Narendra Kumar Dhar

Internet of Things based framework for trajectory tracking control

Controlling physical devices from remote places have become necessity in todays practice. These kind of operations require a proper infrastructure which ties all kinds of devices (sensors, actuators, plant etc.) along with the controllers at remote places (either centralized or decentralized) using a communication medium. The heterogeneity of platforms is a challenge to integration of all these aspects. The use of Internet of Things (IoT) provides connectivity across several devices and platforms. The paper presents IoT based real time trajectory tracking by a vehicle. The controller at a far off place devises control actions relying on the information obtained from sensors. The control actions are then sent to actuators through the communication channel so that vehicle tracks the reference trajectory efficiently. The sliding mode controller is used which decides the control actions on the basis of objective function. The framework works on a non uniformly sized control interval consisting of variable number of sampling instants of fixed length. The objective function considers the system states, time interval and also the control and communication constraints (delays and packet losses). The developed algorithm based on IoT shows a proper convergence to the reference trajectory.

On an Integrated Approach to Networked Climate Control of a Smart Home

Climate control of thermal spaces or zones is very important for complex systems like smart home. The climate control system is connected to network for the transfer of measurement data and control action packets from sensors to controller and from controller to actuators, respectively. The system can, therefore, be categorized as a cyber-physical system (CPS). Heterogeneous nature of control and cyber domains poses a great challenge in dealing with CPS development. An integrated framework of intelligent control and communication is presented in this paper for performance improvements in the climate control system. The joint framework considers relevant system objectives based on system states and actuator actions. The constraints related to errors and delays in communication along with the limited capabilities of the devices are also taken care of. The formulated problem has been solved through the real-time optimization approach following the communication protocol using two separate controller methodologies: 1) learning-based proportional-integral (PI) controller and 2) adaptive critic-based controller. The gradient descent algorithm updates the parameters of the PI controller, whereas a properly trained adaptive critic controller generates real-time control actions for achieving desired states. The real-time performance obtained for both the controllers are significantly improved even in inconsistent data communication.

Adaptive backstepping sliding mode control based on nonlinear disturbance observer for trajectory tracking of robotic manipulator

This paper proposes and analyzes two different control techniques to remove the effect of lumped uncertainties and disturbances for trajectory tracking by robotic manipulator. These techniques are a) Adaptive backstepping sliding mode control and b) Nonlinear disturbance observer based backstepping sliding mode control. Adaptive backstepping sliding mode control estimates the system uncertainties and disturbance using an adaptive law. Lyapunov theory is used to define the adaptive law for the convergence of tracking error. The second technique initially estimates the unknown external disturbances using non-linear disturbance observer and then generates control input using beckstepping sliding mode controller. Backstepping sliding mode ensures the sliding surface to be chattering free and improves convergence rate in finite-time. The stability of system is analyzed using Lyapunov theory for both the techniques. Simulation results show the effectiveness and robustness of proposed techniques FOR trajectory tracking.

Intelligent controller design coupled in a communication framework for a networked HVAC system

Heating, ventilation and air-conditioning(HVAC) system is a very important component in designing a Smart Home. The HVAC system itself is a Cyber-Physical system(CPS) and comes under Industry 4.0. Being connected to network it requires an integrated architecture of communication and control for its smooth operation. Heterogeneous nature of control and cyber domains is a great challenge in dealing with CPS development. An intelligent controller design coupled in a communication framework is presented in this paper for performance improvements in HVAC system. The control and communication architecture considers relevant system objectives based on system states and actuator actions. The HVAC system regulates the flow of conditioned air for various desired temperatures in different thermal zones. The formulated problem has been solved through real time optimization approach using learning based Proportional-Integral(PI) controller methodology following the communication protocol. The gradient descent algorithm updates the parameters of PI controller which in turn generates online control actions for achieving desired states. The algorithm helps in obtaining optimal control actions for the actuators and shows a fast convergence to the different desired temperature sets.

Vision based object follower automated guided vehicle using compressive tracking and stereo-vision

Integration of a visual sensing system plays a vital role in automated navigation by providing a sensing ability of the surrounding environment. The problem of object following is challenging due to changes in appearance that can occur due to motion, pose, illumination and occlusion. The real-time implementation of a computer vision based object following system is presented in this paper. The position of the object to be followed is determined by processing a real time image feed from a calibrated stereo-camera. The method incorporates compressive tracking and stereo-vision based disparity mapping boosted with relocation of the tracking window using Speeded Up Robust Features (SURF). The proposed algorithm runs in real-time and performs favorably in terms of computational efficiency, accuracy and robustness.

Vision based obstacle avoidance and recognition system

Automation techniques have been applied in almost every field in past few years. Automated Guided Vehicle (AGV) are most often used in industries and inventories for object management. Obstacle avoidance being a necessary requirement for navigation in any vehicle, still faces many challenges in the field of automation due to uncertain nature of the surrounding environment. This paper presents the implementation of an obstacle avoidance method on an AGV using stereoscopic vision by creating a disparity map and measuring the relative distances of the objects in the scene. Not only it avoids collision but it also classifies the object into one of the specified categories using supervised learning algorithm. The integration of image classification with stereovision can allow the AGV to understand which objects to pick up and which ones to leave behind.

Evolutionary Algorithm Tuned Fuzzy PI Controller for a Networked HVAC System

Heating, ventilation and air-conditioning (HVAC) system is an important component of Smart Home. The HVAC system is connected to network for the transfer of measurement data and control action packets from sensors to controller and controller to actuators respectively. The HVAC system can therefore be categorized as a Cyber-Physical system (CPS). Such systems are prone to communication uncertainties like packet losses and delays. Such systems require integrated architecture of communication and control. An evolutionary algorithm tuned fuzzy PI controller design coupled in a communication framework is presented in this paper for performance improvements of HVAC system. The entire architecture considers relevant system objectives based on system states and actuator actions. The formulated problem has been solved through real time optimization approach using the designed controller following the communication protocol. The developed algorithm helps in obtaining optimal actuator actions and shows a fast convergence to the different desired temperature sets. The results also show that the system can recover from sudden burst packet losses.

Priority based optimal path routing for automated guided vehicle

The AGV system for industries needs to be efficient in terms of time, labour and cost. One way of achieving it is to make path routing algorithm optimal. From industrial point of view, there can be numerous locations of loading, unloading and disposal. The AGV must perform material handling by visiting different locations. Therefore, to make the routed path optimal, the paper proposes priority based implementation which can be adopted in industrial environment and the AGV can be made to follow the optimal path. The main focus of the method is to prioritize the locations to be visited and plan an optimal path for visiting locations in the same order of priority.

Real-time remote monitoring of an air compressor using MTConnect standard protocol

An intelligent condition based monitoring system needs to have a communication subsystem for consensus among the devices of that system. Development of such a communication system has to follow an industry oriented universally acceptable standard protocol. Having universal acceptability, MTConnect is potentially most effective, efficient and sustainable protocol for this purpose. This paper presents real time remote monitoring of a reciprocating air compressor based on MTConnect standard protocol for communicating the data related to air compressor between device and clients or applications. The acoustic and vibration data from air compressor are communicated to two clients (viz. web browser and MS Excel) from a dedicated MTConnect agent. The data obtained at client end has a timestamp which notifies the client about instant at which that particular data was acquired from device.

Event-Triggered Sliding Mode Control Based Trajectory Tracking in a Cyber-Physical Space

Time-triggered controllers have been developed for many trajectory tracking applications. The efficiency of controller plays an important role along with the accuracy of the tracking. Hence, an event-triggered sliding mode controller in a cyber-physical space is proposed in this paper. Event-triggered approach reduces control efforts of the system as the control actions are generated at specific occurrence of events and thereby reduces load on the communication network. The designed event-triggered approach in a cyber-physical space is integrated with communication protocol to prevent system malfunctioning by delayed and corrupt data packets. The proposed event-triggered controller along with the communication protocol is implemented for an automated-guided vehicle model. The results obtained from event-triggered approach are duly compared with time-triggered controller. The results show the efficiency of developed controller.