Browsing by Subject "Control theory"

Now showing 1 - 5 of 5
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    Charge optimization of lithium-ion batteries for electric-vehicle application
    (2015-03-02) Pramanik, Sourav; Anwar, Sohel; Wasfy, Tamar; Li, Lingxi
    In recent years Lithium-Ion battery as an alternate energy source has gathered lot of importance in all forms of energy requiring applications. Due to its overwhelming benefits over a few disadvantages Lithium Ion is more sought of than any other Battery types. Any battery pack alone cannot perform or achieve its maximum capacity unless there is some robust, efficient and advanced controls developed around it. This control strategy is called Battery Management System or BMS. Most BMS performs the following activity if not all Battery Health Monitoring, Temperature Monitoring, Regeneration Tactics, Discharge Profiles, History logging, etc. One of the major key contributor in a better BMS design and subsequently maintaining a better battery performance and EUL is Regeneration Tactics. In this work, emphasis is laid on understanding the prevalent methods of regeneration and designing a new strategy that better suits the battery performance. A performance index is chosen which aims at minimizing the effort of regeneration along with a minimum deviation from the rated maximum thresholds for cell temperature and regeneration current. Tuning capability is provided for both temperature deviation and current deviation so that it can be tuned based on requirement and battery chemistry and parameters. To solve the optimization problem, Pontryagin's principle is used which is very effective for constraint optimization with both state and input constraints. Simulation results with different sets of tuning shows that the proposed method has a lot of potential and is capable of introducing a new dynamic regeneration tactic for Lithium Ion cells. With the current optimistic results from this work, it is strongly recommended to bring in more battery constraints into the optimization boundary to better understand and incorporate battery chemistry into the regeneration process.
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    An evaluation of the moving horizon estimation algorithm for online estimation of battery state of charge and state of health
    (2014) Bibin Nataraja, Pattel; Anwar, Sohel
    Moving Horizon Estimation (MHE) is a powerful estimation technique for tackling the estimation problems of the state of dynamic systems in the presence of constraints, nonlinearities and disturbances and measurement noises. In this work, the Moving Horizon Estimation approach is applied in estimating the State of Charge (SOC) and State of Health (SOH) of a battery and the results are compared against those for the traditional estimation method of Extended Kalman Filter (EKF). The comparison of the results show that MHE provides improvement in performance over EKF in terms of different state initial conditions, convergence time, and process and sensor noise variations. An equivalent circuit battery model is used to capture the dynamics of the battery states, experimental data is used to identify the parameters of the battery model. MHE based state estimation technique is applied to estimates the states of the battery model, subjected to various estimated initial conditions, process and measurement noises and the results are compared against the traditional EKF based estimation method. Both experimental data and simulations are used to evaluate the performance of the MHE. The results shows that MHE performs better than EKF estimation even with unknown initial state of the estimator, MHE converges faster to the actual states,and also MHE is found to be robust to measurement and process noises.
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    Modeling, monitoring and optimization of discrete event systems using Petri nets
    (2014-01-29) Yan, Jiaxiang; Li, Lingxi; King, Brian; Chen, Yaobin
    Yan, Jiaxiang. M.S.E.C.E., Purdue University, May 2013. Modeling, Monitoring and Optimization of Discrete Event Systems Using Petri Nets. Major Professor: Lingxi Li. In last decades, the research of discrete event systems (DESs) has attracts more and more attention because of the fast development of intelligent control strategies. Such control measures combine the conventional control strategies with discrete decision-making processes which simulate human decision-making processes. Due to the scale and complexity of common DESs, the dedicated models, monitoring methods and optimal control strategies for them are necessary. Among various DES models, Petri nets are famous for the advantage in dealing with asynchronous processes. They have been widely applied in intelligent transportation systems (ITS) and communication technology in recent years. With encoding of the Petri net state, we can also enable fault detection and identification capability in DESs and mitigate potential human errors. This thesis studies various problems in the context of DESs that can be modeled by Petri nets. In particular, we focus on systematic modeling, asynchronous monitoring and optimal control strategies design of Petri nets. This thesis starts by looking at the systematic modeling of ITS. A microscopic model of signalized intersection and its two-layer timed Petri net representation is proposed in this thesis, where the first layer is the representation of the intersection and the second layer is the representation of the traffic light system. Deterministic and stochastic transitions are both involved in such Petri net representation. The detailed operation process of such Petri net representation is stated. The improvement of such Petri net representation is also provided with comparison to previous models. Then we study the asynchronous monitoring of sensor networks. An event sequence reconstruction algorithm for a given sensor network based on asynchronous observations of its state changes is proposed in this thesis. We assume that the sensor network is modeled as a Petri net and the asynchronous observations are in the form of state (token) changes at different places in the Petri net. More specifically, the observed sequences of state changes are provided by local sensors and are asynchronous, i.e., they only contain partial information about the ordering of the state changes that occur. We propose an approach that is able to partition the given net into several subnets and reconstruct the event sequence for each subnet. Then we develop an algorithm that is able to reconstruct the event sequences for the entire net that are consistent with: 1) the asynchronous observations of state changes; 2) the event sequences of each subnet; and 3) the structure of the given Petri net. We discuss the algorithmic complexity. The final problem studied in this thesis is the optimal design method of Petri net controllers with fault-tolerant ability. In particular, we consider multiple faults detection and identification in Petri nets that have state machine structures (i.e., every transition in the net has only one input place and one output place). We develop the approximation algorithms to design the fault-tolerant Petri net controller which achieves the minimal number of connections with the original controller. A design example for an automated guided vehicle (AGV) system is also provided to illustrate our approaches.
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    Modulation of the Cutaneous Silent Period in the Upper-Limb with Whole-Body Instability
    (PLOS, 2016-03-16) Eckert, Nathanial R.; Poston, Brach; Riley, Zachary A.; Department of Kinesiology, School of Physical Education and Tourism Management
    The silent period induced by cutaneous electrical stimulation of the digits has been shown to be task-dependent, at least in the grasping muscles of the hand. However, it is unknown if the cutaneous silent period is adaptable throughout muscles of the entire upper limb, in particular when the task requirements are substantially altered. The purpose of the present study was to examine the characteristics of the cutaneous silent period in several upper limb muscles when introducing increased whole-body instability. The cutaneous silent period was evoked in 10 healthy individuals with electrical stimulation of digit II of the right hand when the subjects were seated, standing, or standing on a wobble board while maintaining a background elbow extension contraction with the triceps brachii of ~5% of maximal voluntary contraction (MVC) strength. The first excitatory response (E1), first inhibitory response (CSP), and second excitatory response (E2) were quantified as the percent change from baseline and by their individual durations. The results showed that the level of CSP suppression was lessened (47.7 ± 7.7% to 33.8 ± 13.2% of baseline, p = 0.019) and the duration of the CSP inhibition decreased ( p = 0.021) in the triceps brachii when comparing the seated and wobble board tasks. For the wobble board task the amount of cutaneous afferent inhibition of EMG activity in the triceps brachii decreased; which is proposed to be due to differential weighting of cutaneous feedback relative to the corticospinal drive, most likely due to presynaptic inhibition, to meet the demands of the unstable task.
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    Optimal Power Control of a Wind Turbine Power Generation System
    (2012-09-27) Xue, Jie; Chen, Yaobin; Li, Lingxi; Rovnyak, Steven
    This thesis focuses on optimization of wind power tracking control systems in order to capture maximum wind power for the generation system. In this work, a mathematical simulation model is developed for a variable speed wind turbine power generation system. The system consists a wind turbine with necessary transmission system, and a permanent magnet synchronous generator and its vector control system. A new fuzzy based hill climbing method for power tracking control is proposed and implemented to optimize the wind power for the system under various conditions. Two existing power tracking control methods, the tip speed ratio (TSR) control method and the speed sensorless control method are also implemented with the wind power system. The computer simulations with a 5 KW wind power generation system are performed. The results from the proposed control method are compared with those obtained using the two existing methods. It is illustrated that the proposed method generally outperforms the two existing methods, especially when the operating point is far away from the maximum point. The proposed control method also has similar stable characteristic when the operating point is close to the peak point in comparison with the existing methods. The proposed fuzzy control method is computationally efficient and can be easily implemented in real-time.