@christuniversity.in
Associate Professor
CHRIST(Deemed to be University)
MCA,MPhil,PhD
Data Analysis, Artificial Intelligence,Neural Network,Machine Learning,Business Intelligence and Medical Image Analysis
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
J. Chandra, G. Da Prato, D. Kannan, G. Ladde, E. Roxin, and M. Sambandham
Informa UK Limited
J. Chandra and G.S. Ladde
Elsevier BV
J. S. H. Tsai, J. Y. Lin, L. S. Shieh, J. Chandra, and S.-M. Guo
Oxford University Press (OUP)
A new methodology is presented to synthesize a digitally redesigned, active, self-tuning, fault-tolerant proportional–integral–derivative (PID) controller for multi-input–multi-output (MIMO) analogue systems to against partial actuator and system component failures. The fault-tolerant control (FTC) scheme possesses the ability to accommodate for system failures automatically and maintains the acceptable overall system performance in the event of partial actuator and system component failures. The theoretically well-designed analogue PID controller is refined using the continuous-time linear-quadratic regulator approach to have the high-gain property. Then, a predication-based digital redesign technique is utilized to discretize the cascaded MIMO analogue PID controller for finding a low-gain digital PID controller. Besides, a self-tuning FTC scheme with a modified Kalman filter algorithm is proposed, which is not only for the control system design but also for the faulty system recovery. The designed scheme can easily be implemented using digital processors. An illustrative example is presented to demonstrate the effectiveness of the proposed methodology.
Zhao Lu, Leang-San Shieh, Guanrong Chen, and Jagdish Chandra
Computers, Materials and Continua (Tech Science Press)
ABSTRACT —In practice, most physical chaotic systems are inherently with unknown nonlinearities, and conventional adaptive control for such chaotic systems typically faces with formidable technical challenges. As a better alternative, we propose using the recurrent high-order neural networks to identify and control the unknown chaotic systems, in which the Lyapunov synthesis approach is utilized for tuning the neural network model parameters. The globally uniform boundedness of the parameters estimation errors and the asymptotical stability of the tracking errors are proved by Lyapunov stability theory and LaSalle-Yoshizawa theorem. This method, in a systematic way, enables stabilization of chaotic motion to a steady state as well as tracking of any desired trajectory. Computer simulation on a complex chaotic system illustrates the effectiveness of the proposed control method. Key Words : Chaotic systems; Adaptive control; Lyapunov function; LaSalle-Yoshizawa theorem 1. INTRODUCTION
Jagdish Chandra and Joshua Landon
Informa UK Limited
Abstract Hybrid mobile wireless architectures that combine the advantages of ad hoc (mobile nodes) and cellular models provide “communications-on-the-move” services with enhanced flexibility and stability. In this article, we investigate the resiliency of such architectures by considering strategies for optimal deployment (number and location) of backup routers that would ensure reliable performance in such interdependent mobile systems.
Jagdish Chandra and
Fuji Technology Press Ltd.
Infrastructures such as transportation systems, power grids, communication networks, water resources, health delivery systems, and financial networks/institutions are vital to the safety, security and the well-being of the society. Reliable performance and protection of such systems is of paramount importance. Critical infrastructure systems, when viewed as complex interacting networks, present many interesting technical challenges to the modeling, analysis and simulation community. In this paper, we review the generic structure of such systems from the perspective of robust design and resilient behavior.
J. Chandra
IEEE
Seven papers are included in this minitrack, presented in two sessions. First session concentrates on assessment of vulnerabilities in interconnected networked systems. Topics include a survey of interdependencies in critical infrastructure systems, assessment of performance and optimal investments in such interconnected architectures, assessment of vulnerabilities for robust design, and design of survivable distributed systems. The second session concentrates on failure modes in interdependent critical infrastructures, with focus on dynamic and probabilistic approaches to specific infrastructure systems such as blackout vulnerability of power transmission grid and load-dependent cascading failures power grids. In a more general setting, the session also considers control and state estimation techniques for building trustworthy systems.
ZHAO LU, LEANG-SAN SHIEH, and JAGDISH CHANDRA
World Scientific Pub Co Pte Lt
The output tracking for a general family of nonlinear systems presents formidable technical challenges. In this paper, we present a novel scheme for tracking control of a class of affine nonlinear systems with multi-inputs. This effective procedure is based on a new sliding mode design for tracking control of such nonlinear systems. The construction of an optimal sliding mode is a difficult problem and no systematic and efficient method is currently available. Here, we develop an innovative approach that utilizes a chaotic optimizing algorithm, which is then successfully applied to obtain the optimal sliding manifold. The existing efficient reaching law approach is then utilized to synthesize the sliding mode control law. The sliding mode control scheme proposed here is particularly appropriate for robust tracking of the chaotic motion trajectory.
J. Chandra and W.A. Wallace
IEEE
J. Chandra
IEEE Comput. Soc
Critical infrastructures such as transportation systems, communication networks, and electric power grids provide rich examples of hybrid systems. These systems contain interactive sub-systems of continuous-time dynamics, discrete-time events, continuoustime controllers, and discrete-time event controllers. Such systems are characterized by complex nonlinear behavior, and experience uncertainty both in their internal description and in external disturbances/environments. The design, analysis and survivability of such infrastructures present many analytical and computational challenges.
SHU-MEI GUO, LEANG-SAN SHIEH, CHING-FANG LIN, and JAGDISH CHANDRA
World Scientific Pub Co Pte Lt
This paper presents a new state-space self-tuning control scheme for adaptive digital control of continuous-time multivariable nonlinear stochastic and chaotic systems, which have unknown system parameters, system and measurement noises, and inaccessible system states. Instead of using the moving average (MA)-based noise model commonly used for adaptive digital control of linear discrete-time stochastic systems in the literature, an adjustable auto-regressive moving average (ARMA)-based noise model with estimated states is constructed for state-space self-tuning control of nonlinear continuous-time stochastic systems. By taking advantage of a digital redesign methodology, which converts a predesigned high-gain analog tracker/observer into a practically implementable low-gain digital tracker/observer, and by taking the non-negligible computation time delay and a relatively longer sampling period into consideration, a digitally redesigned predictive tracker/observer has been newly developed in this paper for adaptive chaotic orbit tracking. The proposed method enables the development of a digitally implementable advanced control algorithm for nonlinear stochastic and chaotic hybrid systems.
Shu-Mei Guo, Leang-San Shieh, Ching-Fang Lin, and J. Chandra
IEEE Comput. Soc
This paper presents a new state-space self-tuning control scheme for adaptive digital control of continuous multivariable nonlinear stochastic hybrid systems with input saturation. The continuous nonlinear stochastic system is assumed to have unknown system parameters, system and measurement noises, and inaccessible system states. The proposed method enables the development of a digitally implementable advanced control algorithm for chaotic stochastic hybrid systems.
JAGDISH CHANDRA, G. S. LADDE, and O. SIRISAENGTAKSIN
Informa UK Limited
Abstract In this paper we consider a multi-time-scale singularly perturbed linear filtering problem. The main goal is to study the convergence of the solution of the reduced-order filters to different modes of high-order filters. This is accomplished by using a completely decoupled auxiliary system. A near-optimal solution to the filtering problem reduces to the solution of three lower-order filtering problems in three different time-scales.
Richard Karp, William Browder, Jagdish Chandra, Morris Hirsch, Richard Karp, James Melcher, Michael Shub, Robert Williams, and Sheldon Axler
Springer Science and Business Media LLC
Jagdish Chandra and Paul Davis
Elsevier
Jagdish Chandra and Alwyn C. Scott
Elsevier
Chandra Jagdish, G.S. Ladde, and V. Lakshmikantham
Informa UK Limited
A study of nonlinear second order stochastic boundary value problems (SBVP for short) is initiated through sample calculus approach. A basic existence result for bounded nonlinearities is established. The method of upper and lower solution processes and a general existence theorem are established. After proving the stochastic version of the needed maximum principle , the monotone iterative technique is developed which yields existence of muptiple solution processes of SBVP. Finally , by developing a stochastic comparison result, the important problem of finding error estimates between the sample solutions of SBVP and the solutions of corresponding deterministic BVP, is considered
Jagdish Chandra, G. S. Ladde, and V. Lakshmikantham
Society for Industrial & Applied Mathematics (SIAM)
By employing the theory of stochastic differential inequalities and a comparison result for the stochastic boundary value problem, the effects of roughness for a nonlinear gas lubricated problem are analyzed. In particular, by summarizing analytic techniques, estimates on the absolute mean and root-mean-square deviation of a normalized load carrying capacity from the smooth case are obtained for a general nonlinear one-dimensional problem.
J. Chandra and P. W. Davis
ASME International
Analytic bounds for and properties of the pressure field in the finite and infinite gas-lubricated slider bearing are derived without resorting to numerical or asymptotic approximations. For example, we show that the pressure profile in a converging-film bearing is always supra-ambient, has exactly one maximum point within the bearing, and exhibits strictly negative outward pressure gradients at the sides and leading and trailing edges of the bearing. The mathematical results on which these conclusions are based are briefly described as well.
Jagdish Chandra, Francis G. Dressel, and Paul Dennis Norman
Cambridge University Press (CUP)
SynopsisA monotone iteration scheme for the solution of the initial boundary problems associated with a system of semilinear parabolic differential equations has been developed that does not require the nonlinearities to be quasimonotone. The class of equations to which this scheme applies includes physical models that describe combustion processes involving Arrhenius reaction terms.