Self-tuning Control Research Articles

Indirect self-tuning controller for a two degree of freedom tracker model

Tracker systems have turned into an increasingly important issue in guidance systems and play a key role in navigational tracking. The aim of this study is to investigate a newly-developed self-tun...

Switched-Capacitor Tuning for Three-Phase Wireless Power Receiver Based on Perturbation and Observation Method

To realize the tuning of three-phase dynamic wireless power receivers for rail vehicles, a non-real-time static self-tuning scheme based on the switched capacitor and the perturbation and observation (P&O) method is studied. First, the reactance regulation characteristics of the parallel and the series switched capacitor are discussed and compared. Then, to avoid the sophisticated mistuning detection, in the case of only observing the output voltage, the feasibility of using the P&O method to tune three phases of the receiver sequentially is analyzed. Furthermore, theoretical analysis shows that the switched capacitor can also be used to control the current phase difference between the three phases. Thereby, by introducing the current phase difference control, a fast three-phase simultaneous tuning strategy is proposed without additional hardware. Afterward, the self-tuning control scheme for the star-connected series-compensated receiver with the parallel and series switched capacitor is design in detail and be applied to a scaled-down prototype of a three-phase dynamic wireless power transfer system for verification. The result shows that the receiver can be tuned within the ±5% deviation of the main compensation capacitance, and the tuning speed of the proposed simultaneous tuning of three phases is about three times that of the sequence tuning.

Indirect self-tuning controller for a two degree of freedom tracker model

Indirect self-tuning controller for a two degree of freedom tracker model

Self-tuning state-feedback control of a rotary pendulum system using adjustable degree-of-stability design

This paper formulates an original hierarchical self-tuning control procedure to enhance the disturbance-rejection capability of under-actuated rotary pendulum systems against exogenous disturbances. The conventional state-feedback controllers generally make a trade-off between the robustness and control effort in a closed-loop system. To combine the aforementioned characteristics into a single framework, this paper contributes to develop and augment the baseline Linear-Quadratic-Regulator (LQR) with a novel “adjustable degree-of-stability design” module. This augmentation dynamically relocates the system's closed-loop poles in the stable (left-half) region of the complex plane by dynamically adjusting a single hyper-parameter that modifies the constituents of LQR's performance index. The hyper-parameter is adaptively modulated online via a pre-calibrated hyperbolic-secant-function that is driven by state-error variables. The performance of the proposed adaptive controller is benchmarked against fixed-gain controllers via credible hardware experiments conducted on the standard QNET Rotary Pendulum setup. The experimental outcomes indicate that the proposed controller significantly enhances the system's robustness against exogenous disturbances and maintains its stability within a broad range of operating conditions, without inducing peak servo requirements.

Design Robust Self-tuning FPIDF Controller for AVR System

This paper presents the fuzzy PID filter (FPIDF) controller for the automatic voltage regulator (AVR). This controller is used to maintain the generating unit output voltage within allowable limit, and improve the weakness of the conventional controller’s fast response under any sudden changes in operating conditions or any disturbance that affect the voltage stability. Firstly, the PID low pass filter (PIDF) controller initial values are calculated by using teaching-learning based optimization (TLBO) algorithms. After that, we construct the FPIDF for self-tuning the PIDF parameters in real-time to make the controller fast response. The dynamic performance characteristic of the terminal voltage is investigated and analyzed when the system subjected to the different step change in reference voltage from low to high. The performance of FPIDF is compared with PIDF, fuzzy PID (FPID), and classical PID controller. Also, the FPIDF controller performance is compared with other metaheuristics algorithms based on the controller in the latest literature. Moreover, the strengths, robustness, and effectiveness of the FPIDF controller are checked under uncertainties of AVR parameters. The maximum total deviation of the system performance is calculated in different ranges of the system parameter deviations. The results show a small maximum total deviation percentage when using the proposed controller. Finally, we can observe that the FPIDF controller has better dynamic performance than the other controllers, also has strong robustness and fast real-time response under any sudden changes in system operation.

Adaptive State-space Control of Under-actuated Systems Using Error-magnitude Dependent Self-tuning of Cost Weighting-factors

This article methodically constructs a novel adaptive self-tuning state-space controller that enhances the robustness of under-actuated systems against bounded exogenous disturbances. The generic Linear-Quadratic-Regulator (LQR) is employed as the baseline controller. The main contribution of this article is the formulation of a hierarchical online gain-adjustment mechanism that adaptively modulates the weighting-factors of LQR’s quadratic-performance-index by using pre-calibrated continuous hyperbolic scaling functions. The hyperbolic scaling functions are driven by the magnitude of system’s state-error variables. This augmentation dynamically updates the solution of the Matrix-Riccati-Equation which modifies the state-feedback gains after every sampling interval. The efficacy of the proposed adaptive controller is validated by conducting hardware-in-the-loop experiments on QNET Rotary Pendulum setup. The experimental outcomes show that the proposed adaptive control scheme yields stronger damping against oscillations and faster error-convergence rate, while maintaining the controller’s asymptotic-stability, under the influence of parametric uncertainties.

Recursive least squares based sliding mode approach for position control of DC motors with self-tuning rule

In this paper, a self-tuning rule-based position control algorithm is proposed for DC motors with system parameter estimation using the recursive least squares method. First, a mathematical model of the angular position control of a DC motor was derived. Next, the time-varying parameters including the rotational inertia in the model were estimated using the RLS method along with multiple forgetting factors without prior knowledge of the system. Based on the derived model and the parameter estimation, a sliding mode control algorithm was designed by applying a self-tuning rule that enables the magnitude of the voltage input to be adaptively adjusted for improvement of the energy efficiency. The performance of the designed control algorithm was then experimentally evaluated under several different load conditions. Finally, the evaluation results show that the designed controller achieves a satisfactory capability for a DC motor to deal with both tracking accuracy and energy efficiency without prior knowledge of the system.

Design of robust self‐tuning regulator adaptive controller on single‐phase full‐bridge inverter

This paper depicts a self-tuning adaptive control method along with a novel robust procedure to system identification which is applied to a single-phase full-bridge Inverter with LC filter by Pulse Width Modulation (PWM). Moreover, an LC filter is designed to decrease the disturbing harmonics produced by PWM which, the stability of the filter can be noted as an important issue. On the other hand, a dynamic change of the inverter can lead to instability issues in which the proposed approach can overcome this problem and perform with a great response. Due to the parametric uncertainty on a full-bridge inverter and other disturbing factors, a digital adaptive controller is proposed which is performed by minimum degree pole placement (MDPP) technique combined with Improved Exponential Regressive Least identification (IERLS) algorithm. To prevent the undesired influences of high variance noises and disturbance on the performance of the identification approach, a robust identification algorithm is introduced which is capable of keeping the parametric estimation process in a desired range. Additionally, to deal with the variations of supply DC voltage, a proportional-integral-derivative (PID) controller is designed. Finally, the experimental and simulation results are performed by Matlab-Simulink to show the validation of the work.

Self-tuning fuzzy PID controller for servo control of hard disk drive with time delay

This paper presents the implementation of conventional proportional-integral-derivative (PID) controller, fuzzy logic with proportional-derivative (FL-PD) control configuration and self-tuning fuzzy logic PID (STFL-PID) controller for servo control of hard disk drive (HDD). Comprehensive performance analyses of the conventional PID, FL-PD and STFL-PID controllers are performed, and identify the superior control technique for the HDD. It is shown that the proposed and designed control technique improves the track seeking performance. The proposed controller is used to keep the read/write (R/W) head on track i.e., to minimize the position error signal (PES).

Control for Carbon Dioxide Exchange Process in a Membrane Oxygenator Using Online Self-Tuning Fuzzy-PID Controller

Background and objectiveThe aim of this study is to evaluate the performance of conventional PID that is tuned using Zeigler-Nichols continuous cycling, Fuzzy Logic Controller (FLC) and self-tuning Fuzzy-PID (self-tuning FPID) methods to control the rate of CO2 removal from a membrane oxygenator during extracorporeal blood purification process. MethodsSweep gas flow rate is chosen as the manipulated variable of arterial CO2 partial pressure (pCO2) in blood. The performance of these controllers is evaluated based on their response in controlling task and also by the calculation of three performance indices, namely Integral Absolute Error (IAE), Integral Squared Error (ISE) and Integral Time Absolute Error (ITAE). The robustness of the controllers using these tuning methods is then assessed for set point tracking and load disturbance rejection tests. ResultsResults indicated that the self-tuning FPID is observed as the best controller compared to conventional PID and FLC with lower oscillation, overshoot and shorter settling time. As for quantitative measurement, self-tuning FPID outshines the other controllers with 0.854, 1.084 and 41.450 for IAE, ISE and ITAE, respectively in set point tracking task while 0.532 IAE, 0.016 ISE and 28.970 ITAE measured for load disturbance rejections. ConclusionIt can be concluded that self-tuning FPID is the best controller to be used in the automation of extracorporeal circulation control for both set point tracking and load disturbance rejection tests.

Adaptive control strategy for improved dynamic performance of two islanded inter-connected micro-grids

Micro-grids with proper control should be able to maintain stability and achieve the best response when subjected to different disturbances. Traditionally, power electronic converters used in micro-grids are controlled using linear fixed parameter controllers such as, conventional PI controller and droop controller, which are unable to mitigate such disturbances efficiently over a wide range of operating conditions. An adaptive self-tuning controller that can adapt in real-time as operating conditions change is investigated in this paper. An adaptive self-tuning controller based on recursive least squares identification and pole-shifting control is designed and implemented on the dispatchable sources connected boost converter in two connected micro-grids. Its performance is compared with the fixed parameter PI controller. Parameters of the PI controller and gains of the self-tuning adaptive controller are optimized using an advanced optimization technique called global Porcellio Scaber algorithm. Effectiveness of the proposed controller is investigated on a two inter-connected micro-grids system isolated from the grid under various scenarios such as load variations and weather conditions fluctuations. Simulation results verify that the system response based on the proposed pole-shift controller is better than the classical PI controller under various operating conditions.

A New Methodology for a Retrofitted Self-tuned Controller with Open-Source FPGA.

Servo systems are feedback control systems characterized by position, speed, and/or acceleration outputs. Nowadays, industrial advances make the electronic stages in these systems obsolete compared to the mechanical elements, which generates a recurring problem in technological, commercial and industrial applications. This article presents a methodology for the development of an open-architecture controller that is based on reconfigurable hardware under the open source concept for servo applications. The most outstanding contribution of this paper is the implementation of a Genetic Algorithm for online self tuning with a focus on both high-quality servo control and reduction of vibrations during the positioning of a linear motion system. The proposed techniques have been validated on a real platform and form a novel, effective approach as compared to the conventional tuning methods that employ empirical or analytical solutions and cannot improve their parameter set. The controller was elaborated from the Graphical User Interface to the logical implementation while using free tools. This approach also allows for modification and updates to be made easily, thereby reducing the susceptibility to obsolescence. A comparison of the logical implementation with the manufacturer software was also conducted in order to test the performance of free tools in FPGAs. The Graphical User Interface developed in Python presents features, such as speed profiling, controller auto-tuning, measurement of main parameters, and monitoring of servo system vibrations.

Frequency regulation of a weakly connected microgrid using the fuzzy-PID controller

Abstract Microgrid system stability is a major source of concern due to the rapid increase in load demand and a high level of renewable energy penetration. During the grid- connected mode, the microgrid power quality is mainly affected by the level of connection strength with the host grid. Thus, this paper aims to investigate the impact of the implemented control strategy in the microgrid, on frequency response when its level of connection strength is weak, that is, the frequency and voltage are not dominantly controlled by the grid. A control scheme based on a fuzzy logic-based self-tuning PID controller (fuzzy-PID) is used to maintain the frequency within the acceptable range. Simulations illustrate that the frequency dynamic response of the microgrid guarantees a good performance using the fuzzy-PID controller despite a large drop in grid inertia and the presence of disturbances whereas the classical PID controller cannot maintain the frequency within the acceptable range.

Self-Tuning Fuzzy Task Space Controller for Puma 560 Robot

Since in most robot applications the desired paths are determined in task space or Cartesian space, it is important to control the robot arm in task space. In this paper, a fuzzy controller with modifiable scaling factors is proposed to control the robot end-effector in task space. The controller is a fuzzy system with a mechanism to change the scaling factors when the error is bounded under a predetermined value. The controller is designed in joint space and is developed to work space by using inverse Jacobian strategy. The simulations results on Puma 560 robot manipulator illustrate the high performance of the presented control method.

Survey of Optimal Control and Model Predictive Control with State Estimation and a Real Time Application

Abstract The optimal control and its limited version namely the model predictive control represent one of the most important nonlinear control alternatives nowadays. The success of them are also proven in many practical applications. These can provide for several industrial applications the optimal trajectory calculation as well as calculation of the real-time control signal. One successful version of this is Generalized Predictive Control (GPC). A big advantage of these control algorithms is that they solutions are able to take into account the limitations of the inputs, and the states. In some cases, it is important to know the mathematical model chosen and the complete state information. Otherwise, the model can be estimated during the operation. Our study shows through the control of the cathode heating of a high-power electron beam device the self-tuning adaptive control thus constructed. Using a suitable dynamic model and an extended Kalman estimator, we determine the estimated temperature of the two cathodes during operation and the saturation electron current, which ensures the maximum cathode life. The practical application was tested on a CTW 5/60 type electron gun.

Coordinated Self-Tuning Thermal Management Controller for Mobile Devices

Editor's notes: Thermal management is a critical factor in determining the performance limits of mobile devices due to their limited cooling capabilities. This article presents a coordinated self-tuning controller that reduces thermal violations significantly while providing higher performance. - Umit Y. Ogras, Arizona State University.

A PID-Type Fuzzy Logic Controller-Based Approach for Motion Control Applications

Motion control is widely used in industrial applications since machinery, robots, conveyor bands use smooth movements in order to reach a desired position decreasing the steady error and energy consumption. In this paper, a new Proportional-Integral-Derivative (PID) -type fuzzy logic controller (FLC) tuning strategy that is based on direct fuzzy relations is proposed in order to compute the PID constants. The motion control algorithm is composed by PID-type FLC and S-curve velocity profile, which is developed in C/C++ programming language; therefore, a license is not required to reproduce the code among embedded systems. The self-tuning controller is carried out online, it depends on error and change in error to adapt according to the system variations. The experimental results were obtained in a linear platform integrated by a direct current (DC) motor connected to an encoder to measure the position. The shaft of the motor is connected to an endless screw; a cart is placed on the screw to control its position. The rise time, overshoot, and settling time values measured in the experimentation are 0.124 s, 8.985% and 0.248 s, respectively. These results presented in part 6 demonstrate the performance of the controller, since the rise time and settling time are improved according to the state of the art. Besides, these parameters are compared with different control architectures reported in the literature. This comparison is made after applying a step input signal to the DC motor.

Model reference self-tuning fractional order PID control based on for a power system stabilizer

<p><span lang="EN-US">This paper presents a novel approach of self-tuning for a Modified Fractional Order PID (MFOPID) depends on the Model Reference Adaptive System (MRAS). The proposed self-tuning controller is applied to Power System Stabilizer (PSS). Takaji-Sugeno (TS) fuzzy logic technique is used to construct the MFOPID controller. The objective of MRAS is to update the five parameters of Takaji-Sugeno Modified FOPID (TSMFOPID) controller online. For different operating points of PSS, MRAS is applied to investigate the effectiveness of proposed controllers. The harmony optimization technique used to obtain the optimal parameters of TSMFOPID controllers and MRAS parameters. For different operating points with different disturbance under parameters variations the simulation results are obtained. This is to show that Self-Tuning of TSMFOPID based on (MRAS) have better performance than the fixed parameters TSMOFOPID controller.</span></p>

Multi-point Mooring PID Control Based on Kalman Filtering-Genetic Algorithm-Slow Disturbance Observer Compensation

An adaptive PID control technique based on the Kalman Filtering (KF) Genetic Algorithm (GA) and Slow Disturbance Observer Compensation (SDOC) is proposed for multi-point mooring system in this paper. The multi-point mooring model, which is simplified to two-point mooring, is established, its self-tuning PID mooring controller based on KF-GA-SDOC is designed. The multi-point mooring model is updated on-line with the KF and SDOC to filter and observe time-varying signal; the PID mooring control gains are adjustable parameters by selection, crossover and mutation operator of GA; the mooring control system based on KF-GA-SDOC PID is optimized. The simulation results show that the designed KF-GA-SDOC PID mooring controller can maintain good control performance under different conditions.

A method for autonomous robotic manipulation through exploratory interactions with uncertain environments

Expanding robot autonomy can deliver functional flexibility and enable fast deployment of robots in challenging and unstructured environments. In this direction, significant advances have been recently made in visual-perception driven autonomy, which is mainly due to the availability of rich sensory data-sets. However, current robots’ physical interaction autonomy levels still remain at a basic level. Towards providing a systematic approach to this problem, this paper presents a new context-aware and adaptive method that allows a robotic platform to interact with unknown environments. In particular, a multi-axes self-tuning impedance controller is introduced to regulate quasi-static parameters of the robot based on previous experience in interacting with similar environments and the real-time sensory data. The proposed method is also capable of differentiating internal and external disruptions, and responding to them accordingly and appropriately. An agricultural experiment with different deformable material is presented to validate robot interaction autonomy improvements, and the capability of the proposed methodology in detecting and responding to unexpected events (e.g., faults).