Vishal Goyal

Performance Boosting in IDMA System Using Helical Interleaver and Gold Codes

In Interleave Division Multiple Access (IDMA) scheme, interleavers have significant importance in the performance of whole system. In recent years interleavers have been proved to give the best performance in terms of data security and noise immunity, but huge memory requirement and complexity are major concerns for specifying the interleaver pattern. A new helical interleaver based IDMA system has already proposed due to some distinct advantages such as low system complexity and significant reduction in memory requirement as well. In this paper the performance of layer specific helically interleaved IDMA (HIDMA) system has been compared to randomly interleave and tree based IDMA with BPSK coding and with Gold Codes. Evaluation is done on the basis of mathematics and results are simulated in MATLAB.

A Discrete-Time Sliding Mode Controller for Time-Delay Linear Time-Invariant Systems with Uncertainty

This paper presents the Linear time invariant system with discrete time sliding mode control with modified switching function. The method is capable of handling both the systems with delayed states and control input delay. The simulation results are demonstrated with better asymptotic convergence in presence of static disturbance and robustness is justified.

Performance Analysis of PAPR Reduction in Helical Interleaved OFDM System

Orthogonal Frequency Division Multiplexing (OFDM) is one of the most promising technique for the fourth generation (4G) communication. High spectral efficiency, immunity to channel interference and nonlinear distortions are some advantages of OFDM. But frequency offset and high peak-to-average power ratios (PAPR) for large number of sub-carriers are two major drawbacks for practical application. This paper presents the PAPR reduction techniques for OFDM system such as interleaving and different phase rotation schemes. Selected mapping (SLM) and partial transmit sequence (PTS) are applied with mentioning distinct conditions for the application of these techniques. This paper also presents helical interleaver in OFDM system, for the reduction of system complexity and significant reduction in memory requirement as well. Evaluation is done on the basis of mathematical analysis and mentions best way to simulate in step-wise manner in MATLAB.

Adaptive Control of a Nonlinear Surge Tank-Level System Using Neural Network-Based PID Controller

A conventional Proportional–Integral–Derivative (PID) controller is not able to adapt to the changes in the system of a plant having nonlinear dynamics. In this paper, a Neural Network PID (NN-PID) controller is designed based on Multi-layer Neural Network (MLN) technique for controlling of the liquid level in a nonlinear surge tank system. A separate MLN identifier is implemented to approximate the plant’s dynamics which operates in parallel to the controller with disturbance and parametric uncertainties in the system. The NN-PID controller works using backpropagation algorithm and weights are updated according to the gradient descent based learning rule. The simulation results show that as the variations occur in the plant, MLN identifier follows the plant’s dynamics by adjusting its parameters and the controller reads just the plant’s output to the desired level by adjusting its own parameters. In addition to this, NN-PID controller response is much accurate and faster than the conventional PID controller and an improvement of 97.35% was achieved in terms of ISE.

Analysis of Parallel Control Structure for Efficient Servo and Regulatory Actions

This paper investigates an intriguing issue about the tuning aspects of the parallel control structures. This parallel control structure essentially decouples the servo action from the regulatory action and provides an opportunity to the control engineer for separately deciding the ability of the controllers for servo and regulatory action. This paper provides a thorough comparative study and thereby suggesting an appropriate combination of tuning rules for achieving better efficiency of the control structure. Three different well accepted tuning rules viz. Ziegler Nichols, Direct Synthesis (DS) and Gain Margin Phase Margin formulae have been considered and a critical analysis of the control tuning rules combinations have been performed. The performance of considered tuning rules combinations is assessed on the basis of a transient response criterion, i.e., overshoot, an error-based criterion, i.e., Integral of time-weighted absolute error for both setpoint and disturbance rejection, and a measure of controller output aggression, i.e., Integral of absolute rate of controller output. On the basis of performed studies for a first-order plus dead time system, it may be inferred that DS–DS tuning rule combination provided superior performance among all the considered cases for nominal as well as plant-model mismatch case.

Cooperative relay beamforming in IDMA communication networks

Abstract In this paper, a new combination of Interleave division multiple access (IDMA) and spatial diversity offered by cooperative relay aided distributed beam forming is proposed. In the offered scheme communication strategy consists two steps. All users broadcast their message to relays in the first step and then relays amplifies and forward the information to the desired destination. IDMA, which is popular non-orthogonal multiple access (NOMA) technique is used to combat the effect of multiple access interference (MAI) at relay as well as destination nodes. Each relay processed the signal to maintain the QoS of destination. The goal of this work is to find the appropriate beam forming weights by minimising the transmit power and without compromising the QoS in terms of SINR. However power minimization is not the convex problem, so semi-definite relaxation is used to modify the problem in to semi-definite programming (SDP) problem and the conventional SDP problem solver CVX is used for solution. The numerical explanation and simulation experiment of the proposed scheme shows the performance improvements in terms of bit error rate.

Sliding Mode Control of Uncertain Nonlinear Discrete Delayed Time System Using Chebyshev Neural Network

This paper investigates a Chebyshev Neural Network (CNN) sliding mode controller for stabilization of time-delayed version of system with uncertainty and nonlinearity. The nonlinearity in the system is unknown but bounded and has been approximated with the help of CNN. The input delay has been balanced and further converted into regular form and the original system is converted into a delayed free version with the help of Smith Predictor. Now, the predicted states of the system and “Gao’s reaching law” are used to derive the robust control law. Further, to prove the stability analysis Lyapunov–Krasovskii candidates has been chosen according to the proposed system. A numerical example is provided to illustrate the stability of the system in the presence of uncertainty, time delay and nonlinearity.

Stabilization of sliding mode controller for uncertain discrete-time-delayed nonlinear systems using descriptor approach

Control of nonlinear systems is vital due to wide range of their application. As it is obvious that the minimum requirement in any control system is the stability, however the proof of stability is not trivial in case of the nonlinear control systems. One of the best nonlinear control techniques is sliding mode control by applying a descriptor model transformation for bounding cross terms. Descriptor approach in sliding mode controller design for uncertain discrete time delayed nonlinear system is investigated in this paper.

A Discrete-Time Sliding Mode Controller with Modified Function for Linear Time-Varying Systems

This paper contains the linear time varying systems with discrete time sliding mode control with modified switching function. The changed sliding surface improves control input in the initial phase and reduces the chattering with improved robustness. Also the system state is uniformly eventually bounded with better asymptotic convergence under the existence of time varying disturbances.

Backstepping Control of Continuous Nonlinear Systems Using Chebyshev Neural Network

There are two types of system, one is linear and another one is nonlinear. For the control of linear systems there are several methods. Linear control theory is not directly applicable on nonlinear systems and there are so many approximations if linear control theory is directly applied on nonlinear systems. There is no unique method for analyzing nonlinear systems. A back stepping like design approach for reduced-order nonlinear observers is proposed. The basic idea of this approach is as follows. First, an appropriate function of the state variables to be estimated is constructed. The next function of the state variables to be estimated is then derived by designing the previous nonlinear function observer. Finally the procedure terminates, resulting in a partial differential equation to be solved. If the resultant differential equation is solvable, then the observer can be calculated. The connection between observers with linear error dynamics and this approach is discussed.