Tracking Of Reference Signal Research Articles

Type-III closed loop control systems-Digital PID controller design

The problem of tuning digital PID controllers for type-III control loops is investigated in this work. Type-III control loops are capable of achieving perfect tracking of step, ramp and parabolic reference signals with zero steady state position, velocity and acceleration error. The proposed PID control law involves any dominant time constants of the process itself, and any parasitic dynamics introduced by both the process and the controller, i.e. time delays within the closed control system. The development of the proposed control law takes place in the frequency domain and basis of the theory is the principle of the Magnitude Optimum criterion. The final control law consists of closed form expressions which involve also the controller's sampling time Ts. The potential of the proposed theory is justified for the control of several benchmark process models throughout simulation examples. The affect of the choice of the controller's sampling time is investigated further to the step and frequency response of the control loop both for the output of the control loop and the controller's command signal.

Active Disturbance Rejection Control of Nonlinear Thermal Process

The main contribution of this paper is to design active disturbance rejection control for a nonlinear thermal process to track reference signals while operating under the influence of disturbances. A linear active disturbance rejection controller is designed through an extended state observer to estimate and compensate the uncertainties of the system. The simulation result demonstrates very good performance of the controller in the absence of an accurate mathematical model of the process.

Linear parameter varying control of a doubly fed induction generator based wind turbine with primary grid frequency support

SUMMARYThis paper proposes a control method for a doubly fed induction generator (DFIG) driven by a wind turbine, whose rotor is connected to the power grid via two back‐to‐back pulse‐width modulation power converters. First, we design a rotor current controller for this system using the linear matrix inequality based approach to linear parameter varying systems, which takes into account the nonlinear dynamics of the system. We propose a two‐loop hierarchical control structure. The inner‐loop current controller, which considers the synchronous speed and the generator rotor speed as the components of the parameter vector, achieves tracking of the rotor current reference signals. The outer‐loop electrical torque controller aims for wind energy capture maximization and also grid frequency support, and it generates the reference rotor current. We perform a controller reduction for the inner‐loop linear parameter varying controller, which is not doable by conventional model‐reduction techniques, because the controller is parameter dependent. In simulation, the reduced‐order controller has been tested on a nonlinear fourth‐order DFIG model with a two‐mass model for the drive train. Stability and high performance have been achieved over the entire operating range of the DFIG in the wind turbine. Simulation results have demonstrated the capability of the proposed two‐loop control system to implement also grid frequency support. Copyright © 2013 John Wiley & Sons, Ltd.

Output tracking of uncertain fractional-order nonlinear systems via a novel fractional-order sliding mode approach

In this paper, a board class of uncertain fractional-order nonlinear systems is considered. A novel fractional-order sliding mode controller for output tracking of a time-varying reference signal is designed which can conquer the uncertainties and guarantees the asymptotic convergence of the system output toward the desired time-varying reference signal. For this purpose, an appropriate sliding surface is designed where maintaining the system’s states on this surface leads to asymptotic vanishing of error signal. Moreover, by tacking the fractional derivative of order α from the sliding surface, the convergence of system’s trajectories into the sliding surface in a finite time is proven. Finally, in order to verify the theoretical results, the proposed method is applied to a fractional-order gyroscope model and computer simulations show the efficiency of the proposed method in output tracking.

Fuzzy model reference control with adaptation of input fuzzy sets

An improved adaptation mechanism to fuzzy model reference learning control (FMRLC) will be introduced in this paper. The main idea of the presented approach consists in including the controller input fuzzy sets into the adaptation process. In comparison with other FMRLC modifications the proposed method can be started with smaller number of input membership functions resulting in better reference signal tracking. Performance of the proposed procedure is demonstrated on control of a nonlinear laboratory system.

Robust loop-shaping control for a nano-positioning stage

This paper proposes robust loop-shaping techniques for a two-axis nano-positioning piezoelectric stage. Piezoelectric transducers are usually used to drive precision mechanisms because of their favorable properties, such as high resolution, high accuracy, and large driving force. However, the nonlinear characteristics of piezoelectric materials can degrade system performance. Therefore, we model a piezoelectric stage as a linear system, and regard its nonlinear factors as system uncertainties. Because robust control can guarantee stability and performance for systems with uncertainties and disturbances, we apply loop-shaping techniques and design standard robust controllers for the stage. In addition, we consider fixed-order robust control for the system in that controllers with lower orders are preferred for hardware implementation. Lastly, the designed controllers are implemented for experimental verification. The results demonstrate the effectiveness of these robust controllers in tracking reference signals and suppressing high-frequency vibrations.

A Simplified Power Conditioner Based on Half-Bridge Converter for High-Speed Railway System

With the rapid development of high-speed and high-power railway system in China, power quality such as the negative sequence current and harmonic current caused by electric locomotives becomes more and more critical. This paper proposes a half-bridge-converter-based railway static power conditioner (RPC) (HBRPC) which consists of two half-bridge converters connected by two capacitors in series. Compared with the traditional RPC, the HBRPC requires only a pair of power switch legs and two capacitors. Under the premise of accomplishing the same function of RPC, the proposed conditioner can reduce half of the power switches, which can make it with lower cost and hardware complexity. A double-loop control is proposed for HBRPC to keep the dc-link voltage stable and achieve the dynamic tracking of the current reference signals, while a balanced voltage control is proposed to eliminate the error of two capacitor voltages and maintain the normal operation of HBRPC. Finally, simulation and experiment results have verified the proposed structure and its control method effectively.

Funnel Control for Systems with Relative Degree Two

Tracking of reference signals $y_{\mathrm{ref}}(\cdot)$ by the output $y(\cdot)$ of linear (as well as a considerably large class of nonlinear) single-input, single-output systems is considered. The system is assumed to have strict relative degree two with (weakly) stable zero dynamics. The control objective is tracking of the error $e=y-y_{\mathrm{ref}}$ and its derivative $\dot{e}$ within two prespecified performance funnels, respectively. This is achieved by the so-called funnel controller $u(t)=-k_0(t)^2e(t)-k_1(t)\dot{e}(t)$, where the simple proportional error feedback has gain functions $k_0$ and $k_1$ designed in such a way to preclude contact of $e$ and $\dot{e}$ with the funnel boundaries, respectively. The funnel controller also ensures boundedness of all signals. We also show that the same funnel controller (i) is applicable to relative degree one systems, (ii) allows for input constraints provided a feasibility condition (formulated in terms of the system data, the saturation bounds, the funnel data, bounds on the reference signal, and the initial state) holds, (iii) is robust in terms of the gap metric: if a system is sufficiently close to a system with relative degree two, stable zero dynamics, and positive high-frequency gain, but does not necessarily have these properties, then for small initial values the funnel controller also achieves the control objective. Finally, we illustrate the theoretical results by experimental results: the funnel controller is applied to a rotatory mechanical system for position control.

Distributed Average Tracking of Multiple Time-Varying Reference Signals With Bounded Derivatives

We present a distributed discontinuous control algorithm for a team of agents to track the average of multiple time-varying reference signals with bounded derivatives. We use tools from nonsmooth analysis to analyze the stability of the system. For time-invariant undirected connected network topologies, we prove that the states of all agents will converge to the average of the time-varying reference signals with bounded derivatives in finite time provided that the control gain is properly chosen. The validity of this result is also established for scenarios with switching undirected connected network topologies. For time-invariant directed network topologies with a directed spanning tree, we show that all agents will still reach a consensus in finite time, but the convergent value is generally not the average of the time-varying reference signals with bounded derivatives. Simulation examples are presented to show the validity of the above results.

No Steady-State Error Tracking Control of Multi-Axle Steering Vehicle

In order to improve the interference suppression capability for the muti-axle steering vehicle(MASV) and to reduce the design complexity of the controller , no steady-state error tracking control system was designed so that the contol system can meet the requirements of disturbance rejection and robust tracking. Using the no steady-state error tracking control strategy to the MASV, it can track reference signal perfectly. Its yaw angular velocity, sidesip angle and rolling angle are degraded at high vehicle speed. The stability and driving safety of the vehicle are improved. According to actual needs, the Parameter of the controller can be changed through the different characteristic value; The design and adjustment of the controller are simple amd easy.

SISO linear system control via saturating actuator: L2 tracking performance in the presence of arbitrary-shaped inputs

Most studies on linear system control in the presence of actuator saturation have focused on closed-loop asymptotic stabilisation. Available tracking results are generally limited to constraint-compatible inputs (references, disturbances) with known exogenous input models. The problem of output-reference tracking in the presence of arbitrary-shaped not necessarily constraint-compatible inputs has yet to be investigated. In this study, we show that an tracking performance is achievable for SISO linear systems using a given class of saturated controllers. Accordingly, the tracking error energy (resp. power) is bounded by the energy (resp. power) of a well-defined mismatch input depending on the disturbance and reference compatibility. In the disturbance-free case, this entails perfect asymptotic tracking of arbitrary-shaped constraint-compatible reference signals. Otherwise, the average tracking quality is proportional to the mismatch input power. In the case of periodic inputs (constraint-compatible or not), all system signals are shown to be periodic with the same period as the inputs.

Multivariable Repetitive-Predictive Controllers Using Frequency Decomposition

Repetitive control is a methodology for the tracking of a periodic reference signal. This paper develops a new approach to repetitive control systems design using receding horizon control with frequency decomposition of the reference signal. Moreover, design and implementation issues for this form of repetitive predictive control are investigated from the perspectives of controller complexity and the effects of measurement noise. The analysis is supported by a simulation study on a multi-input multi-output robot arm where the model has been constructed from measured frequency response data, and experimental results from application to an industrial AC motor.

Precise tracking control of piezoelectric actuators based on a hysteresis observer

In this paper, a precise tracking control method for piezoelectric actuators based on a hysteresis observer is considered. A nonlinear observer to estimate the hysteretic nonlinearity in the piezoelectric actuator is designed, and then the hysteretic nonlinearity is compensated for by a feedforward control. The proposed observer is easy to design and has better performance compared to the previous work presented in the literature. A feedback controller is also designed to track reference signals. A numerical simulation is presented to verify the method proposed.

Observer–PID Stabilization Strategy for Unstable First-Order Linear Systems with Large Time Delay

This work considers the stabilization and control of a class of unstable first-order linear systems subject to a relatively large input–output time delay. As a first step, a particular observer scheme is proposed in order to predict a specific internal signal in the process. Conditions to ensure the adequate prediction convergence of the signals are formally stated. In a second step, the internal predicted signal is used to implement classical P, PI, and PID controllers providing stability conditions for the resulting closed-loop system. The proposed control strategy allows one to address time delays as large as four times the unstable time constant of the open-loop system, in contrast with the reported related literature where the maximal bound has been stated until now as two times the unstable time constant of the open-loop system. The proposed observer-based control structure considers also the tracking of step reference signals and the rejection of input step disturbances.

A Feedback Linearization Based Unified Power Flow Controller Internal Controller for Power Flow Control

This article presents a feedback linearization based controller design methodology for a unified power flow controller to achieve rapid reference signal tracking in the internal control level. Feedback linearization is a non-linear control technique based on the differential geometry theory and overcomes the drawback of traditional linear proportional-integral control, which is typically tuned for one specific operating condition. In this article, feedback linearization control is developed for the unified power flow controller dynamic model via an appropriate coordinate transformation, and linear quadratic regulator control is then applied on the transformed linear system. The proposed control is validated via a detailed device-level simulation on an 11-bus system and a large scale simulation on the IEEE 118-bus and 300-bus systems. The proposed control is benchmarked against proportional-integral control.

Adaptive fuzzy sliding mode control for electro-hydraulic servo mechanism

An innovative approach to adaptive fuzzy sliding mode control for a class of SISO continuous nonlinear systems with unknown dynamics and bounded disturbances is introduced in this paper. The main idea of the presented method consists in the introduction of the fuzzy self-tuning mechanism for adaptation of the sliding mode control parameters – extended feedback and switching gains. Such modification reduces the well-known chattering problem in classical sliding mode control. In comparison with the other algorithms eliminating this problem the proposed method results in faster convergence and more transparent and interpretable design of self-tuning mechanism. Moreover, the proposed method guaranteing the asymptotic reference signal tracking with bounded system signals can be easily implemented to high order systems. The performance of the presented control design is demonstrated on control of a nonlinear electro-hydraulic servo mechanism.

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct rotor-field oriented control (DRFOC) of the induction motor (IM) drive structure. Connective weights of the controller are trained on-line according to the error between the actual speed of the drive and the reference model output signal. The rotor flux and speed of the vector controlled induction motor are estimated using the model reference adaptive system (MRAS) - type estimator. Presented simulation results are verified by experimental tests performed on the laboratory-rig with DSP controller.

Model Based Control for Closed Loop Testing of 1-D Engine Simulation Models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts and prediction of the resulting engine transient response. The latter often requires closed loop control over the model to ensure operation within physical limits and tracking of reference signals. For this purpose, a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). As an example this study is focused on the transient response of a light-duty car Diesel engine. For the cases examined the proposed controller implementation gives a more systematic procedure than other ad-hoc approaches that require considerable tuning effort.

Minimum Variance Adaptive Control of A Servo Drive with Unknown Structure and Parameters

AbstractThis paper presents an adaptive controller with real‐time simultaneous estimation of coefficients and orders of the plant polynomials in the reference signal tracking task of a servo drive.

Comparison of two non-linear control approaches to fast nanopositioning: Impulsive control and signal transformation

Non-linear approaches to feedback control for nanopositioning have recently attracted renewed interest thanks to their superior performance in the presence of measurement noise. In this article, we investigate two recent non-linear control schemes, namely signal transformation and impulsive control, and show that in the context of triangular waveform tracking, they are inherently related. This rather surprising result not only fosters further theoretical studies but also has a significant impact on implementation. We demonstrate that for the tracking of triangular reference signals, impulsive control drastically improves the transient tracking error while providing the same steady state performance. Both methods are compared in theory, simulation and experiments.