Conventional Linear Control Research Articles

Optimal Power Management in Wireless Control Systems

This paper considers the control of a linear plant when plant state information is being transmitted from a sensor to the controller over a wireless fading channel. The power allocated to these transmissions determines the probability of successful packet reception and is allowed to adapt online to both channel conditions and plant state. The goal is to design plant input and transmit power policies that minimize an infinite horizon cost combining power expenses and the conventional linear quadratic regulator control cost. Since plant inputs and transmit powers are in general coupled, a restricted information structure is imposed allowing them to be designed separately. Under this information structure the standard LQR controller becomes the optimal plant input policy, while the optimal communication policy follows a Markov decision process minimizing transmit power at the sensor and state estimation error at the controller. The optimal power adaptation to channel and plant states is examined qualitatively for general forward error correcting codes. In the particular case of capacity achieving codes event-triggered policies are recovered, where the sensor decides whether to transmit or not based on plant and channel conditions. Approximate dynamic programming is employed to derive a family of tractable suboptimal communication policies exhibiting the same qualitative features as the optimal one. The performance of our suboptimal policies is shown in simulations and is contrasted to other simple transmission policies.

Nonlinear Model Predictive Control for DFIG-based Wind Power Generation

摘要: 在现代风力发电厂中, 需对双馈式风力发电机(Doubly fed induction generator, DFIG)进行有效控制来确保高效率和高负荷跟踪能力. 风力发电厂包含很多不确定因素和非线性因素, 传统的线性控制器往往难以奏效. 本文针对双馈式风力发电机的功率控制提出了一种非线性模型预测控制方法. 文中的目标函数考虑了现实约束下的经济因素和设定值跟踪能力, 同时降低机组磨损和机械疲劳. 预测值可基于输入输出反馈线性化(Input-output feedback linearization, IOFL)策略来计算. 仿真实验结果验证了所构造的非线性模型预测控制器的有效性. 关键词: 双馈发电机 / 输入输出反馈线性化 / 预测控制

Study on the Control Algorithm of Two-Stage DC-DC Converter for Electric Vehicles

The fast response, high efficiency, and good reliability are very important characteristics to electric vehicles (EVs) dc/dc converters. Two-stage dc-dc converter is a kind of dc-dc topologies that can offer those characteristics to EVs. Presently, nonlinear control is an active area of research in the field of the control algorithm of dc-dc converters. However, very few papers research on two-stage converter for EVs. In this paper, a fixed switching frequency sliding mode (FSFSM) controller and double-integral sliding mode (DISM) controller for two-stage dc-dc converter are proposed. And a conventional linear control (lag) is chosen as the comparison. The performances of the proposed FSFSM controller are compared with those obtained by the lag controller. In consequence, the satisfactory simulation and experiment results show that the FSFSM controller is capable of offering good large-signal operations with fast dynamical responses to the converter. At last, some other simulation results are presented to prove that the DISM controller is a promising method for the converter to eliminate the steady-state error.

Finite-time convergent continuous control design based on sliding mode algorithms with application to a hydraulic drive

Sliding modes impose strong robustness toward parametric plant uncertainties and disturbances and provide for accurate tracking performance in control systems. However, in physical systems the application of sliding modes may give rise to undesirable chattering of the control signal due to actuator dynamics, possible excitation of unmodelled dynamics and structural resonant modes of load systems, etc. This may be avoided by application of smoothing functions imposing boundary layers on the control constraint, or by carrying out the design in relation to the control derivative. However, such boundary layers introduce additional design parameters and actuator dynamics may not allow the desired control accuracy to be reached. In this paper continuous controllers are proposed, with the designs taking their offset in some well-known sliding controllers. The proposed controllers preserve the finite-time convergence properties known from sliding control while at the same time avoiding control chattering, however, on the cost of robustness. Experimental results confirm the announced properties when applied to a hydraulic valve-cylinder drive, and demonstrates superior performance over conventional linear controllers.

Stochastic synchronization of complex network via a novel adaptive nonlinear controller

In this paper, a novel adaptive nonlinear controller is designed to achieve stochastic synchronization of complex networks. We find that this novel adaptive nonlinear controller is less conservative and may be more widely used than the traditional adaptive linear controller. By using the properties of Weiner process, the stochastic synchronization of complex networks with stochastic perturbation via the proposed novel adaptive nonlinear controller can be achieved. Experimental tests demonstrate the superior performance of this novel adaptive nonlinear controller as compared to a conventional adaptive linear controller.

Sliding Mode Control of Anti-Lock Braking System

Many different control methods for Anti-lock Braking System (ABS) have been developed. In this paper, a new control algorithm is proposed for ABS based on sliding mode control algorithm, which represents the nonlinear characteristics of external interferences. The proposed sliding mode controller guarantees a highly robust performance against large variations in the system parameters and disturbances. Simulation results show that the proposed method has advantages compared with conventional linear controllers.

Current control loop of 3-phase grid-connected inverter

This paper presents a comparative study of current control loop in 3-phase inverter which is used to control the active and reactive output power. Generally, current control loop, power control loop and phase lock-loop are the conventional parameters that can be found in an inverter system controlled by the conventional linear control type, for instance proportional (P), integral (I) and derivative (D). If the grid remains stable throughout the day, PID control can be use. However variation of magnitude, frequency, voltage dips, transient, and other related power quality issues occur in a 3-phase grid often affects the control loop. This paper aims to provide an overall review on the available current control techniques used in grid connected system.

Simplified Feedback Linearization Control of Three-Phase Photovoltaic Inverter With an LCL Filter

The conventional grid-connected photovoltaic (PV) inverter is controlled by a dual-loop control strategy in synchronous reference frame, and the controllers are designed for steady-state operating point based on the small signal model by neglecting the high-order and coupling terms. However, in an LCL filter, the coupling terms are complicated due to the dq transformation which will affect the dynamic performance. In this paper, an innovative simplified feedback linearization (SFL) control strategy is proposed for the PV inverter with the LCL filter, which offers satisfactory performance, particularly, in decoupling the control system, improving the dynamic performance, and enhancing the adaptability. Furthermore, the SFL controllers are simpler than the high-order tracking controllers used in conventional feedback linearization control. The detailed simplification process and accurate transfer functions for SFL control strategy have been presented, and the performance comparisons between the proposed SFL control strategy and the classical dual-loop method are carried out to show the characteristics of the proposed control algorithm. Finally, a laboratory prototype of a 150-kW PV inverter with the LCL filter has been implemented to test the feasibility and effectiveness of the proposed strategy. The proposed SFL control strategy can also be applied to a higher order system or other power converters.

A Family of Three-Switch Three-State Single-Phase $Z$-Source Inverters

This paper proposes a new family of three-switch three-state single-phase Z-source inverters (TSTS-ZSIs) that can be classified into two groups, boost-based TSTS-ZSI and buck–boost-based TSTS-ZSI, according to the step-up circuit. All of the topologies have the merits of buck–boost capability and low voltage stress, and some of them have the feature of dual grounding. In addition, the step-up in dc side and inversion in ac side is completely decoupled in the proposed topologies. In terms of a linear voltage gain, the conventional linear control methods can be used, which makes the control system very simple. The operating principles of the two types of topologies are described, respectively, and the comprehensive comparison between them is provided. Finally, the theoretical analysis and comparison of the proposed topologies are verified by the simulation and experimental results.

Vertical stabilization of ITER plasma using explicit model predictive control

In this work we explore advanced control algorithms for the vertical stabilization of plasma in the ITER tokamak for the case where a combination of ohmic in-vessel and superconducting poloidal actuators is used for effective response to disturbances subject to thermal constraints. We apply constrained linear-quadratic optimal control, which is a hybrid between conventional linear quadratic optimal control and model predictive control (MPC). We discuss the issues of practical implementation in the form of explicit MPC, which allows application to fast processes by avoiding the use of on-line optimization.

Velocity control of a secondary controlled closed-loop hydrostatic transmission system using an adaptive fuzzy sliding mode controller

A secondary-controlled hydrostatic transmission system (SC-HST), which considered being an energy-saving system, can recuperate most of the lost vehicle kinetic energy in decelerating and braking time and it shows advantage in fuel economy improvement of vehicle. Almost secondary control units (SCU) in SC-HST inherently contain nonlinear characteristics such as dead-zone input. Therefore, it is difficult to obtain precise position or velocity control by conventional linear controllers. This problem limits the application of SC-HST in industry and mobile vehicle. This paper gives a description of SC-HST and proposes an adaptive fuzzy sliding mode controller (AFSMC) for velocity control of SCU. Experiments were carried out in the condition of disturbance load by using both the proposed controller and PID controller for the comparison and evaluation of the effectiveness of the proposed controller. The experimental results showed that the proposed controller was excellent from the standpoints of performance and stability for the velocity control of SC-HST.

Guidance system for agricultural tractor with four wheel steering

In a typical automatic guidance system for agricultural machines, the guidance system controls only one degree of freedom; either the steering angle of the front wheels of the tractor or other steering equipment is used for steering. In a tractor with the multiple degrees of freedom, like four wheel steering, the guidance system may use both the degrees of freedom for path tracking. However, the implement connected has to support the additional degrees of freedom; otherwise kinematic constraints are addressed. This paper presents a path tracking algorithm for four wheel steered agricultural tractor that is designed to be autonomous. The path tracking algorithm utilizes the kinematic and dynamical model of the vehicle, dynamic prediction and linear control laws to steer both front and rear axles of the tractor. The kinematic model is used to separate the two-times-time control problem into two single-input single-output problems. Conventional linear controllers are used for feedback control together with feedforward part. The guidance system uses real time kinematic GPS receiver for global positioning and additional sensors to measure the attitude of the vehicle. The developed path tracking system was tested in an agricultural field with a mounted seeder; by sowing 2.4 ha winter wheat. The results show that in straight swaths the lateral tracking error was less than 0.05m and the angular tracking error less than 1 degree. The results show also that during the field experiment, the GPS positioning signal was within the quality limits 15% of time that caused number of interrupts for continuous autonomous drive. The longest continous period of valid signal was eighteen minutes while the average of continuous driving was five minutes.

Offset-Free Predictive Control for Variable Speed Wind Turbines

Wind turbine aerodynamics is known as a nonlinear and stochastic system; hence, a high-performance requirement of tight optimal regime tracking is beyond the capability of the conventional linear PI controller. On the other hand, the linear model of the nonlinear wind turbine aerodynamics at a specific operating point produces a mismatch between plant and model which is the main reason for reference tracking offset seen in a conventional predictive controller. This paper presents a new predictive control approach for variable speed wind turbines in order to guarantee maximum power captured under the rated wind speed. The proposed algorithm, offset-free predictive control (OF-PC), has been exploited to provide zero error tracking of the nonstationary optimal speed trajectory. The control scheme attempts to add additional output disturbance signals to the linear presentation of wind turbine aerodynamics together with an appropriate observer design to lump the plant-model mismatches and/or unmodeled disturbances. The simulation and experiment results demonstrate the effectiveness of the control method.

D02 状態量の無限級数を用いたAcrobotの近似線形化制御(M-OS14-1:非線形制御理論とその応用I,M-OS14 非線形制御理論とその応用,「海を越え,国を越え,世代を超えて!」)

This paper deals with an approximate linearization control for the Acrobot using a novel linearization coordinate. The linearization coordinate is systematically determined by solving two first order linear partial differential equations and obtained in analytical form, as an infinite series of the state variables. The resulting system with the approximate linearization control posseses a larger basin of attraction comparing with that of the conventional linear control based on linearly approximated model. The advantage of the proposed control is clearly shown in numerical simulations but experimental results also shows their difference.

VGT and EGR Control of Common-Rail Diesel Engines Using an Artificial Neural Network

In diesel engines, variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR) systems are used to increase engine specific power and reduce NOx emissions, respectively. Because the dynamics of both the VGT and EGR are highly nonlinear and coupled to each other, better performance may be attained by substituting nonlinear multiple input, multiple output (MIMO) controllers for the existing conventional lookup table-based linear controllers. This paper presents a coordinated VGT/EGR control system for common-rail direct injection diesel engines. The objective of the control system is to track target mass air flow and target intake manifold pressure by adjusting the EGR and VGT actuator positions. We designed a nonlinear MIMO control system using a neural control scheme that adopts an indirect adaptive control approach. The neural control system is comprised of a neural network identifier, which mimics the target air system, and a neural network controller, which calculates the actuator positions. The proposed control system has been validated with engine experiments under transient operating conditions. It was demonstrated from experimental results that the proposed control system shows improved target value tracking performance over conventional VGT/EGR control system.

LMI-based Sliding Mode Speed Tracking Control Design for Surface-mounted Permanent Magnet Synchronous Motors

For precisely regulating the speed of a permanent magnet synchronous motor system with unknown load torque disturbance and disturbance inputs, an LMI-based sliding mode control scheme is proposed in this paper. After a brief review of the PMSM mathematical model, the sliding mode control law is designed in terms of linear matrix inequalities (LMIs). By adding an extended observer which estimates the unknown load torque, the proposed speed tracking controller can guarantee a good control performance. The stability of the proposed control system is proven through the reachability condition and an approximate method to implement the chattering reduction is also presented. The proposed control algorithm is implemented by using a digital signal processor (DSP) TMS320F28335. The simulation and experimental results verify that the proposed methodology achieves a more robust performance and a faster dynamic response than the conventional linear PI control method in the presence of PMSM parameter uncertainties and unknown external noises.

Sliding-Mode Input–Output Linearization Controller for the DC/DC ZVS CLL-T Resonant Converter

A sliding-mode input–output linearization controller for the dc/dc zero-voltage switching (ZVS) CLL-T resonant converter is presented. The proposed controller significantly improves the transient response and disturbance rejection of the converter while preserving the closed-loop stability. An averaged large-signal dynamic model of the converter operating with a novel discrete ZVS modulation technique is developed and used as starting point for the controller design. Since the model derivation process does not include small signal approximations, it can be used for large-signal analysis, providing accurate predictions of the converter dynamic behavior. The combination of the proposed controller and modulation technique provides ZVS operation over a wide load range, narrowed regulating frequency range, robustness, and fast transient response against transient load changes. Experimental and simulation results are reported to validate the theoretical predictions and to confirm the superior performance of the nonlinear controller when it is compared with a conventional linear controller.

Integral sliding mode compensator for load pressure control of die-cushion cylinder drive

This paper discusses problems of the load pressure control of electro-hydraulic drives in a presence of unknown disturbances and parametrical uncertainties. In many applications, the standard, linear control methods do not assure a satisfactory dynamical behavior and are likely to fail if a working point or the system properties change drastically. In order to guarantee a desired robustness and precision of the closed-loop system, a combination of the input–output linearization technique with the integral sliding mode is proposed. The structure of the presented controller is very simple, and can be easily implemented in standard industrial PLC's. The commissioning and tuning of the controller are uncomplicated and the adjustment procedure is partially automated. Conducted tests confirm a very good and robust performance of the closed loop control. The results are compared with those obtained with conventional linear controllers (P and PI).

Nonlinear Model Predictive Control versus Linear Time-Variant Control for Mobile Robots Prone to Input Saturation

This research work is focused on solving the practical problems that arise in trajectory tracking control of Hilare robots when the conventional Linear Time-Variant Controller (LTVC) is employed. The trajectory tracking of a Hilare robot on a flat 2D ground is considered. The left and the right wheel speeds of the robot are considered as the control inputs. It is assumed that the control inputs have a maximum affordable limit. The practical problems arise when the LTVC calculates control inputs that are beyond the affordable limit, and hence are truncated when applied to the real robot. The application of truncated control inputs causes system instability (and control failure) in practical situations. The failure of the LTVC when the control inputs are saturated is demonstrated by experimentation on a real robot. The Nonlinear Model Predictive Controller (NMPC) is proposed for eliminating the system instability due to an input saturation. The maximum affordable wheel speeds of the robot are implemented as constraints for the control input calculation by the NMPC. So, the calculated control inputs never exceed the affordable limit. The experimentation on a robot with the NMPC exhibits that the system instability due to the input saturation is eliminated.

Feedforward linearization and disturbance rejection of mechanical systems using acceleration measurements

In this paper a time-delayed acceleration measurement is used to linearize a second order nonlinear system. A theoretical foundation is developed, and a control strategy is presented which handles the challenges related to classical linearization. Utilizing the acceleration measurement to directly cancel the nonlinearities constitute a feedforward approach which increases robustness with respect to unmodeled dynamics and model uncertainties. Due to the time-delay, one or more perturbation terms dependent on a previous state of the system appears. This work outlines a stability criterion which these terms must satisfy in order for the linearization to be valid, where it is shown that the performance of the scheme is dependent on the measurement time-delay. The proposed method proves feasible when compared to two other nonlinear control strategies, including a conventional linearization control law and a sliding mode control law. In comparison, the feedforward linearization features robust performance without aggressive control input.