Adaptive Robust Control of Hydraulic Robots With Recursive Least Squares

2009 ◽  
Author(s):  
Longke Wang ◽  
Wayne J. Book ◽  
James D. Huggins
Keyword(s):  
Robot Control ◽  
Control Algorithm ◽  
Adaptive Robust Control ◽  
Least Square ◽  
Recursive Least Squares ◽  
Parameter Design ◽  
Recursive Least Square ◽  
Computationally Efficient ◽  
Control Approach ◽  
Simple Parameter

This paper proposes a robot control approach using a discrete recursive least square algorithm. The scheme shows robustness when the system suffers from measurement noise and has a fast parameter convergence rate. The control algorithm is computationally efficient and numerically stable. Guaranteed trajectory tracking can be achieved by simple parameter design if disturbances are bounded.

Simulation and Experimentation of a Precise Nonlinear Tracking Control Algorithm for a Rotary Servo-Hydraulic System With Minimum Sensors

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
M. H. Toufighi ◽  
S. H. Sadati ◽  
F. Najafi ◽  
A. A. Jafari
Keyword(s):  
Singular Perturbation ◽  
Hydraulic System ◽  
Control Algorithm ◽  
Small Error ◽  
Least Square ◽  
Real System ◽  
Singular Perturbation Theory ◽  
Control Analysis ◽  
Recursive Least Square ◽  
The Real

The dynamics of hydraulic systems involves slow and fast modes. These modes are associated with the mechanical components and those involving fluid flow, respectively. As such, controllers for electro-hydraulic servo systems (EHSS) can be designed and analyzed using singular perturbation theory. In this paper, a singular perturbation control (SPC) algorithm is proposed and investigated on a rotary EHSS modeled based on a two-time-scale behavior of the system. For modeling, the components of the hydraulic system, specifically the nonlinear model of the orifice in servo valve, are modeled. A mathematical modeling and nonlinear control analysis that validated by experiment is presented. The controlled system with the SPC algorithm tracks a fairly smooth trajectory with very small error. As well, the control algorithm is successfully verified by experiment as the main contribution of the paper. In addition, this is robust to variations in the hydraulic fluid bulk modulus such that only its nominal value is sufficient. Furthermore, the proposed control design will not require derivatives of the control pressures and any output acceleration feedback. Hence, it can be implemented easier in the real system setup. The controller design approach addresses the nonlinearities of the rotary EHSS. The parameters of the real system model are experimentally identified using the continuous recursive least square method.

scholarly journals Torque Ripple Minimization in PMSM Based on an Indirect Adaptive Robust Controller

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Ruichao Tao ◽  
Jie Ma ◽  
Hui Zhao
Keyword(s):  
Permanent Magnet Synchronous Motor ◽  
Torque Ripple ◽  
Adaptive Robust Control ◽  
Least Square ◽  
Parametric Estimation ◽  
Current Loop ◽  
Recursive Least Square ◽  
Robust Controller ◽  
Adaptation Law ◽  
Torque Ripples

This paper addresses the problem of torque ripple minimization in permanent magnet synchronous motor (PMSM), which plays an important role in modern aerospace industry. Accurate motion control and disturbance compensation are challenging issues of PMSM systems, where the nonlinear disturbances are quite complicated and various uncertainties exist. To overcome these control problems, based on the adaptive robust control (ARC) algorithm, an indirect adaptive robust controller (IARC) with a robust recursive least square (RRLS) adaption law is proposed as a solution. A modified PMSM model which indicates the torque ripple generation is first derived. The IARC in current loop is then described, holding the good tracking performance of ARC algorithm and minimizing the torque ripples while speed tracking. The RRLS adaption law in IARC is synthesized based on modified model and then a correction factor is added to enhance the robustness of this adaptation law. This can enable the better parametric estimation and adaptive compensation to minimize the torque ripples. The stability of the system with the proposed controller is proved. Finally, the effectiveness of the proposed method is demonstrated by the simulation results.

Adaptive Order Tracking Technique Using Recursive Least-Square Algorithm

2002 ◽  
Vol 124 (4) ◽  
pp. 502-511 ◽  
Author(s):  
Mingsian R. Bai ◽  
Jihjau Jeng ◽  
Chingyu Chen
Keyword(s):  
Least Square ◽  
Recursive Least Squares ◽  
Frequency Resolution ◽  
Shaft Speed ◽  
Recursive Least Square ◽  
Rls Algorithm ◽  
Tracking Technique ◽  
Order Tracking ◽  
Conventional Methods ◽  
Bandpass Signals

Order tracking technique is one of the important tools for diagnosis of rotating machinery. Conventional methods of order tracking are primarily based on Fourier analysis with reference to shaft speed. Resampling is generally required in the fast Fourier transform (FFT)-based methods to compromise between time and frequency resolution for varying shaft speeds. Conventional methods suffer from a number of shortcomings. In particular, smearing problems arise when closely spaced orders or crossing orders are present. Conventional methods also are ineffective for the applications involving multiple independent shaft speeds. This paper presents an adaptive order tracking technique based on the Recursive Least-Squares (RLS) algorithm to overcome the problems encountered in conventional methods. In the proposed method, the problem is treated as the tracking of frequency-varying bandpass signals. Order amplitudes can be calculated with high resolution by using the proposed method in real-time fashion. The RLS order tracking technique is applicable whether it is a single-axle or multi-axle system.

An Adaptive Semiactive Control Algorithm for Vehicle Suspension Systems

2003 ◽  
Author(s):  
Xubin Song ◽  
Mehdi Ahmadian ◽  
Steve Southward
Keyword(s):  
Dynamic System ◽  
Adaptive Algorithm ◽  
Control Algorithm ◽  
Suspension System ◽  
Least Square ◽  
Vehicle Suspension ◽  
Semiactive Control ◽  
Vehicle Speed ◽  
Recursive Least Square ◽  
Line System

In general, a vehicle suspension system can be characterized as a nonlinear dynamic system that is subjected to unknown vibration sources, dependent on road roughness and vehicle speed. In this paper, we will present a nonlinear-model-based adaptive semiactive control algorithm developed for nonlinear systems exposed to broadband non-stationary random vibration sources that are assumed to be unknown or not measurable. If there exist unknown and/or varying parameters of the dynamic system such as mass and stiffness, then the adaptive algorithm can include a recursive least square (RLS) method for on-line system identification. Since the adaptive algorithm is developed for semiactive systems, stability is guaranteed based on the fact that the system is energy conservative. The convergence of the adaptive system, however is not guaranteed, and is investigated through a numerical approach for a specific case. The simulation results for a magneto-rheological seat suspension system with the suggested adaptive control are presented. The results are compared with low-damping and high-damping cases, as well æ other configurations of skyhook control, in order to show the extent of the procurement that can be expected with the suggested adaptive skyhook control provides a better broadbandk performance for the suspension, as compared to the other damping configurations that are included here.

A power perturbation-based MTPA control with disturbance torque observer for IPMSM drive system

2018 ◽  
Vol 40 (10) ◽  
pp. 3179-3188 ◽  
Author(s):  
Faa-Jeng Lin ◽  
Shih-Gang Chen ◽  
Ying-Tsen Liu ◽  
Shih-Yao Chen
Keyword(s):  
Digital Signal Processor ◽  
Feedforward Control ◽  
Permanent Magnet Synchronous Motor ◽  
Drive System ◽  
Least Square ◽  
Experimental Results ◽  
Recursive Least Square ◽  
Control Approach ◽  
Torque Observer ◽  
Disturbance Torque

A novel maximum torque per ampere (MTPA) method based on power perturbation for a field-oriented control (FOC) interior permanent magnet synchronous motor (IPMSM) drive system is proposed in this study. The proposed MTPA method is designed based on the power perturbation resulting from the signal injection in the current angle. Moreover, the influence of current and voltage harmonics to the MTPA control can be effectively eliminated. Furthermore, to enhance the robustness of the control system, a real-time design scheme for the integral–proportional (IP) speed controller using a recursive least square (RLS) estimator with disturbance torque feedforward control is developed. The disturbance torque is obtained from an improved disturbance torque observer with online parameters updated. Finally, some experimental results using an IPMSM drive system based on a low-price digital signal processor (DSP) are presented. From the experimental results, the proposed control approach can guarantee the control performance of a speed loop even under a cyclic fluctuating load.

INVERSE DYNAMIC INPUT ESTIMATION OF A SEISMIC SOIL–STRUCTURE INTERACTION SYSTEM

2014 ◽  
Vol 06 (04) ◽  
pp. 1450040 ◽  
Author(s):  
MING-HUI LEE
Keyword(s):  
Soil Structure ◽  
Estimation Method ◽  
Least Square ◽  
Recursive Least Squares ◽  
Soil Structure Interaction ◽  
Recursive Least Square ◽  
Inverse Dynamic ◽  
Input Estimation ◽  
Structure Interaction ◽  
Interaction System

The innovative fuzzy weighting input estimation method is used to estimate the ground motion acceleration of a soil–structure interaction system in this study. The input estimation method is comprised of the Kalman filter without the input term and the fuzzy weighting recursive least square estimator. The recursive least squares estimator (RLSE) is weighted using the fuzzy weighting factor. The superior capabilities of this inverse method are demonstrated by solving the soil–structure interaction estimation problem. The precision of the proposed method is verified using the actual earthquake acceleration. The results show that this method has the advantages of stability and accuracy.

Chaos Control in Bonhoeffer-van der Pol System Using Fuzzy Estimation

Volume 1 ◽  
2004 ◽  
Author(s):  
Aria Alasty ◽  
Hassan Salarieh
Keyword(s):  
Fuzzy Control ◽  
Transient Response ◽  
Control Algorithm ◽  
Chaos Control ◽  
Least Square ◽  
Delayed Feedback Control ◽  
Recursive Least Square ◽  
Van Der Pol ◽  
Time Dynamic ◽  
Energy Behavior

This paper illustrates the control of chaos using a fuzzy estimating system based on batch training and recursive least square methods for a continuous time dynamic system. The fuzzy estimator system is trained on both Ott-Geobogi-Yorke (OGY) control algorithm and Pyragas’s delayed feedback control algorithm. The system, considered for this study, is a Bonhoeffer-van der Pol (BVP) oscillator. It is found that the implemented fuzzy control system constructed on OGY algorithm results in smaller control transient response than that of the OGY control algorithm itself. The transient response of Pyragas fuzzy control does not show a significant improvement in compare to the Pyragas control itself. In general the proposed control techniques show very effective low cost energy behavior in chaos control in compare to conventional nonlinear control methods.

scholarly journals Manuscript shapes generated by novel bi-axis control algorithm based on a mathematical handwriting model

2016 ◽  
Vol 4 (3) ◽  
pp. 230
Author(s):  
Imene Mahmoud ◽  
Ines Chihi ◽  
Afef Abedlkrim ◽  
Mohamed Benrejeb
Keyword(s):  
Control Algorithm ◽  
Biological Process ◽  
Velocity Model ◽  
Least Square ◽  
Recursive Least Square ◽  
Output Data ◽  
Arabic Word ◽  
Identification Technique ◽  
Human Motions ◽  
Complex Activities

<span lang="EN-US">Handwriting movement is one of the most complex activities of human motions. It’s a blend of kinesthetic, cognitive, perceptual and motor components. The study of this biological process shows that bell-shaped velocity profiles are generally observed in the handwriting motion. In this paper, an identification technique, based on Recursive Least Square algorithm (RLS), is proposed to identify the pen-tip movement in human handwriting process, by using input and output data which present EMG signals and velocities according to x and y coordinates.  Using the estimated coordinates that have resulted from the velocity model; we propose a novel algorithm to generate handwritten graphic traces, which is inspired from the idea of tracing circles by Bresenham bi-axis control algorithm. The effectiveness of this approach should be observed on predicting cursive Arabic letters and Arabic word written on (</span><em><span lang="EN-US">x,y</span></em><span lang="EN-US">) plane, these shapes constituting a recorded experimental basis.</span>

scholarly journals Recursive Least Squares Filtering Algorithms for On-Line Viscoelastic Characterization of Biosamples

Actuators ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 74 ◽  
Author(s):  
Paolo Di Giamberardino ◽  
Maria Aceto ◽  
Oliviero Giannini ◽  
Matteo Verotti
Keyword(s):  
Least Square ◽  
Constitutive Law ◽  
Recursive Least Squares ◽  
Measurement Tool ◽  
Recursive Least Square ◽  
Novel Approach ◽  
Rigid Body Model ◽  
Gradient Based ◽  
On Line

The mechanical characterization of biological samples is a fundamental issue in biology and related fields, such as tissue and cell mechanics, regenerative medicine and diagnosis of diseases. In this paper, a novel approach for the identification of the stiffness and damping coefficients of biosamples is introduced. According to the proposed method, a MEMS-based microgripper in operational condition is used as a measurement tool. The mechanical model describing the dynamics of the gripper-sample system considers the pseudo-rigid body model for the microgripper, and the Kelvin–Voigt constitutive law of viscoelasticity for the sample. Then, two algorithms based on recursive least square (RLS) methods are implemented for the estimation of the mechanical coefficients, that are the forgetting factor based RLS and the normalised gradient based RLS algorithms. Numerical simulations are performed to verify the effectiveness of the proposed approach. Results confirm the feasibility of the method that enables the ability to perform simultaneously two tasks: sample manipulation and parameters identification.

scholarly journals Parameter Identification of BLDC Motor Using Electromechanical Tests and Recursive Least-Squares Algorithm: Experimental Validation

Actuators ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 143
Author(s):  
Jose Jimenez-Gonzalez ◽  
Felipe Gonzalez-Montañez ◽  
Victor Manuel Jimenez-Mondragon ◽  
Jesús Ulises Liceaga-Castro ◽  
Rafael Escarela-Perez ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Real Time ◽  
Digital Simulation ◽  
Least Square ◽  
Recursive Least Squares ◽  
Rotor Speed ◽  
Recursive Least Square ◽  
Brushless Dc ◽  
Speed Controller ◽  
Two Stages

In this article, the parameter identification of a brushless DC motor (BLDC) is presented. The approach here presented is based on a direct identification considering a three-phase line-to-line voltage electromagnetic torque as function of the electric currents and rotor speed. The estimation is divided into two stages. First, the electrical parameters are estimated by well-known no-load and DC tests. Consequently, estimation of mechanical parameters is performed using a recursive Least Square Algorithm. The proposed approach is validated by comparing model responses to motor real time responses. Additionally, the design, digital simulation and real time implementation of a PI rotor speed controller, based on the estimated model, validate the identification proposal presented here.

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