Anuj Nandanwar
Verified @gmail.com
Faculty Fellow
IIT Mandi iHub and HCI Foundation
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Human-Computer Interaction
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Anuj Nandanwar, Narendra Kumar Dhar, Laxmidhar Behera, Saeid Nahavandi, and Rajesh Sinha
Institute of Electrical and Electronics Engineers (IEEE)
In this article, we propose a novel stochastic event-driven near-optimal sliding-mode controller design for addressing the consensus of a multiagent system in a network. The system is prone to external disturbances and network uncertainties, such as losses and delays of data packets. The randomness of network uncertainties introduces stochasticity in the system. The design starts with the formulation of control-affine dynamics based on a single integrator robot model, formation error, and sliding surface dynamics. An event-triggering condition is then derived for an update of control input for each agent. These input updates guarantee desired consensus in finite time with reaching time of each agent's sliding surface having an upper bound. The admissibility of event-driven near-optimal control updates is also ensured for each agent. The near-optimal control design for each agent has achieved through neural-network-based actor-critic architecture. The implementation of Pioneer P3-DX mobile robots illustrates threefold efficacy of the proposed design: 1) advantages of event-driven approach and higher order sliding mode controller; 2) robustness to network uncertainties; and 3) near-optimality in system performance.
Anuj Nandanwar and Varun Dutt
ACM
Social robots are designed to interact with humans in social and emotional ways. Although social robots can have practical use cases where privacy concerns prevail, the use of social robots in such cases has been limited. This paper addresses this literature gap by evaluating a social robot in assessing people’s stress, anxiety, and depression via conversational AI. In this work, we develop a social robot called “Furhat” for assessment of stress, anxiety, and depression via conversational AI as an alternative to the traditional pencil and paper method. The Furhat robot is designed to interact with individuals and provide a safe and non-judgmental space for individuals to express their stress, anxiety, and depression symptoms. The study compared the levels of stress, anxiety and depression assessed from Furhat with those assessed using the conventional pencil-and-paper method. Results demonstrated that the Furhat robot-based data collection and analysis method was similar to the pencil-and-paper method. Additionally, social robots were a preferred option for patients, as they reported higher levels of comfort and satisfaction with the Furhat-based screening process compared to that via the pencil-and-paper method. The use of social robots for data collection and emotional support has excellent potential for various applications in healthcare, education, and other domains.
Narendra Kumar Dhar and Anuj Nandanwar
IEEE
This paper proposes dynamic updates in stochastic backstepping control for a networked system. The system is prone to network uncertainties such as packet loss and transmission delay. These uncertainties introduce stochasticity in the system. The dynamic updates and generic triggering conditions for each subsystem are formulated to ensure system stability. The neural networks are used to precisely approximate stabilizing functions and control input because each subsystem dynamics has stochastic functions. The triggering conditions are further used to obtain generic expressions for permissible value of round-trip data packet losses and delay between consecutive triggers for each subsystem. A comprehensive analysis of proposed design is done for trajectory tracking by a networked system prone to uncertainties.
Anuj Nandanwar, Narendra Kumar Dhar, Laxmidhar Behera, and Rajesh Sinha
Informa UK Limited
We propose a continuous-time design for finite-time consensus control for multi-robot system using event-based near-optimal sliding mode control. The system has a leader–follower framework prone to external bounded disturbance. The proposed design comprises of three parts: (i) formulation of control-affine dynamics, (ii) design a triggering condition for control updates that guarantee stability and consensus in the system, and (iii) design a near-optimal sliding mode control using neural-network based approximate dynamic programming. We derive a bound on inter-event time that guarantees admissibility of updated control input values. We finally validate the efficacy of proposed design through real-time experiments using three Pioneer P3-DX mobile robots (leader and two followers) and comparative analyses with other state-of-the-art approaches. The control updates of follower-1 and follower-2 robots are approximately and , respectively, that reduce the computational burden in multi-robot framework. GRAPHICAL ABSTRACT
Padmini Singh, Anuj Nandanwar, Laxmidhar Behera, Nishchal K. Verma, and Saeid Nahavandi
Institute of Electrical and Electronics Engineers (IEEE)
This work proposes a novel event-triggered exponential supertwisting algorithm (ESTA) for path tracking of a mobile robot. The proposed work is divided into three parts. In the first part, a fractional-order sliding surface-based exponential supertwisting event-triggered controller has been proposed. Fractional-order sliding surface improves the transient response, and the exponential supertwisting reaching law reduces the reaching phase time and eliminates the chattering. The event-triggering condition is derived using the Lipschitz method for minimum actuator utilization, and the interexecution time between two events is derived. In the second part, a fault estimator is designed to estimate the actuator fault using the Lyapunov stability theory. Furthermore, it is shown that in the presence of matched and unmatched uncertainty, event-trigger-based controller performance degrades. Hence, in the third part, an integral sliding-mode controller (ISMC) has been clubbed with the event-trigger ESTA for filtering of the uncertainties. It is also shown that when fault estimator-based ESTA is clubbed with ISMC, then the robustness of the controller increases, and the tracking performance improves. This novel technique is robust toward uncertainty and fault, offers finite-time convergence, reduces chattering, and offers minimum resource utilization. Simulations and experimental studies are carried out to validate the advantages of the proposed controller over the existing methods.
Anuj Nandanwar, Narendra Kumar Dhar, Dmitry Malyshev, Larisa Rybak, and Laxmidhar Behera
Institute of Electrical and Electronics Engineers (IEEE)
This article presents a novel stochastic event-based super-twisting controller design for addressing the formation control problem in the networked multiagent system in the presence of an external disturbance. The stochasticity in the system is introduced by randomness of network uncertainties, i.e., losses and delays of data packets. The proposed design has three parts. The first part derives an event-triggering condition for control input updates of each agent in the system. The second part guarantees desired formation in finite time by deriving an upper bound on reaching time to the designed sliding surface of each agent. The third part ensures admissibility of event-based control updates of the agents such that they achieve stable desired formation. The proposed stochastic design has been validated on Pioneer P3-DX mobile robots. The results show the three-fold effectiveness of stochastic design. They are: 1) retaining the advantages of event-triggering strategy; 2) retaining the advantages of super-twisting sliding-mode controller; and 3) robust toward network uncertainties.
Narendra Kumar Dhar, Anuj Nandanwar, Nishchal K. Verma, and Laxmidhar Behera
Institute of Electrical and Electronics Engineers (IEEE)
This article proposes an online stochastic dynamic event-based near-optimal controller for formation in the networked multirobot system. The system is prone to network uncertainties, such as packet loss and transmission delay, that introduce stochasticity in the system. The multirobot formation problem poses a nonzero-sum game scenario. The near-optimal control inputs/policies based on proposed event-based methodology attain a Nash equilibrium achieving the desired formation in the system. These policies are generated online only at events using actor–critic neural network architecture whose weights are updated too at the same instants. The approach ensures system stability by deriving the ultimate boundedness of estimation errors of actor–critic weights and the event-based closed-loop formation error. The efficacy of the proposed approach has been validated in real-time using three Pioneer P3-Dx mobile robots in a multirobot framework. The control update instants are minimized to as low as 20% and 18% for the two follower robots.
Anuj Nandanwar, Vibhu Kumar Tripathi, and Laxmidhar Behera
IEEE
This work is concerned with the development of an active fault tolerant scheme using second order sliding mode control for multi-robotics systems in the presence of actuator faults. The fault-tolerant controller based on conventional sliding mode control gives asymptotic convergence, less robustness, slower transient response and large amplitude of chattering that restrict its uses in real-time application. To overcome these issues, a nonlinear terminal sliding variable and a variable gain super twisting reaching law are employed to design nonlinear controller which ensures finite-time convergence and chattering attenuation. The closed-loop finite-time stability is analyzed using Lyapunov stability theory. The actuator faults information provided by the fault detection and diagnosis unit that is constituted by higher order sliding mode observer which will be used for reconfigure the controller parameters to retain the nominal tracking performance with high precision despite the actuator fault. Finally, the proposed methodology efficacy and effectiveness is tested using extensive simulation under both normal and faulty condition.
Padmini Singh, Pooja Agrawal, Anuj Nandanwar, Laxmidhar Behera, Nishchal Kumar Verma, Saeid Nahavandi, and Mo Jamshidi
Institute of Electrical and Electronics Engineers (IEEE)
This article presents a multivariable event-triggered generalized super-twisting sliding-mode algorithm for a nonholonomic mobile-robot safe navigation in unknown indoor environment. For robot safe navigation, vision-based variable gain composite guidance law is proposed to generate desired angular velocity. The guidance strategy uses the centroid of the depth map of the obstacles obtained from RGB-depth sensor. The propose controller follows the path generated by the guidance law. Stability analysis of the controller is done to show the fast convergence as compared to the existing controllers. To show the robustness of the controller in comparison to the existing super-twisting algorithm, a sensitivity analysis is carried out. Furthermore, for minimizing the controller effort, an event-triggered condition for the proposed controller is obtained using Lyapunov stability theory. Comparative simulation study is carried out to show the fast convergence and robustness of the proposed controller. Experiments are done for robot safe navigation in presence of disturbance.
Anuj Nandanwar, Narendra Kumar Dhar, Dmitry Malyshev, Larisa Rybak, and Laxmidhar Behera
Institute of Electrical and Electronics Engineers (IEEE)
This article addresses the problem of event-based consensus in a leader–follower multiagent system framework prone to external bounded disturbance. The proposed approach has three parts. The first part defines a novel measurement error based on sliding surface for super-twisting sliding-mode controller. The Lyapunov stability analysis is then used to derive a dynamic event-triggering condition for control updates. The event-based control updates guarantee stability along with the desired consensus amongst agents (robots). The second part derives a bound on reaching time to the sliding surface, thereby guaranteeing finite-time consensus control for each agent. The third part guarantees the admissibility of event-based control updates for each agent. The robustness of the proposed approach is validated through simulation and real-time experiments using three Pioneer P3-DX mobile robots in a multiagent framework. The real-time experimental results prove the reduction in computational burden of the entire system as control updates for two followers are found to be approximately <inline-formula><tex-math notation="LaTeX">$\\text{28.33}\\%$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\\text{23.33}\\%$</tex-math></inline-formula>, respectively, in the presence of disturbances.
Anuj Nandanwar, Ranjith Ravindranathan Nair, and Laxmidhar Behera
Institution of Engineering and Technology (IET)
In this study, the authors address the problem of optimal routing and relative motion control in a network of robots. The path planning scheme has been designed using a fuzzy-based potential function employing optimal routing parameters. The optimal routing variables, such as routing probability and the transmission rate are obtained using a discrete optimisation problem. To deal with the disturbances and uncertainties in the physical system, an adaptive second-order sliding mode control(SMC) scheme has been proposed for the relative motion control of the networks of robots, where the disturbances are estimated using a novel disturbance observer and the controller parameters are updated online using an adaptive tuning algorithm derived based on Lyapunov theory. The robustness of the proposed path planner and the control scheme are validated through simulation as well as through real-time experimentation based on Pioneer P3-DX robots. The comparison results based on conventional SMC and adaptive SMC are also drawn.
Anuj Nandanwar, Laxmidhar Behera, Amit Shukla, and Hamad Karki
IEEE
In this work, we approach the problem of maximization of delay constraint utility function for a group of robots using a Cyber-Physical System (CPS) framework. For any task involving coordination of robots, a reliable communication link is required to be established. The maintenance of this link reliability highly depends on trajectories of individual robots. This needs a hybrid approach to be adopted, in which mobility and routing control are taken care of simultaneously. In this paper, a hybrid approach has been proposed based on bidirectional optimization i.e. network utility maximization and energy minimization in the presence of delay constraint. Network Utility function allocates network resources to the robots based on physical constraints involved. The result of this optimization problem would empower the hybrid controller to control both robot position as well as communication link strength.
Anuj Nandanwar, Meher Preetam Korukonda, and Laxmidhar Behera
Elsevier BV
Abstract The rapid advancement of smart grid technology has led to inundation of vast amount of sensors and distributed controllers into the grid which requires unconventional methods for treating problems like stability, reliability, etc. This paper deals with stabilization of grid dynamics after modeling it a Cyber-Physical Energy System. The design of the communication system between the sensors and the distributed controllers play an important role in achieving stability of bus voltages in the grid. A greedy-based network routing scheme was employed while considering both bandwidth and connection constraints. The approach was successfully tested over a sample 4-bus system.