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Author : Bassam Alrifaee
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (17 download)
Download or read book Networked Model Predictive Control for Vehicle Collision Avoidance written by Bassam Alrifaee and published by . This book was released on 2017* with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hikmet D. Ozdemir
Publisher :
ISBN 13 :
Total Pages : 116 pages
Book Rating : 4.:/5 (127 download)
Download or read book Evaluation of Model Predictive Control Method for Collision Avoidance of Automated Vehicles written by Hikmet D. Ozdemir and published by . This book was released on 2020 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collision avoidance design plays an essential role in autonomous vehicle technology. It's an attractive research area that will need much experimentation in the future. This research area is very important for providing the maximum safety to automated vehicles, which have to be tested several times under diFFerent circumstances for safety before use in real life. This thesis proposes a method for designing and presenting a collision avoidance maneuver by using a model predictive controller with a moving obstacle for automated vehicles. It consists of a plant model, an adaptive MPC controller, and a reference trajectory. The proposed strategy applies a dynamic bicycle model as the plant model, adaptive model predictive controller for the lateral control, and a custom reference trajectory for the scenario design. The model was developed using the Model Predictive Control Toolbox and Automated Driving Toolbox in Matlab. Builtin tools available in Matlab/Simulink were used to verify the modeling approach and analyze the performance of the system. The major contribution of this thesis work was implementing a novel dynamic obstacle avoidance control method for automated vehicles. The study used validated parameters obtained from previous research. The novelty of this research was performing the studies using a MPC based controller instead of a sliding mode controller, that was primarily used in other studies. The results obtained from the study are compared with the validated models. The comparisons consisted of the lateral overlap, lateral error, and steering angle simulation results between the models. Additionally, this study also included outcomes for the yaw angle. The comparisons and other outcomes obtained in this study indicated that the developed control model produced reasonably acceptable results and recommendations for future studies.
Author : Mohammadmehdi Jalalmaab
Publisher :
ISBN 13 :
Total Pages : 98 pages
Book Rating : 4.:/5 (13 download)
Download or read book Model Predictive Control of Highway Emergency Maneuvering and Collision Avoidance written by Mohammadmehdi Jalalmaab and published by . This book was released on 2017 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous emergency maneuvering (AEM) is an active safety system that automates safe maneuvers to avoid imminent collision, particularly in highway driving situations. Uncertainty about the surrounding vehicles' decisions and also about the road condition, which has significant effects on the vehicle's maneuverability, makes it challenging to implement the AEM strategy in practice. With the rise of vehicular networks and connected vehicles, vehicles would be able to share their perception and also intentions with other cars. Therefore, cooperative AEM can incor- porate surrounding vehicles' decisions and perceptions in order to improve vehicles' predictions and estimations and thereby provide better decisions for emergency maneuvering. In this thesis, we develop an adaptive, cooperative motion planning scheme for emergency maneuvering, based on the model predictive control (MPC) approach, for vehicles within a ve- hicular network. The proposed emergency maneuver planning scheme finds the best combination of longitudinal and lateral maneuvers to avoid imminent collision with surrounding vehicles and obstacles. To implement real-time MPC for the non-convex problem of collision free motion planning, safety constraints are suggested to be convexified based on the road geometry. To take advantage of vehicular communication, the surrounding vehicles' decisions are incorporated in the prediction model to improve the motion planning results. The MPC approach is prone to loss of feasibility due to the limited prediction horizon for decision-making. For the autonomous vehicle motion planning problem, many of detected ob- stacles, which are beyond the prediction horizon, cannot be considered in the instantaneous de- cisions, and late consideration of them may cause infeasibility. The conditions that guarantee persistent feasibility of a model predictive motion planning scheme are studied in this thesis. Maintaining the system's states in a control invariant set of the system guarantees the persis- tent feasibility of the corresponding MPC scheme. Specifically, we present two approaches to compute control invariant sets of the motion planning problem; the linearized convexified ap- proach and the brute-force approach. The resulting computed control invariant sets of these two approaches are compared with each other to demonstrate the performance of the proposed algorithm. Time-variation of the road condition affects the vehicle dynamics and constraints. Therefore, it necessitates the on-line identification of the road friction parameter and implementation of an adaptive emergency maneuver motion planning scheme. In this thesis, we investigate coopera- tive road condition estimation in order to improve collision avoidance performance of the AEM system. Each vehicle estimates the road condition individually, and disseminates it through the vehicular network. Accordingly, a consensus estimation algorithm fuses the individual estimates to find the maximum likelihood estimate of the road condition parameter. The performance of the proposed cooperative road condition estimation has been validated through simulations.
Author : Shima Savehshemshaki
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)
Download or read book Model Predictive Control Strategies For Constrained Unmanned Vehicles written by Shima Savehshemshaki and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis deals with two control problems for unmanned vehicles, namely battery shortage prevention for electric unmanned vehicles and collision avoidance strategy for constrained multi unmanned vehicle systems. In the battery shortage prevention problem, we design a novel control architecture, equipped with a battery manager module, capable of avoiding energy shortage by appropriately imposing time-varying upper bounds on the vehicle's maximum acceleration. Here, the dual-mode control paradigm known as set-theoretic model predictive control is applied to couple the reference tracking and the battery shortage problems. First, we offline design a conservative maximum acceleration profile capable of assuring that the electric unmanned vehicle will reach the desired target without incurring into a battery shortage along the given path. Then, online, by following a receding horizon approach, we show that the battery manager can enhance the performance by using the current battery's state-of-charge. Moreover, a simulation example is presented to clarify and show the proposed control framework's potential and features. In the collision avoidance problem, we deal with vehicles moving in a shared environment where each UV follows a trajectory given by a local planner. We assume that the planners are uncoordinated and each vehicle is subject to different constraints and disturbances. In this context, we design a new centralized traffic manager that, in conjunction with ad-hoc designed local model predictive controller, can ensure the absence of collisions while minimizing the total vehicle's stops occurrences. In particular, in a receding horizon fashion, the traffic manager exploits available previews on the successive vehicle's waypoints to speed-up or speed-down the vehicles and minimize the chance of collisions. Moreover, by exploiting basic set-theoretic arguments, traffic manager can impose a vehicle to stop and safely prevent collisions whenever necessary. Finally, two different simulation examples are presented to better illustrate the capability of the proposed solution.
Author : Yi, Boliang
Publisher : KIT Scientific Publishing
ISBN 13 : 3731507854
Total Pages : 174 pages
Book Rating : 4.7/5 (315 download)
Download or read book Integrated Planning and Control for Collision Avoidance Systems written by Yi, Boliang and published by KIT Scientific Publishing. This book was released on 2018-08-29 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collision avoidance systems like emergency braking assist systems have demonstrated their effectiveness in increasing the safety of vehicle passengers in various studies. To further increase the effectiveness of collision avoidance systems, the exploitation of the lateral free space by evasive maneuvers is being investigated in this book. This work focuses on methods for integrated trajectory planning and vehicle dynamics control in collision avoidance scenarios by combined evasion and braking.
Author : Guan-Zhen Wu
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)
Download or read book Autonomous Cars Crossroad Collision Avoidance Based on Geometry Approach and Model Predictive Control written by Guan-Zhen Wu and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An approach of collision avoidance in autonomous cars based on geometry and Model Predict Control (MPC) in crossroad without traffic light is proposed in this study. Due to the advanced of 5G and autonomous cars, V2V communication allows for the exchange of information. The algorithm presented here employs geometry approach to identify potential of collision, incorporating a priority sequencing to simplify the calculation complexity. Under the circumstances the collision will happen, the second part of collision avoidance strategy will be activated. Collision avoidance strategy can be divided into collision avoidance stage and path correcting stage. Each stage addresses collision avoidance separately in the longitudinal and lateral directions. The magnitude of collision avoidance is determined based on position and velocity information which will be substituted into MPC to achieve collision avoidance. To increase the speed of convergence and efficiency, the control inputs of vehicle model and the cost function of MPC are optimized. After collision avoidance stage, trajectory adjustments are result in the necessary of path correcting stage, focusing initially on position and lateral incorporating velocity. To validate the effectiveness of the proposed collision avoidance algorithm, simulations are conducted using Matlab/Driving Scenario Designer, considering potential collision scenarios and initial conditions.
Author : Christoph Stiller
Publisher : Springer Nature
ISBN 13 : 3031604946
Total Pages : 601 pages
Book Rating : 4.0/5 (316 download)
Download or read book Cooperatively Interacting Vehicles written by Christoph Stiller and published by Springer Nature. This book was released on with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 9 pages
Book Rating : 4.:/5 (574 download)
Download or read book Control and Information Architecture for Coordinated Networked Systems written by and published by . This book was released on 2009 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unifying framework for the design and operation of networked coordinated systems has been researched with developments focusing on application in the management of autonomous vehicles which are subject to large external disturbances, such as wind gusts. The benchmark problem is the use of intervehicle communication and active control to effect collision avoidance in multi-vehicle systems with significant environmental disturbances. The central aim of the work was to combine constrained optimal control, achieved via so-called Model Predictive Control methods, with limited capacity communication link resource assignment to achieve collision avoidance with a nominal fleet formation and a specified level of external disturbances. The core results concern the use of the covariance or quantified uncertainty of the estimate of the other vehicles' positions as the link between communications resource assignment -- more bits of communications means more accurate position estimates -- and collision avoidance requirements -- close vehicles in the formation require more accurate position information to avoid collision. A computational tool is derived. The work has been presented at AFRL.
Author : Didier Theilliol
Publisher : Springer Nature
ISBN 13 : 3031275403
Total Pages : 352 pages
Book Rating : 4.0/5 (312 download)
Download or read book Recent Developments in Model-Based and Data-Driven Methods for Advanced Control and Diagnosis written by Didier Theilliol and published by Springer Nature. This book was released on 2023-07-15 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book consists of recent works on several axes either with a more theoretical nature or with a focus on applications, which will span a variety of up-to-date topics in the field of systems and control. The main market area of the contributions include: Advanced fault-tolerant control, control reconfiguration, health monitoring techniques for industrial systems, data-driven diagnosis methods, process supervision, diagnosis and control of discrete-event systems, maintenance and repair strategies, statistical methods for fault diagnosis, reliability and safety of industrial systems artificial intelligence methods for control and diagnosis, health-aware control design strategies, advanced control approaches, deep learning-based methods for control and diagnosis, reinforcement learning-based approaches for advanced control, diagnosis and prognosis techniques applied to industrial problems, Industry 4.0 as well as instrumentation and sensors. These works constitute advances in the aforementioned scientific fields and will be used by graduate as well as doctoral students along with established researchers to update themselves with the state of the art and recent advances in their respective fields. As the book includes several applicative studies with several multi-disciplinary contributions (deep learning, reinforcement learning, model-based/data-based control etc.), the book proves to be equally useful for the practitioners as well industrial professionals.
Author : Adnan Tahirovic
Publisher : Springer Science & Business Media
ISBN 13 : 144715049X
Total Pages : 64 pages
Book Rating : 4.4/5 (471 download)
Download or read book Passivity-Based Model Predictive Control for Mobile Vehicle Motion Planning written by Adnan Tahirovic and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehicle navigation in both indoor and outdoor environments. The brief also introduces analysis of the worst-case scenario that might occur during the task execution. Some of the questions answered in the text include: • how to use an MPC optimization framework for the mobile vehicle navigation approach; • how to guarantee safe task completion even in complex environments including obstacle avoidance and sideslip and rollover avoidance; and • what to expect in the worst-case scenario in which the roughness of the terrain leads the algorithm to generate the longest possible path to the goal. The passivity-based MPC approach provides a framework in which a wide range of complex vehicles can be accommodated to obtain a safer and more realizable tool during the path-planning stage. During task execution, the optimization step is continuously repeated to take into account new local sensor measurements. These ongoing changes make the path generated rather robust in comparison with techniques that fix the entire path prior to task execution. In addition to researchers working in MPC, engineers interested in vehicle path planning for a number of purposes: rescued mission in hazardous environments; humanitarian demining; agriculture; and even planetary exploration, will find this SpringerBrief to be instructive and helpful.
Author : Andrew Hegman
Publisher :
ISBN 13 :
Total Pages : 84 pages
Book Rating : 4.:/5 (111 download)
Download or read book A Real-time Predictive Vehicular Collision Avoidance System on an Embedded General-purpose GPU written by Andrew Hegman and published by . This book was released on 2018 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collision avoidance is an essential capability for autonomous and assisted-driving ground vehicles. In this work, we developed a novel model predictive control based intelligent collision avoidance (CA) algorithm for a multi-trailer industrial ground vehicle implemented on a General Purpose Graphical Processing Unit (GPGPU). The CA problem is formulated as a multi-objective optimal control problem and solved using a limited look-ahead control scheme in real-time. Through hardware-in-the-loop-simulations and experimental results obtained in this work, we have demonstrated that the proposed algorithm, using NVIDA's CUDA framework and the NVIDIA Jetson TX2 development platform, is capable of dynamically assisting drivers and maintaining the vehicle a safe distance from the detected obstacles on-the-fly. We have demonstrated that a GPGPU, paired with an appropriate algorithm, can be the key enabler in relieving the computational burden that is commonly associated with model-based control problems and thus make them suitable for real-time applications.
Author : Jie Ji
Publisher : Springer Nature
ISBN 13 : 303101507X
Total Pages : 144 pages
Book Rating : 4.0/5 (31 download)
Download or read book Path Planning and Tracking for Vehicle Collision Avoidance in Lateral and Longitudinal Motion Directions written by Jie Ji and published by Springer Nature. This book was released on 2022-06-01 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the control of Connected and Automated Vehicles (CAVs) has attracted strong attention for various automotive applications. One of the important features demanded of CAVs is collision avoidance, whether it is a stationary or a moving obstacle. Due to complex traffic conditions and various vehicle dynamics, the collision avoidance system should ensure that the vehicle can avoid collision with other vehicles or obstacles in longitudinal and lateral directions simultaneously. The longitudinal collision avoidance controller can avoid or mitigate vehicle collision accidents effectively via Forward Collision Warning (FCW), Brake Assist System (BAS), and Autonomous Emergency Braking (AEB), which has been commercially applied in many new vehicles launched by automobile enterprises. But in lateral motion direction, it is necessary to determine a flexible collision avoidance path in real time in case of detecting any obstacle. Then, a path-tracking algorithm is designed to assure that the vehicle will follow the predetermined path precisely, while guaranteeing certain comfort and vehicle stability over a wide range of velocities. In recent years, the rapid development of sensor, control, and communication technology has brought both possibilities and challenges to the improvement of vehicle collision avoidance capability, so collision avoidance system still needs to be further studied based on the emerging technologies. In this book, we provide a comprehensive overview of the current collision avoidance strategies for traditional vehicles and CAVs. First, the book introduces some emergency path planning methods that can be applied in global route design and local path generation situations which are the most common scenarios in driving. A comparison is made in the path-planning problem in both timing and performance between the conventional algorithms and emergency methods. In addition, this book introduces and designs an up-to-date path-planning method based on artificial potential field methods for collision avoidance, and verifies the effectiveness of this method in complex road environment. Next, in order to accurately track the predetermined path for collision avoidance, traditional control methods, humanlike control strategies, and intelligent approaches are discussed to solve the path-tracking problem and ensure the vehicle successfully avoids the collisions. In addition, this book designs and applies robust control to solve the path-tracking problem and verify its tracking effect in different scenarios. Finally, this book introduces the basic principles and test methods of AEB system for collision avoidance of a single vehicle. Meanwhile, by taking advantage of data sharing between vehicles based on V2X (vehicle-to-vehicle or vehicle-to-infrastructure) communication, pile-up accidents in longitudinal direction are effectively avoided through cooperative motion control of multiple vehicles.
Author : Alexander Schwab
Publisher : Logos Verlag Berlin GmbH
ISBN 13 : 3832555498
Total Pages : 192 pages
Book Rating : 4.8/5 (325 download)
Download or read book Cooperative Control of Networked Vehicles written by Alexander Schwab and published by Logos Verlag Berlin GmbH. This book was released on 2022-08-29 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis concerns the cooperative control of networked vehicles. Autonomous driving is a topic that is currently being discussed with great interest from researchers, vehicle manufacturers and the corresponding media. Future autonomous vehicles should bring the passengers to their desired destination while improving both safety and efficiency compared to current human-driven vehicles. The inherent problem of all vehicle coordination tasks is to guarantee collision avoidance in every situation. To this end, autonomous vehicles have to share information with each other in order to perform traffic manoeuvres that require the cooperation of multiple vehicles. The fundamental problem of vehicle platooning is studied extensively which describes the task of arranging a set of vehicles so that they drive with a common velocity and a prescribed distance. Local design objectives are derived that have to be satisfied by the vehicle controllers. In particular, it is shown that the vehicles have to be externally positive to achieve collision avoidance. As an abstraction from real traffic scenarios, swarms of networked vehicles are considered. The main difference between swarming and traffic problems is that a communication structure that has been appropriate in the beginning might become unsuited for the control task due to the relative movement of the vehicles. To solve this problem, this thesis proposes to use the Delaunay triangulation as a switching communication structure.
Author : Gerard Ferrer Usieto
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (112 download)
Download or read book Trajectory Generation for Autonomous Highway Driving Using Model Predictive Control written by Gerard Ferrer Usieto and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control (MPC) has had an increasing role in autonomous driving applications over the last decade, enabled by the continuous rising of the computational power in microcontrollers. In this thesis a collision avoidance trajectory generation algorithm based in MPC formulation is developed. The operating environment consists in a one-way highway with two lanes. The overall system is equipped with a low-level controller capable of tracking the trajectory generated by the MPC planner. In the path towards this goal, a MPC based lane changing application in an obstacle-free highway environment has been developed. A point-mass kinematic vehicle model is used as the MPC plant model for its simplicity and enabled by the usage of a low-level controller. This thesis studies several obstacle representation approaches and then, explains in detail the development process of the collision avoidance trajectory generation application, defining and discussing simulation results for each intermediate approach obtained. Both applications have been implemented in a BeagleBone Black online board situated in small-scale trucks (1:12) for testing purpose. The experimental results have been studied and discussed to prove the algorithms functionalities, as well as to check the board capabilities to run online MPC applications in comparison with polynomials based approaches.
Author : Craig Earl Beal
Publisher : Stanford University
ISBN 13 :
Total Pages : 161 pages
Book Rating : 4.F/5 ( download)
Download or read book Applications of Model Predictive Control to Vehicle Dynamics for Active Safety and Stability written by Craig Earl Beal and published by Stanford University. This book was released on 2011 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each year in the United States, thousands of lives are lost as a result of loss of control crashes. Production driver assistance systems such as electronic stability control (ESC) have been shown to be highly effective in preventing many of these automotive crashes, yet these systems rely on a sensor suite that yields limited information about the road conditions and vehicle motion. Furthermore, ESC systems rely on gains and thresholds that are tuned to yield good performance without feeling overly restrictive to the driver. This dissertation presents an alternative approach to providing stabilization assistance to the driver which leverages additional information about the vehicle and road that may be obtained with advanced estimation techniques. This new approach is based on well-known and robust vehicle models and utilizes phase plane analysis techniques to describe the limits of stable vehicle handling, alleviating the need for hand tuning of gains and thresholds. The resulting state space within the computed handling boundaries is referred to as a safe handling envelope. In addition to the boundaries being straightforward to calculate, this approach has the benefit of offering a way for the designer of the system to directly adjust the controller to accomodate the preferences of different drivers. A model predictive control structure capable of keeping the vehicle within the safe handling boundaries is the final component of the envelope control system. This dissertation presents the design of a controller that is capable of smoothly and progressively augmenting the driver steering input to enforce the boundaries of the envelope. The model predictive control formulation provides a method for making trade-offs between enforcing the boundaries of the envelope, minimizing disruptive interventions, and tracking the driver's intended trajectory. Experiments with a steer-by-wire test vehicle demonstrate that the model predictive envelope control system is capable of operating in conjunction with a human driver to prevent loss of control of the vehicle while yielding a predictable vehicle trajectory. These experiments considered both the ideal case of state information from a GPS/INS system and an a priori friction estimate as well as a real-world implementation estimating the vehicle states and friction coefficient from steering effort and inertial sensors. Results from the experiments demonstrated a controller that is tolerant of vehicle and tire parameterization errors and works well over a wide range of conditions. When real time sensing of the states and friction properties is enabled, the results show that coupling of the controller and estimator is possible and the model predictive control structure provides a mechanism for minimizing undesirable coupled dynamics through tuning of intuitive controller parameters. The model predictive control structure presented in this dissertation may also be considered as a general framework for vehicle control in conjunction with a human driver. The structure utilized for envelope control may also be used to restrict other vehicle states for safety and stability. Results are presented in this dissertation to show that a model predictive controller can coordinate a secondary actuator to alter the planar states and reduce the energy transferred into the roll modes of the vehicle. The systematic approach to vehicle stabilization presented in this dissertation has the potential to improve the design methodology for future systems and form the basis for the inclusion of more advanced functions as sensing and computing capabilities improve. The envelope control system presented here offers the opportunity to advance the state of the art in stabilization assistance and provides a way to help drivers of all skill levels maintain control of their vehicle.
Download or read book MPC-BASED AUTONOMOUS DRIVING CONTROL WITH LOCALIZED PATH PLANNING FOR OBSTACLE AVOIDANCE AND NAVIGATING SIGNALIZED INTERSECTIONS written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : Connected and autonomous vehicles are becoming the major focus of research for the industry and academia in the automotive field. Many companies and research groups have demonstrated the advantages and the requirement of such technology to improve the energy efficiency of vehicles, decrease the number of crash and road accidents, and control emissions. This research delves into improving the autonomy of self-driving vehicles by implementing localized path planning algorithms to introduce motion control for obstacle avoidance during uncertainties. Lateral path planning is implemented using the A* algorithm combined with piecewise Bezier curve generation which provides an optimum trajectory reference to avoid a collision. Model Predictive Control (MPC) is used to implement longitudinal and lateral control of the vehicle. The data from vehicle-to-everything (V2X) communication infrastructure is used to navigate through multiple signalized intersections. Furthermore, a new method of developing Advanced Driver Assistance Systems (ADAS) algorithms and vehicle controllers using Model-In-the-Loop (MIL) testing is explored with the use of PreScan®. With PreScan®, various traffic scenarios are modeled and the sensor data are simulated by using physics-based sensor models, which are fed to the controller for data processing and motion planning. Obstacle detection and collision avoidance are demonstrated using the presented MPC controller. The results of the proposed controller and the scope of the future work conclude the research.
Author : Anthony Tri Tran C.
Publisher : Springer
ISBN 13 : 9811084092
Total Pages : 247 pages
Book Rating : 4.8/5 (11 download)
Download or read book A Quadratic Constraint Approach to Model Predictive Control of Interconnected Systems written by Anthony Tri Tran C. and published by Springer. This book was released on 2018-03-06 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the stabilization and model predictive control of interconnected systems with mixed connection configurations. It introduces the concept of dissipation-based quadratic constraint for developing attractivity assurance methods for interconnected systems. In order to develop these methods, distributed and decentralized architectures are employed, whereby the communication between subsystems is fully connected, partially connected, or completely disconnected. Given that the control inputs are entirely or partially decoupled between subsystems and no additional constraints are imposed on the interactive variables beyond the coupling constraint itself, the proposed approaches can be used with various types of systems and applications. Further, the book describes how the effects of coupling delays and data losses in device networks are resolved. From a practical perspective, the innovations presented are of benefit in applications in a broad range of fields, including the process and manufacturing industries, networked robotics, and network-centric systems such as chemical process systems, power systems, telecommunication networks, transportation networks, and, no less importantly, supply chain automation.
