Smith predictor with sliding mode control for processes with large dead times

The paper discusses the Smith Predictor scheme with Sliding Mode Controller (SP-SMC) for processes with large dead times. This technique gives improved load-disturbance rejection with optimum input control signal variations. A power rate reaching law is incorporated in the sporadic part of sliding mode control such that the overall performance recovers meaningfully. The proposed scheme obtains parameter values by satisfying a new performance index which is based on biobjective constraint. In simulation study, the efficiency of the method is evaluated for robustness and transient performance over reported technique

A single-step identification strategy for the coupled TITO process using fractional calculus

The reliable performance of a complete control system depends on accurate model information being used to represent each subsystem. The identification and modelling of multivariable systems are complex and challenging due to cross-coupling. Such a system may require multiple steps and decentralized testing to obtain full system models effectively. In this paper, a direct identification strategy is proposed for the coupled two-input two-output (TITO) system with measurable input–output signals. A well-known closed-loop relay test is utilized to generate a set of inputs–outputs data from a single run. Based on the collected data, four individual fractional-order transfer functions, two for main paths and two for cross-paths, are estimated from single-run test signals. The orthogonal series-based algebraic approach is adopted, namely the Haar wavelet operational matrix, to handle the fractional derivatives of the signal in a simple manner. A single-step strategy yields faster identification with accurate estimation. The simulation and experimental studies depict the efficiency and applicability of the proposed identification technique. The demonstrated results on the twin rotor multiple-input multiple- output (MIMO) system (TRMS) clearly reveal that the presented idea works well with the highly coupled system even in the presence of measurement noise

A Low Cost Linear Force Feedback Control System for a Two-Fingered Parallel Configuration Gripper

This paper presents a simple linear control based force feedback for the gripper of a SCORBOT ER-4u robotic arm. The SCORBOT ER-4u is a 5 degree of freedom (DOF) dexterous robotic arm with a rigid 2-fingered parallel configuration gripper. A Flexi-Force Force Sensitive Resistor (FSR) is attached to one of the claws of the gripper and interfaced to a notebook computer using Arduino Uno microcontroller. The force sensor aids the robotic arm in three different ways: one, senses if an object has been successfully grasped, second determine the coefficient of friction of the object, and third prevent damage when the object will be grasped. The gripper along with the force sensor is calibrated prior to grasping objects. During calibration, samples of the object to be manipulated are used to establish the extents of the gripper on the basis of its grasping force. By following calibration pattern, the gripper is able to grasp objects with approximately the same coefficient of friction. Most importantly, it ensures that the object to be grasped is not damaged by applying sufficient amount of force based on the object’s weight. The experimental analyses of the proposed work have shown interesting results to control both the SCORBOT ER-4u robotic arm and the force sensor for grasping masses, strictly conforming to the safety margin of the object

Fractional - order system modeling and its applications

In order to control or operate any system in a closed-loop, it is important to know its behavior in the form of mathematical models. In the last two decades, a fractional-order model has received more attention in system identification instead of classical integer-order model transfer function. Literature shows recently that some techniques on fractional calculus and fractional-order models have been presenting valuable contributions to real-world processes and achieved better results. Such new developments have impelled research into extensions of the classical identification techniques to advanced fields of science and engineering. This article surveys the recent methods in the field and other related challenges to implement the fractional-order derivatives and miss-matching with conventional science. The comprehensive discussion on available literature would help the readers to grasp the concept of fractional-order modeling and can facilitate future investigations. One can anticipate manifesting recent advances in fractional-order modeling in this paper and unlocking more opportunities for research

Smart Path Guidance Mobile Aid for Visually Disabled Persons

A traditional blind-navigation cane mostly used by a visually impaired person is not very appropriate mainly due to narrow search area. While a conventional cane warns of changes along the ground, it does not warn of other walking hazards and objects above a person’s waist. There are many electronics based blind-navigation devices employ a voice guided GPS (global positioning system) and/or complex high-order processor. It is apparent that the costs of these devices are too high that a common visually impaired people cannot afford them. In addition, a kind of previous arts is difficult to handle due to the weight, volume and functions incubated with basic purpose. Therefore, these types of advanced navigation systems are difficult to be commercialized. The purpose of this research is to design and develop a smart path guidance system for the blind and visually impaired, particularly the mobile aid to carry by hand, contains a smart sensor logic system. An appropriate model has developed for the selected design with embedding fuzzy logic decision. A presented solution is also tested for various condition inputs to verify the system’s behavior. Through several experiments, the sensors are calibrated to increase the accuracy of decision. The presented prototype enables the blind person to walk freely in an unfamiliar environment

Parametric identification of nonlinear fractional Hammerstein models

In this paper, a system identification method for continuous fractional-order Hammerstein models is proposed. A block structured nonlinear system constituting a static nonlinear block followed by a fractional-order linear dynamic system is considered. The fractional differential operator is represented through the generalized operational matrix of block pulse functions to reduce computational complexity. A special test signal is developed to isolate the identification of the nonlinear static function from that of the fractional-order linear dynamic system. The merit of the proposed technique is indicated by concurrent identification of the fractional order with linear system coefficients, algebraic representation of the immeasurable nonlinear static function output, and permitting use of non-iterative procedures for identification of the nonlinearity. The efficacy of the proposed method is exhibited through simulation at various signal-to-noise ratios

Generalized formulation to estimate the Supercapacitor’s R-C series impedance using fractional order model

The main objective of this paper is to develop a new technique for the supercapacitor’s parameter identification that can handle the issue of initial voltage. An effective approach is proposed using the fractional-order derivative for accurate identification of a well-known series Resistance-Capacitance (R-C) model. An expression is derived using the Caputo definition and the Haar wavelet operational matrix, which is sufficient for both charging and discharging phase data of supercapacitors. To extract impedance parameters, voltage stimulated step response is utilized and parameters are calculated despite random initial voltage stored in a supercapacitor. This operational matrix approach transforms complex fractional derivative terms into simple algebraic expressions and reduces the overall complexity. The proposed technique shows a very good agreement with experimental data that exhibit different initial voltages and different time-frames. Investigations and experiments with various supercapacitors clearly reveal the importance of the developed equation for a fractional R-C model

Improved control of integrating cascade processes with time delays using fractional - order internal model controller with the Smith predictor

This article proposes an enhanced control of integrating cascade processes. The importance of the scheme shows by controlling a double integrating process with time delay under significant parametric uncertainties and load disturbances. A novel design is proposed based on the Smith predictor principle and uses a fractional-order internal model controller in the outer loop. The required fractional-order tuning parameter follows the desired gain and phase margins. At the same time, another tuning parameter, such as the fractional filter’s time constant, is calculated from the desired performance constraint. Numerical analysis and comparison are performed to showcase the feature of the hybrid structure. The simulation results show that the fractional-order internal model controller–based scheme provides enhanced tracking and faster regulation capabilities and works well under nominal and parameter uncertainty conditions

The constraint optimization approach for robust PID design in AVR system

A constraint optimization approach is discussed for estimating the proportional-integral-derivative (PID) controller gains used for an AVR system. A new evaluation function is given to ensure the less variation in the control signal input to the system without compromising the overall dynamic responses. The robustness of the system is guaranteed by imposing the maximum sensitivity in solving the optimizing problem. The proposed method ensures the better performance even in the presence of the uncertainties in plant parameters. The simulation studies are presented to validate the design method