Showing papers on "Control theory published in 2014"

Distributed Secondary Control for Islanded Microgrids—A Novel Approach

Abstract: This paper presents a novel approach to conceive the secondary control in droop-controlled microgrids (MGs). The conventional approach is based on restoring the frequency and amplitude deviations produced by the local droop controllers by using an MG central controller (MGCC). A distributed networked control system is used in order to implement a distributed secondary control (DSC), thus avoiding its implementation in MGCC. The proposed approach is not only able to restore frequency and voltage of the MG but also ensures reactive power sharing. The distributed secondary control does not rely on a central control, so that the failure of a single unit will not produce the fail down of the whole system. Experimental results are presented to show the feasibility of the DSC. The time latency and data drop-out limits of the communication systems are studied as well.

Self-Synchronized Synchronverters: Inverters Without a Dedicated Synchronization Unit

Abstract: A synchronverter is an inverter that mimics synchronous generators, which offers a mechanism for power systems to control grid-connected renewable energy and facilitates smart grid integration. Similar to other grid-connected inverters, it needs a dedicated synchronization unit, e.g., a phase-locked loop (PLL), to provide the phase, frequency, and amplitude of the grid voltage as references. In this paper, a radical step is taken to improve the synchronverter as a self-synchronized synchronverter by removing the dedicated synchronization unit. It can automatically synchronize itself with the grid before connection and track the grid frequency after connection. This considerably improves the performance, reduces the complexity, and computational burden of the controller. All the functions of the original synchronverter, such as frequency and voltage regulation, real power, and reactive power control, are maintained. Both simulation and experimental results are presented to validate the control strategy. Experimental results have shown that the proposed control strategy can improve the performance of frequency tracking by more than 65%, the performance of real power control by 83%, and the performance of reactive power control by about 70%.

Robust Nonlinear Control Design: State-Space and Lyapunov Techniques

Abstract: Presenting advances in the theory and design of robust nonlinear control systems, this volume identifies two potential sources of excessive control effort in Lyapunov design techniques and shows how such effort can be greatly reduced. Within the framework of Lyapunov design techniques the authors develop a variety of control design methods suitable for systems described by low-order nonlinear ordinary differential equations. There is an emphasis on global controller designs, that is designs for the entire region of model validity.

Multiple processor motor control for modular surgical instruments

Abstract: In various forms, the modular motor control system may comprise one or more motor controllers each having an associated motor. The one or more motor controllers may be in communication with a master controller. The master controller is configured to provide control signals to the motor controllers to control the associated motors. In some forms, the one or more motor controllers and the associated motors may be located within a surgical module. The surgical module may provide a communications interface between the master controller and the one or more motor controllers.

A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments

Abstract: Cloud computing environments allow customers to dynamically scale their applications. The key problem is how to lease the right amount of resources, on a pay-as-you-go basis. Application re-dimensioning can be implemented effortlessly, adapting the resources assigned to the application to the incoming user demand. However, the identification of the right amount of resources to lease in order to meet the required Service Level Agreement, while keeping the overall cost low, is not an easy task. Many techniques have been proposed for automating application scaling. We propose a classification of these techniques into five main categories: static threshold-based rules, control theory, reinforcement learning, queuing theory and time series analysis. Then we use this classification to carry out a literature review of proposals for auto-scaling in the cloud.

Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data

Abstract: Vehicle longitudinal control systems such as (commercially available) autonomous Adaptive Cruise Control (ACC) and its more sophisticated variant Cooperative ACC (CACC) could potentially have significant impacts on traffic flow. Accurate models of the dynamic responses of both of these systems are needed to produce realistic predictions of their effects on highway capacity and traffic flow dynamics. This paper describes the development of models of both ACC and CACC control systems that are based on real experimental data. To this end, four production vehicles were equipped with a commercial ACC system and a newly developed CACC controller. The Intelligent Driver Model (IDM) that has been widely used for ACC car-following modeling was also implemented on the production vehicles. These controllers were tested in different traffic situations in order to measure the actual responses of the vehicles. Test results indicate that: (1) the IDM controller when implemented in our experimental test vehicles does not perceptibly follow the speed changes of the preceding vehicle; (2) strings of consecutive ACC vehicles are unstable, amplifying the speed variations of preceding vehicles; and (3) strings of consecutive CACC vehicles overcome these limitations, providing smooth and stable car following responses. Simple but accurate models of the ACC and CACC vehicle following dynamics were derived from the actual measured responses of the vehicles and applied to simulations of some simple multi-vehicle car following scenarios.

Supervisory Control of an Adaptive-Droop Regulated DC Microgrid With Battery Management Capability

Abstract: DC power systems are gaining an increasing interest in renewable energy applications because of the good matching with dc output type sources such as photovoltaic (PV) systems and secondary batteries. In this paper, several distributed generators (DGs) have been merged together with a pair of batteries and loads to form an autonomous dc microgrid (MG). To overcome the control challenge associated with coordination of multiple batteries within one stand-alone MG, a double-layer hierarchical control strategy was proposed. 1) The unit-level primary control layer was established by an adaptive voltage-droop method aimed to regulate the common bus voltage and to sustain the states of charge (SOCs) of batteries close to each other during moderate replenishment. The control of every unit was expanded with unit-specific algorithm, i.e., finish-of-charging for batteries and maximum power-point tracking (MPPT) for renewable energy sources, with which a smooth online overlap was designed and 2) the supervisory control layer was designed to use the low-bandwidth communication interface between the central controller and sources in order to collect data needed for adaptive calculation of virtual resistances (VRs) as well as transit criteria for changing unit-level operating modes. A small-signal stability for the whole range of VRs. The performance of developed control was assessed through experimental results.

Iterative Training of Dynamic Skills Inspired by Human Coaching Techniques

Abstract: Inspired by how humans learn dynamic motor skills through a progressive process of coaching and practices, we introduce an intuitive and interactive framework for developing dynamic controllers. The user only needs to provide a primitive initial controller and high-level, human-readable instructions as if s/he is coaching a human trainee, while the character has the ability to interpret the abstract instructions, accumulate the knowledge from the coach, and improve its skill iteratively. We introduce “control rigs” as an intermediate layer of control module to facilitate the mapping between high-level instructions and low-level control variables. Control rigs also utilize the human coach's knowledge to reduce the search space for control optimization. In addition, we develop a new sampling-based optimization method, Covariance Matrix Adaptation with Classification (CMA-C), to efficiently compute-control rig parameters. Based on the observation of human ability to “learn from failure”, CMA-C utilizes the failed simulation trials to approximate an infeasible region in the space of control rig parameters, resulting a faster convergence for the CMA optimization. We demonstrate the design process of complex dynamic controllers using our framework, including precision jumps, turnaround jumps, monkey vaults, drop-and-rolls, and wall-backflips.

Extended-State-Observer-Based Output Feedback Nonlinear Robust Control of Hydraulic Systems With Backstepping

Abstract: In this paper, an output feedback nonlinear control is proposed for a hydraulic system with mismatched modeling uncertainties in which an extended state observer (ESO) and a nonlinear robust controller are synthesized via the backstepping method. The ESO is designed to estimate not only the unmeasured system states but also the modeling uncertainties. The nonlinear robust controller is designed to stabilize the closed-loop system. The proposed controller accounts for not only the nonlinearities (e.g., nonlinear flow features of servovalve), but also the modeling uncertainties (e.g., parameter derivations and unmodeled dynamics). Furthermore, the controller theoretically guarantees a prescribed tracking transient performance and final tracking accuracy, while achieving asymptotic tracking performance in the absence of time-varying uncertainties, which is very important for high-accuracy tracking control of hydraulic servo systems. Extensive comparative experimental results are obtained to verify the high-performance nature of the proposed control strategy.

Regions of Active Damping Control for LCL Filters

Abstract: The control of a grid-connected voltage source inverter with an inductive-capacitive-inductive (LCL) filter is a very challenging task, since the LCL network causes a resonance phenomenon near to the control stability boundary. While many active damping methods have been proposed to overcome this issue, the role that pulse width modulation transport delay plays in the effectiveness of these strategies is still not fully resolved. This paper presents a theoretical discrete time-analysis framework that identifies three distinct regions of LCL filter resonance, namely, a high resonant frequency region where active damping is not required, a critical resonant frequency where a controller cannot stabilize the system, and a low resonant frequency region where active damping is essential. Suitable controllers are then proposed for the two stable regions, with gain calculations that allow for the greatest system bandwidth and damping. Simulation and experimental results verify the presented analysis.

Design and control of a bio-inspired soft wearable robotic device for ankle-foot rehabilitation.

Abstract: We describe the design and control of a wearable robotic device powered by pneumatic artificial muscle actuators for use in ankle–foot rehabilitation. The design is inspired by the biological musculoskeletal system of the human foot and lower leg, mimicking the morphology and the functionality of the biological muscle–tendon–ligament structure. A key feature of the device is its soft structure that provides active assistance without restricting natural degrees of freedom at the ankle joint. Four pneumatic artificial muscles assist dorsiflexion and plantarflexion as well as inversion and eversion. The prototype is also equipped with various embedded sensors for gait pattern analysis. For the subject tested, the prototype is capable of generating an ankle range of motion of 27 ◦ (14 ◦ dorsiflexion and 13 ◦ plantarflexion). The controllability of the system is experimentally demonstrated using a linear time-invariant (LTI) controller. The controller is found using an identified LTI model of the system, resulting from the interaction of the soft orthotic device with a human leg, and model-based classical control design techniques. The suitability of the proposed control strategy is demonstrated with several angle-reference following experiments.

Step-by-Step Controller Design for LCL-Type Grid-Connected Inverter with Capacitor–Current-Feedback Active-Damping

Abstract: The injected grid current regulator and active damping of the LCL filter are essential to the control of LCL-type grid-connected inverters. Generally speaking, the current regulator guarantees the quality of the injected grid current, and the active damping suppresses the resonance peak caused by the LCL filter and makes it easier to stabilize the whole system. Based on the proportional-integral (PI) and proportional-resonant (PR) compensator together with capacitor-current-feedback active-damping which are widely used for their effectiveness and simple implementations, this paper proposes a simple step-by-step controller design method for the LCL-type grid-connected inverter. By carefully dealing with the interaction between the current regulator and active damping, the complete satisfactory regions of the controller parameters for meeting the system specifications are obtained, and from which the controller parameters can be easily picked out. Based on these satisfactory regions, it is more convenient and explicit to optimize the system performance. Besides, the insight of tuning the controller parameters from these satisfactory regions is also discussed. Simulation and experimental results verify the proposed step-by-step design method.

Controller Synthesis for String Stability of Vehicle Platoons

Abstract: Cooperative adaptive cruise control (CACC) allows for short-distance automatic vehicle following using intervehicle wireless communication in addition to onboard sensors, thereby potentially improving road throughput. In order to fulfill performance, safety, and comfort requirements, a CACC-equipped vehicle platoon should be string stable, attenuating the effect of disturbances along the vehicle string. Therefore, a controller design method is developed that allows for explicit inclusion of the string stability requirement in the controller synthesis specifications. To this end, the notion of string stability is introduced first, and conditions for L2 string stability of linear systems are presented that motivate the development of an H∞ controller synthesis approach for string stability. The potential of this approach is illustrated by its application to the design of controllers for CACC for one- and two-vehicle look-ahead communication topologies. As a result, L2 string-stable platooning strategies are obtained in both cases, also revealing that the two-vehicle look-ahead topology is particularly effective at a larger communication delay. Finally, the results are experimentally validated using a platoon of three passenger vehicles, illustrating the practical feasibility of this approach.

An Analysis of the Precision and Reliability of the Leap Motion Sensor and Its Suitability for Static and Dynamic Tracking

Abstract: We present the results of an evaluation of the performance of the Leap Motion Controller with the aid of a professional, high-precision, fast motion tracking system A set of static and dynamic measurements was performed with different numbers of tracking objects and configurations For the static measurements, a plastic arm model simulating a human arm was used A set of 37 reference locations was selected to cover the controller's sensory space For the dynamic measurements, a special V-shaped tool, consisting of two tracking objects maintaining a constant distance between them, was created to simulate two human fingers In the static scenario, the standard deviation was less than 05 mm The linear correlation revealed a significant increase in the standard deviation when moving away from the controller The results of the dynamic scenario revealed the inconsistent performance of the controller, with a significant drop in accuracy for samples taken more than 250 mm above the controller's surface The Leap Motion Controller undoubtedly represents a revolutionary input device for gesture-based human-computer interaction; however, due to its rather limited sensory space and inconsistent sampling frequency, in its current configuration it cannot currently be used as a professional tracking system

Model predictive control with signal temporal logic specifications

Abstract: We present a mathematical programming-based method for model predictive control of discrete-time cyber-physical systems subject to signal temporal logic (STL) specifications. We describe the use of STL to specify a wide range of properties of these systems, including safety, response and bounded liveness. For synthesis, we encode STL specifications as mixed integer-linear constraints on the system variables in the optimization problem at each step of a model predictive control framework. We present experimental results for controller synthesis for building energy and climate control.

Stochastic MPC With Learning for Driver-Predictive Vehicle Control and its Application to HEV Energy Management

Abstract: This paper develops an approach for driver-aware vehicle control based on stochastic model predictive control with learning (SMPCL). The framework combines the on-board learning of a Markov chain that represents the driver behavior, a scenario-based approach for stochastic optimization, and quadratic programming. By using quadratic programming, SMPCL can handle, in general, larger state dimension models than stochastic dynamic programming, and can reconfigure in real-time for accommodating changes in driver behavior. The SMPCL approach is demonstrated in the energy management of a series hybrid electrical vehicle, aimed at improving fuel efficiency while enforcing constraints on battery state of charge and power. The SMPCL controller allocates the power from the battery and the engine to meet the driver power request. A Markov chain that models the power request dynamics is learned in real-time to improve the prediction capabilities of model predictive control (MPC). Because of exploiting the learned pattern of the driver behavior, the proposed approach outperforms conventional model predictive control and shows performance close to MPC with full knowledge of future driver power request in standard and real-world driving cycles.

Adaptive Backstepping Stabilization of Nonlinear Uncertain Systems With Quantized Input Signal

Abstract: In this paper, we study a general class of strict feedback nonlinear systems, where the input signal takes quantized values. We consider a stabilization problem for nonlinear uncertain systems via adaptive backstepping approach. The control design is achieved by introducing a hysteretic quantizer to avoid chattering and using backstepping technique. A guideline is derived to select the parameters of the quantizer. The designed controller together with the quantizer ensures the stability of the closed-loop system in the sense of signal boundedness.

Distributed Adaptive Droop Control for DC Distribution Systems

Abstract: A distributed-adaptive droop mechanism is proposed for secondary/primary control of dc microgrids. The conventional secondary control that adjusts the voltage set point for the local droop mechanism is replaced by a voltage regulator. A current regulator is also added to fine-tune the droop coefficient for different loading conditions. The voltage regulator uses an observer that processes neighbors' data to estimate the average voltage across the microgrid. This estimation is further used to generate a voltage correction term to adjust the local voltage set point. The current regulator compares the local per-unit current of each converter with the neighbors' on a communication graph and, accordingly, provides an impedance correction term. This term is then used to update the droop coefficient and synchronize per-unit currents or, equivalently, provide proportional load sharing. The proposed controller precisely accounts for the transmission/distribution line impedances. The controller on each converter exchanges data with only its neighbor converters on a sparse communication graph spanned across the microgrid. Global dynamic model of the microgrid is derived with the proposed controller engaged. A low-voltage dc microgrid prototype is used to verify the controller performance, link-failure resiliency, and the plug-and-play capability.

On the centrality of disturbance rejection in automatic control

Abstract: In this paper, it is shown that the problem of automatic control is, in essence, that of disturbance rejection, with the notion of disturbance generalized to symbolize the uncertainties, both internal and external to the plant. A novel, unifying concept of disturbance rejector is proposed to compliment the traditional notion of controller. The new controller–rejector pair is shown to be a powerful organizing principle in the realm of automatic control, leading to a Copernican moment where the model-centric design philosophy is replaced by the one that is control–centric in the following sense: the controller is designed for a canonical model and is fixed; the difference between the plant and the canonical model is deemed as disturbance and rejected.

A Model Predictive Control System for a Hybrid Battery-Ultracapacitor Power Source

Abstract: A model predictive control system for a hybrid battery-ultracapacitor power source is proposed and experimentally verified in this paper. The main advantage of the proposed system is that the battery current, the battery state of charge, and the ultracapacitor current and voltage are maintained within predefined limits during the operation. In addition, the controller allocates fast current changes to the ultracapacitor while the battery responds mainly to slow current changes which helps to increase the battery lifetime. The presented experimental results verify operation of the proposed system.

Modelling, Design and Robust Control of a Remotely Operated Underwater Vehicle:

Abstract: Underwater remotely operated vehicles (ROVs) play an important role in a number of shallow and deep-water missions for marine science, oil and gas extraction, exploration and salvage. In these applications, the motions of the ROV are guided either by a human pilot on a surface support vessel through an umbilical cord providing power and telemetry, or by an automatic pilot. In the case of automatic control, ROV state feedback is provided by acoustic and inertial sensors and this state information, along with a controller strategy, is used to perform several tasks such as station-keeping and auto-immersion/heading, among others. In this paper, the modelling, design and control of the Kaxan ROV is presented: i) The complete six degrees of freedom, non linear hydrodynamic model with its parameters, ii) the Kaxan hardware/software architecture, iii) numerical simulations in Matlab/Simulink platform of a model-free second order sliding mode control along with ocean currents as disturbances and thruster dynamics...

Sensitivity of the Generic Transport Model upset dynamics to time delay

Abstract: Bifurcation analysis has previously been applied to the NASA Generic Transport Model (GTM) to provide insight into open-loop upset dynamics and also the impact on and sensitivity of such behaviour to closing the loop with a flight controller. However, these studies have not considered time delay in the system: this arises in all feedback controllers and has specific relevance when remotely piloting a vehicle such as the NASA AirSTAR GTM with ground-based controllers. Developments in the AirSTAR programme, in which a sub-scale generic airliner model will be tested for loss-of-control conditions over long ranges, raise the prospect of increased adverse effects of time delay relative to previous testing. This paper utilises bifurcation analysis, supplemented with time histories, on the GTM numerical model with a LQR-PI controller to evaluate the sensitivity of the closed-loop system stability to time delay. In this paper, the impact of time delays in both a fixed-gain and a gain-scheduled version of the controller is presented in terms of stability of nominal and off-nominal solutions.

Cooperative adaptive cruise control: Network-aware analysis of string stability

Abstract: In this paper, we consider a Cooperative Adaptive Cruise Control (CACC) system, which regulates intervehicle distances in a vehicle string, for achieving improved traffic flow stability and throughput. Improved performance can be achieved by utilizing information exchange between vehicles through wireless communication in addition to local sensor measurements. However, wireless communication introduces network-induced imperfections, such as transmission delays, due to the limited bandwidth of the network and the fact that multiple nodes are sharing the same medium. Therefore, we approach the design of a CACC system from a Networked Control System (NCS) perspective and present an NCS modeling framework that incorporates the effect of sampling, hold, and network delays that occur due to wireless communication and sampled-data implementation of the CACC controller over this wireless link. Based on this network-aware modeling approach, we develop a technique to study the so-called string stability property of the string, in which vehicles are interconnected by a vehicle following control law and a constant time headway spacing policy. This analysis technique can be used to investigate tradeoffs between CACC performance (string stability) and network specifications (such as delays), which are essential in the multidisciplinary design of CACC controllers. Finally, we demonstrate the validity of the presented framework in practice by experiments performed with CACC-equipped prototype vehicles. cop. 2014 IEEE.

On the Capacitated Controller Placement Problem in Software Defined Networks

Abstract: Controller placement is a key problem in software defined networks (SDNs). Previously, the solution to this problem only focused on propagation latency but ignored the load of controllers, which is a critical factor in real networks. In this letter, we define a capacitated controller placement problem (CCPP), taking into consideration the load of controllers, and introduce an efficient algorithm to solve the problem. The evaluation shows that the new strategy can significantly reduce the number of required controllers, reduce the load of the maximum-load controller, and reduce the radius stretches compared with the K-center strategy with dynamic controller provision or dynamic scheduling.