Sharad P. Jadhav

Robotics based simultaneous localization and mapping of an unknown environment using Kalman Filtering

In this paper, Robotic application using a microcontroller ATmega2560 based kit mounted with low cost IR sensors for mapping and localization of unknown area is accurately carried out by using Kalman Filtering to determine or measure different parameters. This paper highlights the comparison between the accuracies of output data obtained from IR sensor using Average Technique as well as Kalman Filter. Various cases depending on robot movement in forward and backward direction and wheel rotation in clockwise and anticlockwise direction, are considered in this paper to calculate position encoder resolution. Also probabilistic estimation of actual position of robot is carried out using different techniques i.e Probability Density Function (P.D.F) for verifying the uncertainty in its position and found to be very close to actual position. Simultaneous Localization And Mapping (SLAM) is the only way a robot can navigate through an unknown environment with the use of minimum sensors and get reliable output of the same in identifying an unknown area. Using this method the robot not only create a map more accurate than GPS maps but also localize itself to determine its next position according to the map created more accurately at lower cost. Primarily used for creating a map of an unknown location, this concept can also be used to perform Qualitative Analysis of a given area by equipping the robot with appropriate sensors.

Development and analysis of wireless controlled batch process system using ARM

In automation industry, wired communication tends to bring ample hurdles in building a flexible and fast response system. Wireless technologies are always best solution against investment, speediness and remoteness requirements for implementing an efficient and appropriate technology or system. A prototype model of wireless controlling and monitoring of batch process system consisting ARM controller for real-time data acquisition of temperature and level of a liquid in a tank is presented. Here PC-based GUI is developed for process controlling and monitoring. Wireless communication is developed and secured via zigbee protocol. Some major Challenges and concerns regarding wireless communication and safety in industrial environment are discussed. In this paper, we have implemented a wireless system with integration of sensors and control elements providing a solution for automated monitoring, operating and control of batch process. The proposed approach can usher utilities like well structured optimal control, minuscule software code and reduced debugging requirements in application point of view.

Modeling and Design of Fractional-Order IMC Based Controller for Power Plant Gas Turbine

Fractional-order modeling and controller design by a simplified way is the demanding research area and is gearing more and more momentum. This paper is the attempt of application of fractional-order modeling and controller design for the power plant gas turbine. The Gas Turbine is most important equipment in power, aviation and automotive industry. It converts the thermal energy of fuel into the mechanical power. Therefore, important requirement of gas turbine system is to control the flow of input fuel. The existing identified model of the gas turbine between the input fuel flow and the output speed, is of high-order and integer type, which is reduced to the simple and compact integer-order (IO) and fractional-order (FO) models using local optimization technique. The fractional-order internal model controller (FO-IMC) is designed and to show the performance efficacy it is compared with integer-order internal model controller (IO-IMC), which is also designed using the same methodology and specification. Simulation results show that FO-IMC based controller gives better performance for the set point tracking, plant uncertainty and disturbance rejection than the IO-IMC. FO-IMC controller also satisfy the robust stability condition.Copyright

Comparative study of Fuzzy and IMC based controllers for heat exchanger system

This paper presents the comparative study of PID, Fuzzy logic and Internal model based controller for heat exchanger system. The H.E. system plays a dynamic role in process industry. The performance of heat exchanger is largely depending upon the outlet fluid temperature. The selected heat exchanger system is intended to control the temperature of outlet fluid to a desired set point despite of different disturbances like fluid flow variations and fluctuations in input fluid temperature. The input fluid and inlet steam are the input parameters and outlet temperature of the fluid is the output parameter. Outlet fluid temperature is the controlled by manipulating the inlet steam flow. Whereas the deviation produced in input fluid flow is considered as one of the effective and dominant disturbance. Conventional PID controller is commonly used to control the output temperature. It has its own drawbacks and cannot handle the disturbance properly overall performance of PID is not satisfactory. This report is an attempt to design advanced controller like FLC and IMC for heat exchanger system. To design this controller, the mathematical modeling of H.E. is studied theoretically. Its component wise model is developed in MATLAB Simulink for this developed model, FLC has designed with different membership functions and Mamdani and Takagi-Sugeno (TS) method, and its performance is compared with PID. Further for the same model IMC controller is designed. The performance of PID, FLC and IMC is compared in MATLAB Simulink environment. The performance of IMC controller is superior to PID and FLC. It successfully tracks the set point and handles the disturbances.

Data Acquisition analysis in SLAM applications

The Simultaneous Localization and Mapping (SLAM) problem for mobile robots aims at consistently building a map of an unknown environment while simultaneously determining its position or location within this map. From a control-theory viewpoint, it is somehow analogous to simultaneously estimating the states and output map of the system. In the robotic based engineering applications, SLAM is arguably considered a solved problem on a theoretical and conceptual level, but still it requires considerable maturity on a practical level [16][22]. The state-of-the-art SLAM algorithms require computationally powerful processors, expensive sensors with dense feature extraction and multiple sensors for uncertainty reduction [21]. An approach to the SLAM problem using minimal sensing information is still lacking in both theoretical and practical aspects. This paper highlights the data acquisition & association issues with different sensors like odometric & infra red sensors used in SLAM application due to addition of random Gaussian noise leading to errors & uncertainty in mapping processes [17][22]. Simple filtering techniques using average filtering & Kalman filtering have been implemented on the acquired data to go for comparative analysis of sensor performance & its impact on SLAM process towards reduction in uncertainty or minimal shift in landmark extraction [19].

Reduced-parameter fractional-order modeling of large dynamical system: Application to Gas Turbine

Nowadays, gas turbines are popularly used for power generation. Widespread installations and the dynamic nature of this system has increased the necessity of its accurate modeling and control. It is a large and complex dynamical system and exact identification of its parameters like temperature and speed are the important issues. Noticeable research activities are going on so far in this field in order to understand and simplify the nonlinear behavior of these complex systems. However, the need for simple and compact models has been a strong motivation for researchers. Most of the advanced controllers are model based, if model is bulky or having large parameter then controller design become tedious and time consuming. Online implementation of such model driven strategy is also the main concern. Further it results in sluggish operation and also deteriorates the closed loop performance. Hence simplified and compact model is an important requirement. This paper proposes, application of fractional calculus theory to find compact model of gas turbine. A simple and compact fractional-order models are obtained using parameter reduction technique. A local optimization problem is posed to represent large parameter integer-order systems by few parameters fractional-order models. The dynamics of original system are retained in compact fractional-order models because of its memory type nature. Results shows that the proposed models completely represent the dynamic of large parameter integer-order system.

Design and simulation of Fuzzy and Fuzzy-PI controller for speed of Gas Turbine

In this paper, fuzzy and fuzzy-PI controllers are designed to control the rotor speed of Gas Turbine (GT). The goal of the presented controllers is to keep the turbine rotor speed within predefined limits during startup as well as during operating condition. For speed loop output rotor speed is controlled variable and inlet fuel flow rate is manipulating variable. The fuzzy controller and fuzzy-PI controller are designed using Takagi-Sugeno method and Mamdani method, respectively. In applying the fuzzy-PI control to a gas-turbine plant, the tuning parameters (KP and KI) are modified online by a fuzzy logic approach. Error and rate of change of error are inputs and change in fuel flow is output for both the controllers. Also, the constraints on the inlet fuel flow and output rotor speed are taken into account. The existing linear model of GT available in the literature is considered to design the speed controllers. The performance of Fuzzy and Fuzzy-PI controller is tested in the MATLAB Simulink environment. During simulations, the demand power is taken as disturbance input. The performance of the proposed controllers is compared with each other as well as with H∞ robust and MPC controllers for the same operating conditions. From the obtained results, it is observed that fuzzy controller reduces the overshoot and settling time as compared with MPC and H∞ controller. Fuzzy-PI controller response is better than MPC and fuel constraint is maintained in a smoother way. Fuzzy and Fuzzy-PI controllers can be considered as the options for the speed control of GT.

Design and implementation of remote triggered LabVIEW based PI controller for level setup

This paper presents an application by integrating theories through an experimental setup. In the literature it is found that, researchers designs advanced controllers and presents only simulation results. The motivation here is in-house design and fabrication of level setup and understands the practical difficulties in the real time implementation of software based controllers. They are easy for programming, monitoring and gives platform to develop GUI for mimic the process. This work is the sincere effort to design and real time implementation of LabVIEW based PI controller for laboratory purpose level setup. The mathematical model of the level system is obtained using process reaction curve method and NI ELVIS-II hardware is used as an interface. Tuning methods like Ziegler Nichols, Cohen Coon are considered for smooth control of dynamic level. The performance of simulated and realtime PI controller for different scenario are presented and it is observed that the time domain parameters are in close agreement. Also, a facility of remote triggering of this setup is developed using LabVIEW web server applications.

Design and implementation of fuzzy and neuro-fuzzy controller for mobile robot navigation

This paper investigates design and implementation of controller for robot navigation in real time. The proposed system use sensor input to yield wheel velocities. The novel algorithm is developed to find the range of the mobile robot from obstacle and perform the controlling action by using the Arduino board. Simulation results of Fuzzy, neural and neuro- fuzzy system were compared in this paper. Result shows the effectiveness of the proposed system in various kind of obstacle environment.

Development of wireless embedded automation system for batch process

Presently industrial automation is growing rapidly emphasizing on centralized monitoring and independent control of sub-systems. This increases the number of remote sub-systems, which need intermediate communication. Another challenges observed are the reduction of system size and the maintenance cost with flexibility in operation. Regulatory, repetitive sequential control and interlocking are the typical mandatory requirements for batch execution and safety. This paper presents development and analysis of prototype system for wireless controlling and monitoring of the batch process experimental set-up. It proposes the efficient utilization of ARM micro-controller for the real-time monitoring and control of temperature and level. A graphical user interface using Visual Studio.NET is developed to operate the plant remotely. This facilitates the user to control, supervision and data acquisition through wireless communication between laboratory set-up and user interface via ZigBee protocol. Sensitivity and linearity analysis of RTD output and ultrasonic level sensor output is carried out citing fair linearity of RTD and level sensors calibration. Additionally errors in calculated and observed output at ADC are also investigated. The normal operation and safety interlocks have been identified, executed & validated to mitigate the hazardous events in plant considering the possibility of failure of temperature and level sensors. The proposed system is developed successfully and works in defined manner with overall satisfactory performance.