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Physical systems typically evolve continuously whereas modern controllers and signal processing devices invariably operate in discrete time. Hence sampling arises as a cornerstone problem in essentially all aspects of modern systems science. This paper reviews various aspects of sampling of signals and systems. We argue that careful consideration must be given to sampling to obtain meaningful results...
The world's first robotic insect capable of vertical takeoff was developed and demonstrated by the Harvard Microrobotics Lab. This vehicle consisted of a single power actuator that drove both wings symmetrically. In this case, there was no method to generate body torques, only lift could be modulated. The Harvard Microrobotics Lab has modified this configuration to include not only a single power...
This paper details the flight dynamics and control of a prototype mono-wing rotorcraft that mimics the passive transit of the species of samara (winged seed), Acer diabolicum Blume. The asymmetric and all-rotating platform requires the development of a novel sensing and control framework. The general rigid body dynamics are separated into rotor dynamics and particle navigation, which are derived for...
A new optimal distributed linear averaging (ODLA) problem is presented in this paper. This problem is motivated from the distributed averaging problem which arises in the context of distributed algorithms in computer science and coordination of groups of autonomous agents in engineering. The aim of the ODLA problem is to compute the average of the initial values at nodes of a graph through an optimal...
This paper presents modification of the conventional model reference adaptive control (MRAC) architecture in order to achieve guaranteed transient performance both in the output and input signals of an uncertain system. The proposed modification is based on the tracking error feedback to the reference model. It is shown that approach guarantees tracking of a given command and the ideal control signal...
Adaptive control using multiple identification models is currently well established. Switching, tuning, and switching and tuning in such systems have been extensively investigated, and their stability properties have been established [1]. If the number of models is sufficiently large, and is uniformly distributed in parameter space, the method results in fast and accurate response. In practice, even...
This paper deals with a quadratic optimization problem for linear impulsive hybrid systems. We study a class of LQ-type impulsive hybrid optimal control problems (OCPs) and consider the application of the hybrid Maximum Principle (MP). Our aim is to investigate the natural relationship between the Pontryagin-type MP and the Bellman Dynamic Programming (DP) approach. As next we develop the “hybrid”...
A reduced-order globally convergent observer to estimate the depth of an object projected on the image plane of a camera is presented, assuming that the object is planar or has a planar limb surface and the orientation of the plane is known. A local result can be obtained when the plane unit normal is unknown, and the latter is estimated together with the depth of the object. The observer exploits...
In this paper, we study the output synchronization problem of networked Euler-Lagrange(EL) systems subject to nonholonomic constraints. An EL system subject to nonholonomic constraints can be input-output linearized if a proper decoupling matrix can be found, and the linearized form is equivalent to a double integrator. Although a double integrator is not a passive system, with proper design of the...
Cognitive radio systems are currently a popular topic and are a good prospect for research when combined with control technology. In this paper, we consider the control and estimation via a two switch model which can represent a cognitive radio system. We provide an optimal estimator for this model and demonstrate that the optimal LQG controller is not a linear gain of the estimate of the states,...
This paper considers the problem of time-domain assessment of the Phase Margin (PM) of a Single Input Single Output (SISO) Linear Time-Invariant (LTI) system using a singular perturbation approach, where a SISO LTI fast loop system, whose phase lag increases monotonically with frequency, is introduced into the loop as a singular perturbation with a singular perturbation (time-scale separation) parameter...
This paper is concerned with finite frequency negative imaginary (FFNI) systems. The paper introduces the concept of FFNI transfer function matrices, and the relationship between the FFNI property and the finite frequency positive real (FFPR) property of transfer function matrices is established. The paper also establishes an FFNI lemma which gives a necessary and sufficient condition on the matrices...
This paper discusses the infinite horizon static output feedback Nash games for stochastic weakly-coupled large-scale systems with state-dependent noise. It is shown that the conditions for the existence of Nash equilibria depend on the solutions of a new set of cross-coupled stochastic algebraic Riccati equations (CSAREs). After establishing the asymptotic structure along with the positive semidefiniteness...
A wooden game board named Shoot-the-Moon has interesting dynamics properties despite its simple structure of one steel ball rolling on two cylindrical rods. In this paper, we derive the equations of motion for Shoot-the-moon using an Eular-Lagrangian approach and explore its underactuated, nonlinear, nonholonomic dynamics. Two positon controllers are designed, one for a local linearization and another...
The straight beam in the ball and beam control experiment was replaced by a curved beam mounted away from its center of rotation. The resulting system is much harder to understand, model and control than the ball and straight beam. Nonetheless, the apparatus was constructed, a model was derived using Lagrangian mechanics, and a controller was designed using a linearized model and the LQR. This controller...
Reinforcement learning is a promising paradigm for learning optimal control. We consider policy iteration (PI) algorithms for reinforcement learning, which iteratively evaluate and improve control policies. State-of-the-art, least-squares techniques for policy evaluation are sample-efficient and have relaxed convergence requirements. However, they are typically used in offline PI, whereas a central...
This paper derives the rate of convergence for the distribution free learning problem when the observation process is an exponentially strongly mixing (α-mixing with an exponential rate) Markov chain. If {zk}K=1∞ = {(xk, yk)}k=1∞ ⊂ x × Y ≡ Z is an exponentially strongly mixing Markov chain with stationary measure ρ, it is shown that the empirical estimate fz that minimizes the discrete quadratic risk...
We study two-player security games which can be viewed as sequences of nonzero-sum matrix games played by an Attacker and a Defender. The evolution of the game is based on a stochastic fictitious play process. Players do not have access to each other's payoff matrix. Each has to observe the other's actions up to present and plays the action generated based on the best response to these observations...
The paper presents two open loop methods to control the unstable, longitudinal oscillation of a flapping wing micro-air vehicle (FWMAV). The dynamic model of the FWMAV is derived by modeling the FWMAV as three rigid bodies (two wings and a central body) and through the use of D'Alembert's principle for multiple rigid bodies. The unstable pitching of the central body is controlled through the use of...
A peak-seeking control method is presented which utilizes a linear time-varying Kalman filter. Performance function coordinate and magnitude measurements are used by the Kalman filter to estimate the gradient and Hessian of the performance function. The gradient and Hessian are used to command the system toward a local extremum. The method is naturally applied to multiple-input multiple-output systems...
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