a shunt hybrid active power filter using recursive integral PI

This paper presents a current control method for a shunt hybrid active power filter （HAPF） using recursive integral PI algorithm. The method improves the performance of the HAPF system by reducing the influence of detection accuracy, time delay of instruction current calculation and phase displacement of output filter. Fuzzy logic based set-point weighing algorithm is combined in the control scheme to enhance its robustness and anti-interference ability. The proposed algorithm is easy to implement for engineering applications and easy to compute. Experiment results have verified the validity of the proposed controller. Furthermore, the proposed recursive integral PI algorithm can also be applied in the control of periodic current as in AC drivers.