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Showing papers presented at "American Control Conference in 2006"


Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this paper, it is shown that the unknown dynamics and disturbance can be actively estimated and compensated in real time and this makes the feedback control more robust and less dependent on the detailed mathematical model of the physical process.
Abstract: The question addressed in this paper is: just what do we need to know about a process in order to control it? With active disturbance rejection, perhaps we don't need to know as much as we were told. In fact, it is shown that the unknown dynamics and disturbance can be actively estimated and compensated in real time and this makes the feedback control more robust and less dependent on the detailed mathematical model of the physical process. In this paper we first examine the basic premises in the existing paradigms, from which it is argued that a paradigm shift is necessary. Using a motion control metaphor, the basis of such a shift, the active disturbance rejection control, is introduced. Stability analysis and applications are presented. Finally, the characteristics and significance of the new paradigm are discussed.

803 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, a review of observer design is presented for the benefit of practitioners, in the sense that all observers are examined in terms of: 1) the assumed dynamic structure of the plant; 2) the required information, including the input signals and modeling information of the plants; and 3) the implementation equation of the observer.
Abstract: This paper gives a unified and historical review of observer design for the benefit of practitioners. It is unified in the sense that all observers are examined in terms of: 1) the assumed dynamic structure of the plant; 2) the required information, including the input signals and modeling information of the plant; and 3) the implementation equation of the observer. This allows a practitioner, with a particular observer design problem in mind, to quickly find a suitable solution. The review is historical in the sense that it follows the evolution of ideas in observer design in the last half century. From the distinction in problem formulation, required modeling information and the observer design goal, we can see two schools of thought: one is developed in the framework of modern control theory; the other is based on disturbance estimation, which has been, to some extent, overlooked.

322 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, a group coordination problem where the objective is to steer the differences between output variables of the group members to a prescribed compact set via distributed feedback rules is studied. But the authors focus on a closed-loop system where the information flow between neighboring members is bidirectional.
Abstract: We pursue a group coordination problem where the objective is to steer the differences between output variables of the group members to a prescribed compact set via distributed feedback rules. When the information flow between neighboring members is bidirectional, we show that the closed-loop system exhibits a special interconnection structure which inherits the passivity properties of its components. By exploiting this structure we develop a passivity-based design framework, which results in a broad class of feedback rules that encompass as special cases some of the existing formation stabilization and group agreement designs in the literature. The passivity approach offers additional design flexibility compared to these special cases, and systematically constructs a Lurie-type Lyapunov function for the closed-loop system. We further study the robustness of the feedback laws in the presence of a time-varying communication topology.

319 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, a fractional order PID controller is investigated for a position servomechanism control system considering actuator saturation and the shaft torsional flexibility, and a modified approximation method is introduced to realize the designed fractional-order PID controller.
Abstract: In this paper, a fractional order PID controller is investigated for a position servomechanism control system considering actuator saturation and the shaft torsional flexibility. For actually implementation, we introduced a modified approximation method to realize the designed fractional order PID controller. Numerous simulation comparisons presented in this paper indicate that, the fractional order PID controller, if properly designed and implemented, will outperform the conventional integer order PID controller.

255 citations


Proceedings Article•DOI•
Wei Ren1•
14 Jun 2006
TL;DR: In this paper, a fundamental consensus algorithm for systems modeled by second-order dynamics is introduced, and variants of the consensus algorithm are applied to tackle formation control problems by appropriately choosing information states on which consensus is reached.
Abstract: In this paper we first introduce a fundamental consensus algorithm for systems modeled by second-order dynamics. We then apply variants of the consensus algorithm to tackle formation control problems by appropriately choosing information states on which consensus is reached. Even in the absence of centralized leadership, the consensus based formation control strategies can guarantee accurate formation maintenance in the general case that information flow is unidirectional. We also show that existing leader-follower, behavioral, and virtual structure/virtual leader formation control approaches can be unified in the general framework of consensus building. A multi-vehicle formation control example is shown in simulation to illustrate our strategies.

238 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, the ensemble Kalman filter was applied to representative examples to quantify the tradeoff between estimation accuracy and ensemble size, and it was shown that the ensemble filter worked successfully once a threshold ensemble size was reached.
Abstract: In this paper we described the ensemble Kalman filter algorithm. This approach to nonlinear Kalman filtering is a Monte Carlo procedure, which has been widely used in weather forecasting applications. Our goal was to apply the ensemble Kalman filter to representative examples to quantify the tradeoff between estimation accuracy and ensemble size. For all of the linear and nonlinear examples that we considered, the ensemble Kalman filter worked successfully once a threshold ensemble size was reached. In future work we will investigate the factors that determine this threshold value.

215 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: A novel adaptive control architecture is developed that ensures that the input and output of an uncertain linear system track the input-and- output of a desired linear system during the transient phase, in addition to the asymptotic tracking.
Abstract: In this paper, we develop a novel adaptive control architecture that ensures that the input and output of an uncertain linear system track the input and output of a desired linear system during the transient phase, in addition to the asymptotic tracking. These features are established by first performing an equivalent reparametrization of MRAC, the main difference of which from MRAC is in definition of the error signal for adaptive laws. This new architecture, called companion model adaptive controller (CMAC), allows for incorporation of a low-pass filter into the feedback-loop that enables to enforce the desired transient performance by increasing the adaptation gain. For the proof of asymptotic stability, the Lscr1 gain of a cascaded system, comprised of this filter and the closed-loop desired reference model, is required to be less than the inverse of the upper bound of the norm of unknown parameters used in projection based adaptation laws. Moreover, the new Lscr1 adaptive controller is guaranteed to stay in the low-frequency range. Simulation results illustrate the theoretical findings

210 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: The key idea behind the approach is that the probabilistic obstacle avoidance problem can be expressed as a disjunctive linear program using linear chance constraints, such that planning with uncertainty requires minimal additional computation.
Abstract: Autonomous vehicles need to plan trajectories to a specified goal that avoid obstacles. Previous approaches that used a constrained optimization approach to solve for finite sequences of optimal control inputs have been highly effective. For robust execution, it is essential to take into account the inherent uncertainty in the problem, which arises due to uncertain localization, modeling errors, and disturbances. Prior work has handled the case of deterministically bounded uncertainty. We present here an alternative approach that uses a probabilistic representation of uncertainty, and plans the future probabilistic distribution of the vehicle state so that the probability of collision with obstacles is below a specified threshold. This approach has two main advantages; first, uncertainty is often modeled more naturally using a probabilistic representation (for example in the case of uncertain localization); second, by specifying the probability of successful execution, the desired level of conservatism in the plan can be specified in a meaningful manner. The key idea behind the approach is that the probabilistic obstacle avoidance problem can be expressed as a disjunctive linear program using linear chance constraints. The resulting disjunctive linear program has the same complexity as that corresponding to the deterministic path planning problem with no representation of uncertainty. Hence the resulting problem can be solved using existing, efficient techniques, such that planning with uncertainty requires minimal additional computation. Finally, we present an empirical validation of the new method with a number of aircraft obstacle avoidance scenarios.

189 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: A novel agreement framework for multiple (possibly heterogeneous) agents evolving on a directed information graph with non-uniform delays can ensure agreement of a certain scalar quantity among the agents, as long as it has globally reachable node and the information delays are finite constants.
Abstract: We propose a novel agreement framework for multiple (possibly heterogeneous) agents evolving on a directed information graph with non-uniform delays. Our proposed framework can ensure agreement of a certain scalar quantity among the agents, as long as 1) for each agent, we can design a local control s.t. its closed-loop transfer function has unit gain at dc and gain strictly less than unity elsewhere; 2) the information graph has a globally reachable node (i.e. there exists a path from it to every other nodes); and 3) the information delays are finite constants. Rendezvous simulation is performed to verify the theory.

177 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this paper, the extended state observer (ESO) is reformulated using a generalized disturbance model, which provides a wider range of solutions for disturbance estimation problems and is shown on a realistic motion control simulation platform with favorable results.
Abstract: A brief review of developments in disturbance observers, leading up to the extended state observer (ESO), is first presented. Various digital implementations of the ESO are investigated and compared. The realization in current discrete estimator form evidently helps to maintain stable operation at low sampling rates. Digitization using zero order hold is derived symbolically to further improve accuracy while preserving the simplicity of single parameter tuning. Finally, the ESO is reformulated using a generalized disturbance model which provides a wider range of solutions for disturbance estimation problems. Application of the proposed algorithm is shown on a realistic motion control simulation platform with favorable results.

175 citations


Proceedings Article•DOI•
14 Jun 2006
TL;DR: The trajectories of the leaders can be viewed as exogenous control inputs, which allows to state and study questions concerning controllability and optimal control in heterogenous multi-agent applications.
Abstract: In this paper, we consider the situation where a collection of leaders dictate the motion of the followers in heterogenous multi-agent applications. In particular, the followers move according to a decentralized averaging rule, while the leaders' motion is unconstrained. Thus, the trajectories of the leaders can be viewed as exogenous control inputs, which allows us to state and study questions concerning controllability and optimal control.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: This paper builds on earlier work on dynamic CPU allocation to applications on shared servers, and presents a feedback control system consisting of two nested integral control loops for managing the QoS metric of the application along with the utilization of the allocated CPU resource.
Abstract: Virtualization and consolidation of IT resources have created a need for more effective workload management tools, one that dynamically controls resource allocation to a hosted application to achieve quality of service (QoS) goals. These goals can in turn be driven by the utility of the service, typically based on the application's service level agreement (SLA) as well as the cost of resources allocated. In this paper, we build on our earlier work on dynamic CPU allocation to applications on shared servers, and present a feedback control system consisting of two nested integral control loops for managing the QoS metric of the application along with the utilization of the allocated CPU resource. The control system was implemented on a lab testbed running an Apache Web server and using the 90th percentile of the response times as the QoS metric. Experiments using a synthetic workload based on an industry benchmark validated two important features of the nested control design. First, compared to a single loop for controlling response time only, the nested design is less sensitive to the bimodal behavior of the system resulting in more robust performance. Second, compared to a single loop for controlling CPU utilization only, the new design provides a framework for dealing with the tradeoff between better QoS and lower cost of resources, therefore resulting in better overall utility of the service.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: This paper addresses the development of a vision-based target tracking system for a small unmanned air vehicle that performs autonomous tracking of a moving target, while simultaneously estimating GPS coordinates of the target.
Abstract: This paper addresses the development of a vision-based target tracking system for a small unmanned air vehicle. The algorithm performs autonomous tracking of a moving target, while simultaneously estimating GPS coordinates of the target. A low cost off the shelf system is utilized, with a modified radio controlled aircraft airframe, gas engine and servos. Tracking is enabled using a low-cost, miniature pan-tilt gimbal. The control algorithm provides rapid and sustained target acquisition and tracking capability. A target position estimator was designed and shown to provide reasonable targeting accuracy. The impact of target loss events on the control and estimation algorithms is analyzed in detail.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this paper, the vector fields are used to represent desired ground track headings to direct the UAV onto the desired path, and the key feature of this approach is that ground track heading error and lateral following error approach zero asymptotically even in the presence of constant wind disturbances.
Abstract: This paper presents a new method for unmanned aerial vehicle path following using vector fields to represent desired ground track headings to direct the vehicle onto the desired path. The key feature of this approach is that ground track heading error and lateral following error approach zero asymptotically even in the presence of constant wind disturbances. Methods for following straight-line and circular-orbit paths, as well as combinations of straight lines and arcs, are presented. Experimental results validate the effectiveness of this path following approach for small air vehicles flying in high-wind conditions.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: A full order nonlinear unknown input observer (NUIO) for a class of Lipschitz nonlinear systems with unknown inputs is designed and a sufficient NUIO existence condition which requires solving a nonlinear matrix inequality is derived.
Abstract: A full order nonlinear unknown input observer (NUIO) for a class of Lipschitz nonlinear systems with unknown inputs is designed. A sufficient NUIO existence condition which requires solving a nonlinear matrix inequality is derived. To avoid solving the nonlinear matrix inequality directly, the existence condition is then reformulated as a new sufficient existence condition in terms of an LMI. An important advantage of this LMI based condition is that it enables us to design the proposed full order NUIO using Matlab LMI toolbox and thus makes the difficult NUIO design problem an easy task for the considered class of nonlinear systems. The new sufficient condition, when applied to linear systems, is also necessary. An example is given to show how to use the LMI approach to design the proposed NUIO, and simulation results are presented.

Proceedings Article•DOI•
Jinming Liu1, Huei Peng1•
14 Jun 2006
TL;DR: A dynamic model is developed to investigate the control strategy of the THS power train and an equivalent consumption minimization strategy (ECMS) is developed which is based on instantaneous optimization concept.
Abstract: Toyota hybrid system (THS) is used in the current best-selling hybrid vehicle on the market - the Toyota Prius. This hybrid system contains a power split planetary gear system which combines the benefits of series and parallel hybrid vehicles. This paper first develops a dynamic model to investigate the control strategy of the THS power train. An equivalent consumption minimization strategy (ECMS) is developed which is based on instantaneous optimization concept. The dynamic programming (DP) technique is then utilized to obtain a performance benchmark and insight toward fine-tuning of the ECMS algorithm for better performance.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: Using this algorithm, the average-consensus problem is solved under switching network topologies provided that the network switch between instantaneously balanced, connected-over-time networks.
Abstract: This paper develops a distributed algorithm for average-consensus in a discrete-time framework based on a formal matrix limit definition of average-consensus. Using this algorithm, the average-consensus problem is solved under switching network topologies provided that the network switch between instantaneously balanced, connected-over-time networks. In other words, if at each instant the network is balanced and the union of graphs over every interval T is connected, then average-consensus can be achieved. An interesting product of this analysis is the notion of "deadbeat" consensus where a system of agents achieves consensus (average or otherwise) in finite time rather than asymptotically.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, a real-time algorithm for estimation of slip angle using inexpensive sensors normally available for yaw stability control applications is presented. But the accuracy of the estimation is limited due to the presence of variations in tire-road characteristics.
Abstract: Real-time knowledge of the slip angle in a vehicle is useful in many active vehicle safety applications, including yaw stability control, rollover prevention and lane departure avoidance. Sensors to measure slip angle, including two antenna GPS systems and optical sensors are too expensive for ordinary automotive applications. This paper develops a realtime algorithm for estimation of slip angle using inexpensive sensors normally available for yaw stability control applications. Compared to previous results on slip angle estimation that have been published in literature, the algorithm utilizes a combination of model-based estimation and kinematics-based estimation and compensates for the presence of variations in tire-road characteristics. The developed algorithm is evaluated through experimental tests on a Volvo XC90 sport utility vehicle. Detailed experimental results show that the developed system can accurately estimate slip angle for a variety of test maneuvers.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, the authors explored the development of algorithms for reliable estimation of friction coefficient at each individual wheel of the vehicle and demonstrated that individual wheel friction measurements are expected to be more valuable for active safety systems than average friction measurements.
Abstract: It has long been recognized in the automotive research community that knowledge of the real-time tire-road friction coefficient can be extremely valuable for active safety applications, including traction control, yaw stability control and rollover prevention. Previous research results in literature have focused on estimation of average friction coefficient for the vehicle or on average friction coefficient for both drive wheels of the vehicle. This paper explores the development of algorithms for reliable estimation of friction coefficient at each individual wheel of the vehicle. Three different algorithms are proposed based on the types of sensors available - one that utilizes engine torque, brake torque and GPS measurements, one that utilizes torque measurements and an accelerometer and one that utilizes GPS measurements and an accelerometer. These algorithms are first evaluated in simulation and then evaluated experimentally on a Volvo XC90 sport utility vehicle. Experimental results demonstrate that friction coefficients at the individual wheels and road gradient can both be estimated reliably. Individual wheel friction measurements are expected to be more valuable for active safety systems than average friction measurements.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: It is shown that it is always possible to design a control law as the gradient of a suitably-defined navigation function whose minimum corresponds to the desired configuration.
Abstract: We propose a decentralized cooperative controller for a group of mobile agents. The control design is based on the navigation function formalism. The aim of the group control law is to generate a pattern or formation in a given workspace while avoiding obstacles and collisions. The desired goal is specified in terms of distances among the agents. We show that it is always possible to design a control law as the gradient of a suitably-defined navigation function whose minimum corresponds to the desired configuration. Furthermore in certain cases, such as when the topology of the interconnection is an acyclic graph, this minimum is unique. Some simulations are shown to test the strategy.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, a model predictive control (MPC) approach to active steering is presented for autonomous vehicle systems, which stabilizes a vehicle along a desired path while rejecting wind gusts and fulfilling its physical constraints.
Abstract: A model predictive control (MPC) approach to active steering is presented for autonomous vehicle systems. The controller is designed to stabilize a vehicle along a desired path while rejecting wind gusts and fulfilling its physical constraints. Simulation results of a side wind rejection scenario and a double lane change maneuver on slippery surfaces show the benefits of the systematic control methodology used. A trade-off between the vehicle speed and the required preview on the desired path for vehicle stabilization is highlighted.

Journal Article•DOI•
14 Jun 2006
TL;DR: It is shown that the feasibility of a parametrized collection of mode-dependent coupled algebraic Riccati equations and inequalities are both sufficient and necessary for the existence of a robust decentralized switching controller.
Abstract: We address the problem of decentralized robust control of uncertain Markov jump parameter systems via output feedback, which extends recent results on decentralized state feedback control. It is shown that the feasibility of a parametrized collection of mode-dependent coupled algebraic Riccati equations and inequalities are both sufficient and necessary for the existence of a robust decentralized switching controller. A guaranteed upper bound on robust performance is also obtained.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this paper, the authors explore the implementation of MPC technology into reconfigurable hardware such as a FPGA chip and present a rapid prototyping environment suitable for exploring the various implementation issues to bring MPC onto a chip.
Abstract: With its natural ability in handling constraints, model predictive control (MPC) has become an established control technology in the petrochemical industry, and its use is currently being pioneered in an increasingly wide range of process industries. It is also being proposed for a range of higher bandwidth applications, such as ships, aerospace and road vehicles. To extend its applications to miniaturized devices and/or embedded systems, this paper explores the implementation of the MPC technology into reconfigurable hardware such as a FPGA chip. A rapid prototyping environment suitable for exploring the various implementation issues to bring MPC onto a chip is described. Tests were conducted to verify the applicability of the "MPC on a chip" idea. It is shown that a modest FPGA chip could be used to implement a reasonably sized constrained MPC controller.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: An algorithm to monitor an environmental boundary with mobile sensors to optimally approximate the boundary with a polygon is proposed and an algorithm that distributes the vertices of the approximating polygon uniformly along the boundary is designed.
Abstract: In this paper we propose and analyze an algorithm to monitor an environmental boundary with mobile sensors. The objective is to optimally approximate the boundary with a polygon. The mobile sensors rely only on sensed local information to position some interpolation points and define an approximating polygon. We design an algorithm that distributes the vertices of the approximating polygon uniformly along the boundary. The notion of uniform placement relies on a metric inspired by known results on approximation of convex bodies. The algorithm is provably convergent for static boundaries and also for slowly-moving boundaries because of certain input-to-state stability properties.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: This paper establishes an existence theorem for the connectivity maintenance problem by introducing a novel state-dependent graph, called the double-integrator disk graph, and designs a distributed "flow-control" algorithm to compute optimal connectivity-maintaining controls.
Abstract: In this paper we consider ad-hoc networks of robotic agents with double integrator dynamics. For such networks, the connectivity maintenance problems are: (i) do there exist control inputs for each agent to maintain network connectivity, and (ii) given desired controls for each agent, can one compute the closest connectivity-maintaining controls in a distributed fashion. The proposed solution is based on three contributions. First, we define and characterize admissible sets for double integrators to remain inside disks. Second, we establish an existence theorem for the connectivity maintenance problem by introducing a novel state-dependent graph, called the double-integrator disk graph. Finally, we design a distributed "flow-control" algorithm to compute optimal connectivity-maintaining controls.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, the authors generalize the constraint tightening approach to robust model predictive control, which guarantees robust feasibility and convergence for a constrained linear system subject to persistent, unknown but bounded disturbances.
Abstract: This paper generalizes the constraint tightening approach to robust model predictive control, which guarantees robust feasibility and convergence for a constrained linear system subject to persistent, unknown but bounded disturbances. The constraints in the optimization are tightened in a monotonic sequence such that a predetermined candidate correction policy is feasible for all possible disturbances. The generalization in this paper enables the candidate policy to be time-varying and considers a general convergence problem. A key feature of the generalization is the potential to use a range of nilpotent candidate policies, which eliminate the need to compute a robustly invariant terminal constraint set.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: The main objective of this paper is to open the route to the use of MILP solutions (based on simple linear UAV models) in order to initialize NLP solvers which allow the use to enforce flyability constraints on more detailed Uav models at any desired level of detail.
Abstract: We consider the problem of optimal cooperative three-dimensional conflict resolution involving multiple unmanned air vehicles (UAVs) using numerical trajectory optimization methods. The conflict problem is posed as an optimal control problem of finding trajectories that minimize a certain objective function while maintaining the safe separation between each UAV pair. We assume the origin and destination of the UAV are known and consider UAV models with simplified linear kinematics. The main objective of this report is to present two different approaches to the solution of the problem. In the first approach, the optimal control is converted to a finite dimensional nonlinear program (NLP) by using collocation on finite elements and by reformulating the disjunctions involved in modeling the protected zones by using continuous variables. In the second approach the optimal control is converted to a finite dimensional mixed integer linear program (MILP) using Euler discretization and reformulating the disjunctions involved with the protected zones by using binary variables and Big-M techniques. Based on results of extensive random simulations, we compare time complexity and optimality of the solutions obtained with the MILP approach and the NLP approach. NLPs are essential to enforce flyability constraints on more detailed UAV models. Moreover, any nonlinear extensions to the problem cannot be dealt with by MILP solvers. The main objective of this paper is to open the route to the use of MILP solutions (based on simple linear UAV models) in order to initialize NLP solvers which allow the use of dynamic UAV models at any desired level of detail.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: Distributed estimation algorithms that allow robots in a communication network to maintain estimates of summary statistics describing the shape of the swarm result in the swarm formation statistics being driven to desired values in the presence of a changing network topology and the addition and deletion of robots.
Abstract: We describe distributed estimation algorithms that allow robots in a communication network to maintain estimates of summary statistics describing the shape of the swarm. We show that these estimators, combined with motion controllers implemented on each robot, result in the swarm formation statistics being driven to desired values in the presence of a changing network topology and the addition and deletion of robots.

Proceedings Article•DOI•
14 Jun 2006
TL;DR: In this article, the authors consider the flocking of multiple agents which have significant inertias and evolve on a balanced information graph and propose a provably stable flocking control law, which ensures that the internal group formation is exponentially stabilized to a desired shape.
Abstract: We consider the flocking of multiple agents which have significant inertias and evolve on a balanced information graph. We first show that flocking algorithms that neglect agents' inertial effect can cause unstable group behavior. To incorporate this inertial effect, we use the passive decomposition, which decomposes the closed-loop group dynamics into two decoupled systems: a shape system representing the internal group formation, and a locked system describing the motion of the center-of-mass. Then, analyzing the locked and shape systems separately with the help of graph theory, we propose a provably-stable flocking control law, which ensures that the internal group formation is exponentially stabilized to a desired shape, while all the agents' velocities converge to the centroid velocity that is also shown to be time-invariant. This result still holds for slowly-switching balanced information graphs. Simulation is performed to validate the theory.

Proceedings Article•DOI•
Chengyu Cao1, Naira Hovakimyan1•
14 Jun 2006
TL;DR: A novel adaptive control architecture is presented that ensures that the input and output of an uncertain linear system track the input or output of a desired linear system during the transient phase, in addition to the asymptotic tracking.
Abstract: In this paper, we present a novel adaptive control architecture that ensures that the input and output of an uncertain linear system track the input and output of a desired linear system during the transient phase, in addition to the asymptotic tracking. Design guidelines are presented to ensure that the desired transient specifications can be achieved for both system's input and output signals. The tools from this paper can be used to develop a theoretically justified verification and validation framework for adaptive systems. Simulation results illustrate the theoretical findings