Control Problem Of Vehicle Research Articles

Two layer optimal vehicle control for known routes

Autonomous vehicles could bring a significant benefit in terms of fuel consumption and emissions, besides safety and comfort, but the full potential can only be exploited if the appropriate (optimal) control is applied. However complexity of optimal control can prevent its use in practice. Therefore, we suggest to approximate the optimal vehicle control problem by a two-layer structure in which the upper level provides a solution for the reference speed trajectory using energy consumption as cost function, while the lower one optimally tracks the reference speed considering fuel consumption and emissions. The key advantage is the simplicity of the upper layer, which reduces the computational burden, albeit with some expected loss of optimality if compared to the global optimum. The control and results are shown using a model of a production vehicle with a CI engine. The possibility of using this approach to trade-off fuel vs. NOx is discussed. The authors believe that splitting the optimization problem into a multilayer structure is a sensible approach to enforce computational tractability while recovering part of the optimization potential

An Input-to-State-Stability Approach to Economic Optimization in Model Predictive Control

This paper presents a model predictive control (MPC) scheme where a combination of a stabilizing stage cost and an economic stage cost is employed to allow the minimization of an economic performance index while still guaranteeing convergence toward a desired steady state. Input-to-state-stability with respect to the economic stage cost is provided. More precisely, for the case of an economic stage cost converging to zero, the economic optimization only affects the transient behavior of the closed-loop trajectories preserving the convergence to the desired steady state. Alternatively, if the economic stage cost is merely bounded, or convergent to a bound, the closed-loop state trajectory is ultimately bounded around the desired steady state with the size of the bound being monotonically increasing with the magnitude of the economic stage cost. The loosening of the closed-loop guarantees, i.e., moving from convergence to ultimate boundedness, gives space to the increase of economic performance. Numerical results illustrate the effectiveness of the proposed method on an energy efficient trajectory-tracking control problem of a marine robotic vehicle navigating in the presence of water currents.

Finite-time attitude tracking control design for reusable launch vehicle in reentry phase based on disturbance observer

For the attitude tracking control problem of reentry reusable launch vehicle in reentry phase, a disturbance observer–based sliding mode controller is proposed in this article. At first, attitude m...

Semianalytical minimum‐time solution for the optimal control of a vehicle subject to limited acceleration

SummaryA semianalytic solution of the minimum‐time optimal control problem of a carlike vehicle is herein presented. The vehicle is subject to the effect of laminar (linear) and aerodynamic (quadratic) drag, taking into account the asymmetric bounded longitudinal accelerations. This yields a nonlinear differential equation of the Riccati kind. The associated analytic solution exists in closed form, but it is numerically ill conditioned in some situations; hence, it is reformulated using asymptotic expansions that keep the numerical computations accurate and robust in all cases. Therefore, the proposed algorithm is designed to be fast and robust in sight to be the fundamental module of a more extended optimal control problem that considers a given clothoid curve as the trajectory and the presence of a constraint on the lateral acceleration of the vehicle. The numerical stability of the computation for limit values of the parameters is essential, as shown in the numerical tests.

Geometric and numerical methods for a state constrained minimum time control problem of an electric vehicle

In this article, the minimum time control problem of an electric vehicle is modeled as a Mayer problem in optimal control, with affine dynamics with respect to the control and with state constraints. The candidates as minimizers are selected among a set of extremals, solutions of a Hamiltonian system given by the maximum principle. An analysis, with the techniques of geometric control, is used first to reduce the set of candidates and then to construct the numerical methods. This leads to a numerical investigation based on indirect methods using the HamPath software. Multiple shooting and homotopy techniques are used to build a synthesis with respect to the bounds of the boundary sets.

Finite-time tracking control of hypersonic vehicle with input saturation

This paper studies the finite-time tracking control problem of hypersonic vehicle in presence of model parameter uncertainties, external disturbance and input saturation. Firstly, to cope with the unknown upper bound disturbance of the system, an adaptive fast terminal sliding mode controller is designed based on a non-homogeneous disturbance observer (NHDO) which can alleviate the chattering and make the proposed controller strongly robust. Meanwhile, a new saturation function is introduced to solve the singular problems of the controller. Secondly, to further solve the problem of input saturation, the hyperbolic tangent function and auxiliary system are introduced to design an anti-saturation fast adaptive terminal sliding mode controller which not only can satisfy the requirements of the actuator's physical limitation, but also guarantees that the sliding mode manifold is finite-time stable. Finally, Lyapunov theory is used to prove the stability of the designed controller strictly, and the numerical simulations of the longitudinal model of the hypersonic vehicle are carried out, which further confirm the robustness and effectiveness of the two designed controllers.

Finite-time formation control for multiple flight vehicles with accurate linearization model

The finite-time leader–follower formation control problem of Multiple Flight Vehicle (MFV) system with accurate linearization model is considered. Herein, there is only one leader, the interaction topology among the followers is undirected, and the followers are reachable from the leader. Precise feedback linearization based on differential geometry theory is used to linearize the nonlinear motion model of the flight vehicle and the system model with follower track errors is formulated. A distributed formation control protocol based on finite-time control theory is proposed. With the designed control law, the MFV systems can achieve the desired formation in finite time, where the formation configurations can be specified in advance according to the task requirements. Meanwhile, the convergence analysis is proved and the protocol performance is discussed. Finally, simulation results further demonstrate the effectiveness of the proposed method.

Learning an Optimization Algorithm Through Human Design Iterations

Solving optimal design problems through crowdsourcing faces a dilemma: On the one hand, human beings have been shown to be more effective than algorithms at searching for good solutions of certain real-world problems with high-dimensional or discrete solution spaces; on the other hand, the cost of setting up crowdsourcing environments, the uncertainty in the crowd's domain-specific competence, and the lack of commitment of the crowd contribute to the lack of real-world application of design crowdsourcing. We are thus motivated to investigate a solution-searching mechanism where an optimization algorithm is tuned based on human demonstrations on solution searching, so that the search can be continued after human participants abandon the problem. To do so, we model the iterative search process as a Bayesian optimization (BO) algorithm and propose an inverse BO (IBO) algorithm to find the maximum likelihood estimators (MLEs) of the BO parameters based on human solutions. We show through a vehicle design and control problem that the search performance of BO can be improved by recovering its parameters based on an effective human search. Thus, IBO has the potential to improve the success rate of design crowdsourcing activities, by requiring only good search strategies instead of good solutions from the crowd.

Position Tracking Control for an Aerial Robot Passively Tethered to an Independently Moving Platform

We study the control problem of an aerial vehicle moving in the 3D space and connected to an independently moving platform through a physical link (e.g., a cable, a chain or a rope). The link is attached to the moving platform by means of a passive winch. The latter differs from an active winch by producing only a constant uncontrollable torque. We solve the problem of exact tracking of the 3D position of the aerial vehicle, either absolute or with respect to the moving platform, while the platform is independently moving. We prove two intrinsic properties of the system, namely, the dynamic feedback linearizability and the differential flatness with respect to the output of interest. Exploiting this properties we design a nonlinear controller able to exponentially steer the position of the aerial robot along any sufficiently smooth time-varying trajectory. The proposed method is tested through numerical simulations in several non-ideal cases.

Nonlinear robust adaptive sliding mode control design for miniature unmanned multirotor aerial vehicle

This paper addresses the stability and tracking control problem of miniature unmanned multirotor aerial vehicle (MUMAV) in the presence of bounded uncertainty. The uncertainty may appear from unmodeled dynamics, underactuated property, input disturbance and flying environment. Nonlinear robust adaptive sliding mode control algorithm is designed by using Lyapunov function. Robust adaptation laws are designed to learn and compensate the bounded parametric uncertainty. Lyapunov analysis shows that the proposed algorithms can guarantee asymptotic stability and tracking control property of the linear and angular dynamics of MUMAV system. Compared with other existing control methods, the proposed design is very simple and easy to implement as it does not require multiple design steps, augmented auxiliary signals and exact bound of the uncertainty. Experimental results on a miniature unmanned quadrotor aerial vehicle are presented to illustrate of effectiveness of the proposed design for real-time applications.

A new state-of-charge estimation method for electric vehicle lithium-ion batteries based on multiple input parameter fitting model

Summary The estimation of state-of-charge (SOC) is crucial to determine the remaining capacity of the Lithium-Ion battery, and thus plays an important role in many electric vehicle control and energy storage management problems. The accuracy of the estimated SOC depends mostly on the accuracy of the battery model, which is mainly affected by factors like temperature, State of Health (SOH), and chemical reactions. Also many characteristic parameters of the battery cell, such as the output voltage, the internal resistance and so on, have close relations with SOC. Battery models are often identified by a large amount of experiments under different SOCs and temperatures. To resolve this difficulty and also improve modeling accuracy, a multiple input parameter fitting model of the Lithium-Ion battery and the factors that would affect the accuracy of the battery model are derived from the Nernst equation in this paper. Statistics theory is applied to obtain a more accurate battery model while using less measurement data. The relevant parameters can be calculated by data fitting through measurement on factors like continuously changing temperatures. From the obtained battery model, Extended Kalman Filter algorithm is applied to estimate the SOC. Finally, simulation and experimental results are given to illustrate the advantage of the proposed SOC estimation method. It is found that the proposed SOC estimation method always satisfies the precision requirement in the relevant Standards under different environmental temperatures. Particularly, the SOC estimation accuracy can be improved by 14% under low temperatures below 0 °C compared with existing methods. Copyright © 2017 John Wiley & Sons, Ltd.

Research on the water-entry attitude of a submersible aircraft.

BackgroundThe water entry of a submersible aircraft, which is transient, highly coupled, and nonlinear, is complicated. After analyzing the mechanics of this process, the change rate of every variable is considered. A dynamic model is build and employed to study vehicle attitude and overturn phenomenon during water entry. Experiments are carried out and a method to organize experiment data is proposed. The accuracy of the method is confirmed by comparing the results of simulation of dynamic model and experiment under the same condition.ResultsBased on the analysis of the experiment and simulation, the initial attack angle and angular velocity largely influence the water entry of vehicle. Simulations of water entry with different initial and angular velocities are completed, followed by an analysis, and the motion law of vehicle is obtained. To solve the problem of vehicle stability and control during water entry, an approach is proposed by which the vehicle sails with a zero attack angle after entering water by controlling the initial angular velocity. With the dynamic model and optimization research algorithm, calculation is performed, and the optimal initial angular velocity of water-entry is obtained.ConclusionsThe outcome of simulations confirms that the effectiveness of the propose approach by which the initial water-entry angular velocity is controlled.

Attitude tracking control for Mars entry vehicle via T-S model with time-varying input delay

This paper focuses on the attitude tracking control problem of Mars entry vehicle (MEV) with time-varying input delay. The original attitude dynamics of MEV is divided into slow subsystem and fast subsystem. For slow subsystem, the dynamic inversion method is used to generate the angular velocity command. For fast subsystem, a T-S fuzzy model is used to approximate it, and delays-dependent \(H_{\infty }\) attitude tracking control is applied to reduce the effects of delay on attitude dynamics. Specially, a decomposition coefficient of delay integral inequality is introduced in our proposed results, which may further reduce the design algorithm conservatism. Finally, numerical simulations are used to verify the effectiveness of the proposed method.

Disturbance observer–based dynamic surface control design for a hypersonic vehicle with input constraints and uncertainty

This article presents the flight control problem of a flexible air-breathing hypersonic vehicle under input constraint and aerodynamic uncertainty. First, a control-oriented model is derived and decomposed into velocity subsystem and altitude subsystem, in which compounded disturbances are included to consider aerodynamic uncertainty and the effect of the flexible modes. Second, nonlinear disturbance observer technique is employed to estimate the compounded disturbance, where the estimation error converges to a compact set if the observer design parameters are chosen appropriately. Then, based on disturbance observer, a robust controller and a dynamic surface controller are developed, respectively, for the velocity subsystem and the altitude subsystem. Third, novel robust first-order filters are designed to overcome the “explosion of terms” problem induced by backstepping method. Additional systems are constructed to tackle input constraints. By rigorously Lyapunov stability proof, the designed control strategy can assure that tracking error converges to an arbitrarily small neighborhood around zero. Finally, simulations are performed to show the effectiveness of the presented control strategy.

Control of Autonomous Underwater Vehicle using Reduced Order Model Predictive Control in Three Dimensional Space

The paper investigates the motion control problem of Autonomous Underwater Vehicle (AUV) in three-dimensional space. Here, we consider a non-linear, nonholonomic and highly under-actuated dynamical model of AUV with six degrees of freedom. Because of its higher-dimensional complex model, the traditional model predictive control technique leads to computational complexity and loss of controllability. The paper proposes a novel MPC scheme using reduced dynamical model. In which, the MPC problem to control AUV in vertical and horizontal planes is formulated as independent optimization problems. The proposed scheme reduces higher-dimensional model to two independent time-varying linearized models for controlling motion in vertical and horizontal planes by neglecting weakly coupled dynamics. Further the reduced optimization problem is solved using quadratic programming to achieve trade-off between computational complexity and control effort optimization. The simulation results show the effectiveness of the proposed control scheme which is employed on non-linear model.

Genetic Fuzzy based Artificial Intelligence for Unmanned Combat Aerial Vehicle Control in Simulated Air Combat Missions

Breakthroughs in genetic fuzzy systems, most notably the development of the Genetic Fuzzy Tree methodology, have allowed fuzzy logic based Artificial Intelligences to be developed that can be applied to incredibly complex problems. The ability to have extreme performance and computational efficiency as well as to be robust to uncertainties and randomness, adaptable to changing scenarios, verified and validated to follow safety specifications and operating doctrines via formal methods, and easily designed and implemented are just some of the strengths that this type of control brings. Within this white paper, the authors introduce ALPHA, an Artificial Intelligence that controls flights of Unmanned Combat Aerial Vehicles in aerial combat missions within an extreme-fidelity simulation environment. To this day, this represents the most complex application of a fuzzy-logic based Artificial Intelligence to an Unmanned Combat Aerial Vehicle control problem. While development is on-going, the version of ALPHA presented withinwas assessed by Colonel (retired)Gene Lee who described ALPHA as “the most aggressive, responsive, dynamic and credible AI (he’s) seen-to-date.” The quality of these preliminary results in a problem that is not only complex and rife with uncertainties but also contains an intelligent and unrestricted hostile force has significant implications for this type of Artificial Intelligence. This work adds immensely to the body of evidence that this methodology is an ideal solution to a very wide array of problems.

Nonlinear Adaptive Bottom-Following Control of an AUV in the Presence of Ocean Currents

This paper addresses the bottom-following control problem of an underactuated autonomous underwater vehicle (AUV) in the presence of ocean currents and model parameters uncertainties. The Serret-Frenet frame is used to describe the bottom following of the AUV. An extra degree of freedom for controller design is introduced. The extra degree of freedom makes the virtual AUV can regulate its velocity along with the real AUV. Based on Lyapunov theory and backstepping techniques, a nonlinear adaptive control law is derived. The control law yields convergence of the AUV to the desired path asymptotically. Simulations results show the effectiveness and robustness of the derived controllers.

Observer-based finite-time sliding mode control for reentry vehicle

Purpose – The purpose of this paper is to design a disturbance observer-based finite-time global sliding mode control scheme for the attitude tracking control problem of the reentry vehicle with parameter uncertainties and disturbances. Design/methodology/approach – Feedback linearization is first introduced to transform vehicle model into three independent second order uncertain subsystems. Then a finite-time controller (FTC) is proposed for the nominal system on the basis of the homogeneity theory. Thereafter the integral sliding mode method is introduced for the vehicle with disturbances. The finite time convergence is achieved and global robustness is also assured by the combination of finite time control method and integral sliding mode strategy. Furthermore, to improve the attitude angle tracking accuracy a novel finite time disturbance observer (DO) is constructed. Findings – Simulation is made for the reentry vehicle with disturbances involved. And the results show the finite-time convergence, tracking accuracy and robustness of the proposed strategy. Originality/value – The proposed control strategy has three advantages. First of all it can achieve finite time convergence and avoid singularity. Moreover, it can also realize global robustness. Finally, a new kind of DO is introduced to improve the tracking accuracy.

Diving control of Autonomous Underwater Vehicle based on improved active disturbance rejection control approach

The control problem of Autonomous Underwater Vehicle (AUV) is a very challenging one since the mathematical model of AUV is characterized by high nonlinearity, strongly coupling and time-varying features. In this paper, our aim is to design a diving active disturbance rejection controller for AUV. Firstly, a mathematical model of AUV is established, and the mathematical model is subsequently decoupled into three subsystems including speed control model, diving control model and steering control model. Then, an improved tracking differentiator is employed, which can provide better noise attenuation performance and avoid the chattering phenomenon as compared to the traditional tracking differentiator. After that, the controller is designed by using the active disturbance rejection control (ADRC) with the improved tracking differentiator. Finally, simulations are given to shown the effectiveness of the developed control scheme.

Continuous nonlinear asymptotic tracking control of an air-breathing hypersonic vehicle with flexible structural dynamics and external disturbances

In this paper, the tracking control problem of an air-breathing hypersonic vehicle with structural flexibility is addressed. Due to the harsh high Mach flight condition, the influence associated with the dynamic flexible modes of the hypersonic vehicle cannot be neglected. These flexible dynamic modes, which are affected by the vehicle’s states and control surface deflections, can be viewed as an internal dynamics associated with the system outputs. A new nonlinear robust continuous tracking controller is developed to drive the vehicle’s outputs, which include the vehicle’s velocity, altitude, and attack angle, to track the desired time-varying trajectories in the presence of flexible structural dynamics, parametric uncertainties, and external nonvanishing disturbances. A Lyapunov-based stability analysis is employed to prove that the proposed control design can achieve asymptotic tracking while keeping the internal dynamics to be bounded-input/bounded-output stable. Numerical simulations are performed on the full nonlinear dynamic model to demonstrate the tracking performance of the controller, and highlight the robustness with respect to parametric uncertainties and external disturbances.