Good Disturbance Rejection Research Articles

Fractional order PID control design for semi-active control of smart base-isolated structures: A multi-objective cuckoo search approach

Fractional order PID (FOPID) controllers are introduced as a general form of classical PID controllers using fractional calculus. As this controller provides good disturbance rejection and is robust against plant uncertainties it is appropriate for the vibration mitigation in structures. In this paper, an FOPID controller is designed to adjust the contact force of piezoelectric friction dampers for semi-active control of base-isolated structures during far-field and near-field earthquake excitations. A multi-objective cuckoo search algorithm is employed to tune the controller parameters. Considering the resulting Pareto optimal front, the best input for the FOPID controller is selected. For seven pairs of earthquakes and nine performance indices, the performance of the proposed controller is compared with those provided by several well-known control techniques. According to the simulation results, the proposed controller performs better than other controllers in terms of simultaneous reduction of the maximum base displacement and story acceleration for various types of earthquakes. Also, it provides acceptable responses in terms of inter-story drifts, root mean square of base displacements and floor acceleration. In addition, the evaluation of robustness for a stiffness uncertainty of ±10% indicates that the proposed controller gives a robust performance against such modeling errors.

A Nonlinear Three-Phase Phase-Locked Loop Based on Linear Active Disturbance Rejection Controller

Three-phase phase-locked loops (PLLs) are the most widely used synchronization components in power systems. For common PLL algorithms, there is a tradeoff between the filtering capability and dynamic response. In this paper, a nonlinear PLL (NLADRC-PLL) based on a linear active disturbance rejection controller (LADRC) is proposed to largely improve this tradeoff, thus simultaneously enhancing the filtering capability and dynamic response. With LADRC adopted in PLL structures (LADRC-PLL), good dynamic response and disturbance rejection capability can be achieved. To pursue further improvements in both filtering capability and dynamic response, the NLADRC-PLL derived from the LADRC-PLL is proposed, which adjusts the controller gains adaptively according to the disturbance. It is commonly known that there are stability problems for PLLs with adaptive controller gains, which are highly nonlinear systems. Thanks to the great robustness of LADRC structures, the stability of the proposed NLADRC-PLL is certified by the second method of Lyapunov in the nonlinear model. By comparing its PLL performance with the existing PLL algorithms, the superiority of the NLADRC-PLL in both filtering capability and dynamic response is verified through experimental results.

Novel Observer Scheme of Fuzzy-MRAS Sensorless Speed Control of Induction Motor Drive

This paper presents a novel approach Fuzzy-MRAS conception for robust accurate tracking of induction motor drive operating in a high-performance drives environment. Of the different methods for sensorless control of induction motor drive the model reference adaptive system (MRAS) finds lot of attention due to its good performance. The analysis of the sensorless vector control system using MRAS is presented and the resistance parameters variations and speed observer using new Fuzzy Self-Tuning adaptive IP Controller is proposed. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The present approach helps to achieve a good dynamic response, disturbance rejection and low to plant parameter variations of the induction motor. In order to verify the performances of the proposed observer and control algorithms and to test behaviour of the controlled system, numerical simulation is achieved. Simulation results are presented and discussed to shown the validity and the performance of the proposed observer.

Fuzzy Disturbance Rejection Control of Two Link Robot Manipulator

It is well known that robotic manipulators are nonlinear coupling dynamic systems. The control strategy is fuzzy logic technique to cope with the model parameter disturbances. The simulation is implemented to verify the effectiveness of the proposed fuzzy control policy. From the simulation results, strong robustness, fast response, good disturbance rejection capability and good tracking capability can be obtained. It is also illustrated from simulation results that the proposed control technique is valid for the two-link robot manipulator.

A Polynomial Current Controller for a Third-Harmonic Modulated Power Factor Correction Rectifier Feeding a Vector Controlled Induction Motor Drive

This paper presents the analysis, design, and hardware implementation of a digital polynomial Regulation, Steady-State Error and Tracking (RST) current controller-based third-harmonic modulated boost-type power factor correction (PFC) rectifier. The proposed rectifier is used at the front end of a vector controlled induction motor drive (VCIMD) to eliminate harmonics at the input AC supply. The proposed PFC rectifier modifies the input current to a sinusoid with unity power factor apart from offering DC bus voltage regulation. In this paper, a digital proportional-integral (PI) and RST current controllers are compared in terms of total harmonic distortion (THD) and power factor (PF) at the point of common coupling for different loading conditions. The RST current controller tracks the set-point accurately with zero steady-state error and offers good disturbance rejection that enables further reduction of supply current THD as compared to a conventional PI current controller. The control algorithm for the PFC front end rectifier along with vector control technique is implemented using a digital signal processor, and the dynamic performance is analyzed for step changes in reference speed and load torques, demonstrating significant improvement in the performance indices.

Internal model control based PID tuning using first-order filter

The selection of filter plays an important role in internal model control (IMC) based controller design. As per the rule, for a minimum-phase delay free plant, IMC based controller is obtained by augmenting a filter. We suggest the use of first-order filter for controller design, which is then parameterized to a conventional PID controller. The proposed scheme brings filter size reduction, closed-loop bandwidth enhancement, and easy formulation of the PID structure. The proposed scheme is applied to some class of linear and nonlinear processes. Further the hardware testing for velocity control of precision modular servo system which contains DC servomotor is carried out through this scheme. Quantitative comparison of servo, regulatory and optimal attributes of the proposed scheme with other popular IMC-PID control techniques depicts sharp reference tracking, good disturbance rejection and minimum integral error performance.

On-line Monitoring and Control of Fed-batch Fermentations in Winemaking.

The fermentation of yeast in fed-batch mode shows great potential in winemaking because it allows the concentration of sugars to be kept low and constant throughout the process which, in turn, reduces cell stress and leads to a significant decrease in the production of unwanted secondary metabolites. The implementation of this technique requires reliable on-line analysis of sugar and a robust control strategy to maintain sugar concentrations at defined levels over the course of the fermentation. In this study, a laboratory-scale setup was used to implement and assess a fully automated fed-batch fermentation of Saccharomyces cerevisiae in grape must. Total sugar levels were monitored in-line by FT-MIR ATR spectroscopy and kept constant at 50 g/kg by a modified PI controller regulating the must feed flow rate. Good setpoint tracking and disturbance rejection were achieved in fermentations of up to four days despite occasional yeast sedimentation on the ATR crystal. The controller parameter adaptation strategy needs to be optimized for longer fermentations.

Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots

ABSTRACTThis paper presents methodologies for the identification and control of 6-degrees of freedom (6-DoF) cable-driven parallel robots (CDPRs). First a two-step identification methodology is proposed to accurately estimate the kinematic parameters independently and prior to the dynamic parameters of a physics-based model of CDPRs. Second, an original control scheme is developed, including a vision-based position controller tuned with the H∞ methodology and a cable tension distribution algorithm. The position is controlled in the operational space, making use of the end-effector pose measured by a motion-tracking system. A four-block H∞ design scheme with adjusted weighting filters ensures good trajectory tracking and disturbance rejection properties for the CDPR system, which is a nonlinear-coupled MIMO system with constrained states. The tension management algorithm generates control signals that maintain the cables under feasible tensions. The paper makes an extensive review of the available methods and presents an extension of one of them. The presented methodologies are evaluated by simulations and experimentally on a redundant 6-DoF INCA 6D CDPR with eight cables, equipped with a motion-tracking system.

Grey wolf optimization for PID controller design with prescribed robustness margins

The grey wolf optimization algorithm is proposed to design proportional, integrative and derivative controllers using a two degrees of freedom control configuration. The control system is designed in order to achieve good set-point tracking and disturbance rejection performance. The design is accomplished by minimizing an aggregated cost function based on the time-weighted absolute error integral, subjected to robustness constraints. The control system robustness levels are prescribed in terms of the vector margin and maximum complementary sensitivity function values. Simulation results are presented for several common systems dynamics and compared with the ones obtained with a particle swarm optimization algorithm.

A new control method based on type-2 fuzzy neural PI controller to improve dynamic performance of a half-bridge DC–DC converter

Due to nonlinear behavior and the uncertainty with converter structure, controller design is difficult and accompanied with complexities. In this paper, a new control method based on Type-2 fuzzy neural PI (T2FN PI) controller is applied to improve the dynamic response of half-bridge DC–DC converters for different operation conditions. The T2FNN PI controller amends the specifications of the converter system by controlling its duty cycle of switching. In addition, proposed controller can property handle the uncertainty which is associated to converter structure, measuring devices and measured control signals.The T2FN PI controller is a combination of type-2 fuzzy linguistic process and neural network learning capability. The back-propagation algorithm is applied to train the parameters of T2FNN PI controller. Furthermore, PSO algorithm is applied to obtain the T2FN PI training pattern.In order to evaluate the performance of the proposed T2FN PI controller, it has been compared with a Fuzzy controller and the conventional PI controller for five different operating conditions. The simulation results show efficiency of the T2FNN PI controller in compare to Fuzzy controller and PI controller in terms of better rejection of disturbances, faster transient response and less peak overshoot.

Design of decentralized proportional–integral–derivative controller based on decoupler matrix for two-input/two-output process with active disturbance rejection structure

The framework of the active disturbance rejection internal model control is proposed to solve the problem of the model reduced-order error in the process of the controller design for two-input/two-output system with time delay. In the controller design process of the two-input/two-output system, the decoupler matrix method is used to decompose a multi-loop control system into a set of equivalent independent single loops. Then, a complex equivalent model is obtained, and its order should be reduced for each individual loop. Maclaurin series method is used to reduce the order of the decoupling model. After reducing model order, the proposed method is applied to lessen the effect of the reduced-order error and improve the anti-interference ability and robustness for the control system. Simulation results show that the proposed method possesses a good disturbance rejection performance.

$$\hbox {H}_\infty $$ H ∞ and $$\upmu $$ μ synthesis control of virtual structure satellites formation flying

Recent developments in the space industry and the great tendency to define efficient, precise and low cost missions are the main reasons for the growing interest in satellites formation flight. Regarding the aforementioned, the study of multiple satellites control methods is the subject of the present paper. In this paper, two linear robust control strategies are applied to position control system of certain satellites in the virtual structure formation flight. The proposed controllers are designed considering different parametric uncertainties such as semimajor axis and eccentricity changes as well as some disturbances like second term of gravitational acceleration function (\(j_{2}\)) and drag acceleration which are resulted in asymmetrical shape of the Earth and low density atmosphere in high altitude. In the presence of all parametric and un-modeled dynamic uncertainties, the robust stability and performance of the nonlinear system are guaranteed and good tracking, disturbance and noise rejection characteristics are achieved. Computer simulations show that these approaches have very promising performance when position controllers are applied with PWPF modulators while they are working in their pseudo linear range.

Data driven nonparametric identification and model based control of glucose-insulin process in type 1 diabetics

Closed loop control of glucose homeostasis via subcutaneous insulin infusion and continuous glucose monitoring system can give better living to a type 1 diabetic patient. This paper deals with the real time implementation of internal model control (IMC) of subcutaneous insulin infusion. The model based control is applied on the nonparametric model of the patient identified in real time from input–output data. Meal simulation model of the glucose-insulin system of type 1 diabetic patient based on the work of Dalla Man et. al. is considered. This model is constructed in hardware platform that acts as the virtual patient. The data-driven nonparametric model of the virtual patient is identified in real time by computing Volterra kernels. The kernels are solved up to second order using recursive least squares (RLS) algorithm with short memory length of M=2. The validation results of the identified model output and the actual output have shown good fit in both simulation and real time environments. The frequency domain kernels are used in internal model control to generate insulin dosage. The control algorithm is developed in simulation and implemented in real time with hardware in loop on dSPACE platform. The closed loop system yields good meal disturbance rejection, less undershoots, settling time and more profoundly smaller requirement of insulin infusion as compared to the earlier reported data.

Adaptive predictor control for stabilizing pressure in a managed pressure drilling system under time-delay

In this paper, we address adaptive predictor feedback design for a simplified ODE drilling system in the presence of unknown parameter, disturbance and time-delay. The main objective is to stabilize the bottomhole pressure at a critical depth at a desired set-point directly. The time-delay in the transmission line of the drilling systems is considered. The stabilization of the dynamic system and the asymptotic tracking are demonstrated by the proposed predictor control, where the adaptation employs Lyapunov update law design with normalization. The proposed method is evaluated using a high fidelity drilling simulator and cases from a North Sea drilling operation are simulated. The results show that the proposed predictor controller is effective to stabilize the bottom hole pressure within the desired bound and compensate the effects of the delay in MPD. The simulation also shows that the proposed method provides good tracking, good disturbance rejection, and good compensation of time-delay.

Designing an optimized model-free controller for improved motion tracking by rugged electrohydraulic system

Electrohydraulic actuation systems with proportional valves and industry-grade cylinders have widespread use due to their low cost and ease of maintenance. Achieving good tracking of output position of the piston in such a system by a proper controller design is the objective of this study. Due to various parameter uncertainties and complex nonlinearities like piston friction, valve deadband and flow characteristics, the variation of oil property with working temperature and air entrapment volume, the implementation of a model-based control becomes quite difficult for such systems. A notable contribution of this work is to couple a model-free fuzzy controller with a feedforward controller with all the parameters estimated by a real-coded genetic algorithm. Also, the optimizer has been used for identifying an appropriate fuzzy structure that is easy to implement in real time. A comprehensive experimental study has revealed the best fuzzy structure to be achieved through a Gaussian fuzzification of linear combination of the position and velocity errors as the input and singleton membership function for the output voltage actuating the proportional valve. Excellent responses with good disturbance rejection capability and energy efficiency have been achieved. These responses have emerged superior to those achieved in a similar system with different controller structures and in systems with much costlier components.

Improved Dynamic Behavior in BLDC Drives Using Model Predictive Speed and Current Control

Model-based predictive control is a powerful control strategy to drive electrical machines. Conventional cascade proportional–integral (derivative) [PI(D)] controllers are often used to control speed, torque, and current. However, for low-inertia machines, achieving a high-performance and wide speed range is far beyond the application conditions for which these controllers are designed for. Using two cascaded PI(D) controllers for the speed/current control of a low-inertia machine, changes in the speed set point should be slowly applied in order to avoid stability problems. In this paper, a model predictive control algorithm that is able to control the speed of a low-inertia brushless direct-current machine with a high bandwidth and good disturbance rejection properties is proposed. The algorithm is implemented on a SPARTAN 3E 1600 field-programmable gate-array board, and experimental results verify the performance of the proposed algorithm.

ESO Based LQR Controller for Ball and Beam System

Abstract This paper presents an ESO based Control design for ball and beam system which is one of the most sought after problem for control engineering students. The system comprises a long beam which is moved by using servo motor and a ball on which it rolls with respect to Beam motion. In this design, estimation of a virtual state (“disturbance”) is carried out online with state observer and these states are used in controller to nullify the effects of actual disturbances and uncertainties in the plant. While designing controller, simpler model is used, thus avoiding accurate modeling of the system. Any nonlinear term and unknown parameter in the plant can be considered as internal or external disturbance. This is the peculiar feature of automatic disturbance rejection control or ESO based control scheme. Hence, linearized model of ball and Beam is considered. All simulations have been carried out with the help of MATLAB and SIMULINK. Using this algorithm, controller shows very good disturbance rejection capability and it has been shown with simulation results.

Anti-disturbance autopilot design for missile system via finite time integral sliding mode control method and nonlinear disturbance observer technique

In this paper, a composite anti-disturbance autopilot design for a missile system is proposed based on finite time integral sliding mode control scheme and nonlinear disturbance observer technique. First, a nonlinear disturbance observer is developed to estimate the external disturbances with partial known information. Second, in order to obtain good disturbance rejection performance and reject the other type of disturbances, a finite time integral sliding mode control strategy is employed to the design of a feedback controller. Third, an improved adaptive composite anti-disturbance autopilot is given to avoid the inaccuracy of the upper bound of external disturbances. Finally, simulation results are employed to demonstrate the effectiveness of the proposed method.

The Design of the Simple Structure-Specified Controller of Magnetic Bearings for the High-Speed SRM

Magnetic bearing system controllers using H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> algorithms provide excellent interference rejection capability and robustness. However, in the conventional H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control design, the order of the controller is much higher than that of the plant, making implementation in practical engineering applications difficult. To solve the problem, based on the requirements of the theory of mixed sensitivity design method, this paper designs a simple structure-specified controller of magnetic bearings for the highspeed magnetic levitated switched reluctance motor (SRM) using backpropagation neural network function approximation characteristics. The proposed controller is of lower order than the traditional H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller, and meets performance of H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller, which is more suitable for practical implementation. By contrast with the traditional mixed sensitivity controller, results of simulations verify that the controller is reasonable. The controller is applied on the high-speed magnetic levitated SRM platform, and experimental results verify that the controller can achieve control of magnetic bearing systems with good disturbance rejection and robustness.

Robust Design of PID Controller Using IMC Technique for Integrating Process Based on Maximum Sensitivity

The aim of this work was to obtain a design for the proportional integral derivative controller in series with a second-order lead/lag filter for pure integrating process with time delay based on internal model control principle to achieve efficient disturbance rejection and robustness. A setpoint filter is introduced to reduce the overshoot in the setpoint response. Further, the robustness of the controller is examined by incorporating perturbations in the time delay parameter for model mismatch. The proposed method demonstrated good disturbance rejection and robustness in comparison with recently developed methods with the controller tuned to have same robustness rank with the calculation of the peak of maximum sensitivity $$(M_S )$$ .