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The problem of the charged particle beam dynamics optimization considering particles' distribution density is studied. A combination of a smooth and non-smooth functionals is considered. The expression for the variation of the combined functional and the necessary condition for the optimal control are obtained.
A novel learning Model Predictive Control technique is applied to the autonomous racing problem. The goal of the controller is to minimize the time to complete a lap. The proposed control strategy uses the data from previous laps to improve its performance while satisfying safety requirements. A system identification technique is proposed to estimate the vehicle dynamics. Simulation results with the...
Multi-UAV systems are safety-critical, and guarantees must be made to ensure no unsafe configurations occur. Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems; however, its direct application is limited to small-scale systems of no more than two vehicles due to an exponentially-scaling computational complexity. Previously, the sequential path planning (SPP) method,...
In this paper, we propose a time-optimal trajectory generation algorithm for landing a 3-DOF (x−z and tilt) quadrotor model onto a moving platform. The algorithm exploits the differential flatness of the quadrotor dynamics model and formulates a nonlinear programming problem, which is then solved to obtain the time-optimal landing trajectory. The advantages of the proposed algorithm over state-of-the-art...
In this paper, a planning approach of maneuver trajectory based on dynamic inversion is proposed, which can greatly improve the penetrability of hypersonic glide vehicles in dive phase. Maeuvering and guiding overloads are combined using a weight coefficient, which is designed as the function of altitude. Enough adjust ability is guranteed at the end of dive phase, and more complex maneuver trajectories...
This work addresses the problem of kinematic trajectory planning for mobile manipulators with non-holonomic constraints, and holonomic operational-space tracking constraints. We obtain whole-body trajectories and time-varying kinematic feedback controllers by solving a Constrained Sequential Linear Quadratic Optimal Control problem. The employed algorithm features high efficiency through a continuous-time...
We introduce an information theoretic model predictive control (MPC) algorithm capable of handling complex cost criteria and general nonlinear dynamics. The generality of the approach makes it possible to use multi-layer neural networks as dynamics models, which we incorporate into our MPC algorithm in order to solve model-based reinforcement learning tasks. We test the algorithm in simulation on...
In this paper, the falsification of predefined requirements of a control system is formulated as an optimal control problem. We propose a framework that can be used to design input trajectories such that multiple requirements can be falsified by a single test trajectory. Furthermore, an algorithm based on gradient techniques is proposed for unknown nonlinear systems. A numerical example, treating...
In this paper, we adopt a reachability-based approach to deal with the pursuit-evasion differential game between two players in the presence of dynamic environmental disturbances (e.g., winds, sea currents). We give conditions for the game to be terminated in terms of reachable set inclusions. Level set equations are defined and solved to generate the reachable sets of the pursuer and the evader....
In this work, we consider the problem of optimal precooling of thermostatic loads by a load serving entity (LSE) under time varying electricity prices. Specifically, we propose a low complexity dynamic programming based algorithm for controlling the switching of HVAC units such that the cost of cooling is minimized while ensuring that the resultant temperatures do not violate the comfort constraints...
A representation of a fundamental solution group for a class of wave equations is constructed by exploiting connections between stationary action and optimal control. By using a Yosida approximation of the associated generator, an approximation of the group of interest is represented for sufficiently short time horizons via an idempotent convolution kernel that describes all possible solutions of...
Optimal control finds an optimal input trajectory which steers an initial state to a desired final state while satisfying given state and input constraints. However, most efficient approaches are restricted to a single initial state. In this paper, we present a new approach, which combines reachability analysis with optimal control. This enables us to solve the optimal control problem for a whole...
A novel hybrid technique is discussed to numerically solve nonlinear stochastic optimal control (OC) problems with numerous potential applications. The hybrid technique combines a Legendre Pseudospectral Method (LPM) with a generalized Polynomial Chaos (gPC) method, which are highly accurate numerical methods for solving deterministic OC problems and stochastic differential equations (SDE), respectively...
This paper addresses the problem of control synthesis for nonlinear optimal control problems in the presence of state and input constraints. The presented approach relies upon transforming the given problem into an infinite-dimensional linear program over the space of measures. To generate approximations to this infinite-dimensional program, a sequence of Semi-Definite Programs (SDP)s is formulated...
In this paper we introduce a new method to solve fixed-delay optimal control problems which exploits numerical homotopy procedures. It is known that solving this kind of problems via indirect methods is complex and computationally demanding because their implementation is faced with two difficulties: the extremal equations are of mixed type, and besides, the shooting method has to be carefully initialized...
In the last years emissions related to transportation have been in the focus of various legislation changes. The soon to be introduced Worldwide Harmonized Light-Duty Vehicles Test Procedure (WLTP) is one example for that. However, as shown by recent studies a substantial, often overlooked, factor is the driver itself and fixed procedures for testing within the legislation will not help in suppressing...
This article describes the design and implementation of a Biologically-Inspired Optimal Control Strategy (BIO-CS) for hybrid energy systems. The proposed strategy mimics the ant's rule of pursuit idea in combination with optimal control and multi-agent concepts. This novel approach is developed to address coupling effects among different components of a cyber-physical fuel cell-gas turbine hybrid...
The ability to land on a slope is a meaningful capability of a quadrotor. In slope landing, the controller applied to the quadrotor should precisely control the bottom plane parallel to the slope when touching down, as well as attenuate the disturbances from nonlinearities, ground effects and other interference. In this paper, an output feedback finite-horizon optimal control is used to accurately...
The use of extrinsic stimulation to control activity in neuronal networks i.e., neurocontrol, is a key problem in control engineering and neuroscience. Here, we study the general problem of selective spiking in a population of neurons. The goal is to use an input stimulus in order to induce a spike in a specific neuron of a population while keeping all others suppressed. We formulate a strict version...
In this paper, we present a method to initialize at a feasible point and unfailingly solve a non-convex optimiza- tion problem in which a set-point motion is planned for a multi-link manipulator under state and control constraints. We construct an initial feasible solution by analyzing the final time effect for feasibility problems of flatness based motion planning problems. More specifically, we...
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