L. M. Waghmare

Tuning PID controllers for higher-order oscillatory systems with improved performance

In this paper, model based design of PID controllers is proposed for higher-order oscillatory systems. The proposed method has no limitations regarding systems order, time delays and oscillatory behavior. The reduced model is achieved based on third-order modeling and selection of coefficients through the use of frequency responses. The tuning of the PID parameters are obtained from a reduced third-order model; the procedure seems to be simple and effective, and improved performance of the overall system can be achieved. Three simulation examples and one real-time experiment are included to demonstrate the effectiveness and applicability of the proposed method to systems with oscillatory behavior.

Diving Autopilot Design for Underwater Vehicles Using an Adaptive Neuro-Fuzzy Sliding Mode Controller

In general, the diving dynamics of an autonomous underwater vehicle (AUV) has been derived under various assumptions on the motion of the vehicle in vertical plane. Usually, pitch angle of AUV is assumed to be small in maneuvering, so that the nonlinear dynamics in the depth motion of the vehicle could be linearized. However, a small-pitch-angle is a somewhat strong restricting condition and may cause serious modeling inaccuracies of AUV’s dynamics. For this reason, many researchers concentrated their interests on the applications of adaptive control methodology to the motion control of underwater vehicle. In this chapter, we directly resolve the nonlinear equation of the AUV’s diving motion without any restricting assumption on the pitch angle in diving model. The proposed adaptive neuro-fuzzy sliding mode controller (ANFSMC) with a proportional + integral + derivative (PID) sliding surface is derived so that the actual depth position tracks the desired trajectory despite uncertainty, nonlinear dynamics and external disturbances. In the proposed control structure, the corrective term is approximated by a continuous fuzzy logic control and the equivalent control is determined by a feedforward neural network. The weights of the neural network are updated such that the corrective control term of the ANFSMC goes to zero. The adaptive laws are employed to adjust the output scaling factor and to compute PID sliding surface coefficients. Finally, the lyapunov theory is employed to prove the stability of the ANFSMC for trajectory tracking of diving behaviors. Simulation results show that this control strategy can attain excellent control performance.

Design of decentralized controllers for MIMO processes

In this paper, the design of decentralized PID controller for interactive and delay time processes is proposed. Direct controller synthesis approach is used to obtain parameters of the multi-loop controllers. A detuning factor for each loop is specified based on the closed-loop time constant. Then appropriate controller settings are determined using the Maclaurin series expansion and the model of the process. The success of the proposed algorithm is based on the detuning parameter thus the selection of the desired closed-loop time constant is an important factor. The proposed method has no limitations regarding systems weak or strong interactions, multiple delays, and its operating behaviors such as monotonic or oscillatory. The proposed algorithm is simpler and improved performance of various processes are achieved as compared to some of the prevalent techniques. Simulation examples demonstrate the usefulness of the proposed method.

An Automated Segmentation Method For Iris Recognition

Segmentation is of vital importance in iris based identification. This paper presents a straightforward approach for segmenting the iris. The method determines an automated threshold for binarising and determining the pupil center, based on a histogram of gray scale image and after which the iris is segmented. To access the methods efficacy, this method is applied to a database of 756 images. After segmentation, 160-byte code is extracted from normalized image, which is used for identification

Task Space Control of an Autonomous Underwater Vehicle Manipulator System by Robust Single-Input Fuzzy Logic Control Scheme

In this paper, a robust single-input fuzzy logic control Robust Single Input Fuzzy Logic Controller (RSIFLC) scheme is proposed and applied for task-space trajectory control of an autonomous underwater vehicle manipulator system (AUVMS) employed for underwater manipulation tasks. The effectiveness of the proposed control scheme is numerically demonstrated on a planar underwater vehicle manipulator system [consisting of an underwater vehicle and a two link rotary (2R) serial planar manipulator]. The actuator and sensor dynamics of the system are also incorporated in the dynamical model of an AUVMS. The proposed control law consists of a feedforward term to exaggerate the control activity with immoderation from the known desired acceleration vector and an estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics as a first part and a single-input fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system as a second part. The primary objective of the proposed control scheme is to track the given end-effector task space trajectory despite of external disturbances, system uncertainties, and internal noises associated with the AUVMS. To show the efficacy of the proposed control scheme, comparison is made with conventional fuzzy logic control (CFLC), sliding mode control (SMC), and proportional–integral–derivative (PID) controllers. Simulation results confirmed that with the proposed control scheme, the AUVMS can successfully track the given desired spatial trajectory and gives better and robust control performance.

An iris recognition based on dual tree complex wavelet transform

With an increasing emphasis on security, automated personal identification and verification based biometrics has been receiving extensive attention over the past decade. The iris images captured from the same person or different persons differ in size due to illumination variations and other factors. The iris recognition system is composed of many steps. Namely, capturing the iris patterns; determining the location of the iris boundaries; converting the iris boundary to the polar coordinate system; extracting the iris code based on wavelet transforms; and classification of the iris code. There are many methods proposed for iris recognition by many researchers. The proposed system based on dual tree complex wavelet transform for iris recognition system with high performance and acceptance/rejection capabilities is described.

Voltage flicker assessment of induction motors used in the integrated water pumping station

Now a days flicker estimation is one of the necessary tasks in assessment of flicker emission level for the connection of fluctuating loads to electric power systems. This paper suggests a method under the scope of IEC rules for estimating short time voltage flicker (PST) severity on a 22/3.3 kV network for supplying an induction motor bearing load for the municipal integrated water pumping system. Measurements are done to identify background voltage flicker levels and the contribution of the already operating induction motors at the point of common coupling. In this paper, above system is simulated using Matlab-7.01, which help in presenting the detailed results of all the voltage flickers compensating methodologies. It analyses and compares performances of different flicker mitigation methodologies for this particular application. It has been found from simulated results that the average flicker emission level has reduced to approximately 34% of its initial level.

Fuzzy Adaptive Controllers for Speed Control of PMSM Drive

ABSTRACT The objective of the Fuzzy Adaptive Control (FAC) is to tune the scaling factors of the direct fuzzy logic controller (FLC). In this novel approach output scaling factor of Fuzzy controller is tuned through adaptation mechanism. The idea is to have a control system that will be able to achieve improvement in tracking set point change and rejection of load disturbance. In this paper, the proposed Fuzzy Adaptive Controller is applied to a permanent magnet synchronous motor drive (PMSM). High performances and robustness have been achieved by using the FAC. This will be illustrated by simulation results and comparisons with other controllers such as PI; classical and fuzzy adaptive controller based on tuning of input and output scaling factors. The performance criteria selected is quadratic performance criteria in terms of Rise Time (RT), Settling Time (ST), Integral of square error (ISE) and Integral of absolute error (IAE). Categories and Subject Descriptors

Quality of service analysis in wireless sensor network by controlling end-to-end delay

The delay sensitive industrial control applications like Industrial process control, Environmental control, Gas leakage monitoring, etc. in this a reliable communication between sensor and base station are highly essential. Wireless Sensor Networks (WSN) becomes an immensely popular technology in such application as it offers low latency and high energy-efficiency in message transmission. Life span of the network can be extended by using appropriate energy efficient routing protocol. The three standard routing protocols, namely Ad-hoc On-Demand Distance Vector, Destination Sequence Distance Vector and Ad-hoc On-demand Multipath Distance Vector have been analyzed. In this work we have proposed multi-sink model to compare with conventional single sink model. We have designed probabilistic model to compare transmission delay in these two models. They are also compared with IEEE802.11 and IEEE802.15.4 MAC protocol. The proposed WSN model is analyzed by estimating end-to-end delay, energy consumption and packet drop ratio of both models. NS-2 simulator is used for result analysis in different traffic conditions. The Quality of Service can be improved by minimizing delay in packet delivery of the network. It has been observed that overall delay can be minimized significantly in proposed model.

Algorithmic Trading (AT) - Framework for Futuristic Intelligent Human Interaction with Small Investors

Algorithmic trading has become more popular with large institutional investors these days. Big investment giants and top corporate notches are taking undue advantage of these algorithms over small investors. The one of the most critical factor which is limiting small investors to use these algorithms is lack of interactive user interface. This paper proposes a framework for intelligent interaction of these trading algorithms with the user which maintains required user adaptability, modeling and knowledge sharing in the coming future. Further the paper discuss about the various trading algorithms, their areas of concern and its likely impact on the market presently and in coming future. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org