Integrated Guidance and Control of Multiple Interceptor Missiles Based on Improved Distributed Cooperative Control Strategy

This paper proposes a DSSMC (dynamic surface sliding mode control) strategy to track the desired angle for one elevation equilibrator of truck-mounted howitzer. Dynamic surface control is introduced to solve the problem of nonlinearity, unmatched external loads, parameters uncertainty and differential explosion caused by backstepping method. The stability is proved by Lyapunov method and the performance of this control strategy is verified by the method of co-simulation with AMESim and MATLAB. The co-simulation results show that, compared with PID control strategy, DSSMC strategy has better tracking accuracy and rapidity.

Adaptive robust integrated guidance and control for thrust-vector-controlled aircraft by solving LQR online

Taking input saturation and impact angle constraint into consideration, an anti-windup integrated guidance and control (IGC) scheme is proposed based on dynamic surface control technique in this paper. The auxiliary system is constructed to analyse and compensate the adverse effect of input saturation. Moreover, the finite-time extend state observer is employed to estimate and compensate the uncertainties in the IGC system. According to the stability analysis, the proposed IGC scheme can ensure that all signals in the closed-loop system are uniformly ultimately bounded in presence of input saturation. Nonlinear simulation results are proposed to illustrate the effectiveness of the proposed IGC scheme.

Impact angle-constrained integrated guidance and control for supersonic skid-to-turn missiles using backstepping with global fast terminal sliding mode control

A new cooperative braking control strategy (CBCS) is proposed for a parallel hybrid electric vehicle (HEV) with both a regenerative braking system and an antilock braking system (ABS) to achieve improved braking performance and energy regeneration. The braking system of the vehicle is based on a new method of HEV braking torque distribution that makes the antilock braking system work together with the regenerative braking system harmoniously. In the cooperative braking control strategy, a sliding mode controller (SMC) for ABS is designed to maintain the wheel slip within an optimal range by adjusting the hydraulic braking torque continuously; to reduce the chattering in SMC, a boundary-layer method with moderate tuning of a saturation function is also investigated; based on the wheel slip ratio, battery state of charge (SOC), and the motor speed, a fuzzy logic control strategy (FLC) is applied to adjust the regenerative braking torque dynamically. In order to evaluate the performance of the cooperative braking control strategy, the braking system model of a hybrid electric vehicle is built in MATLAB/SIMULINK. It is found from the simulation that the cooperative braking control strategy suggested in this paper provides satisfactory braking performance, passenger comfort, and high regenerative efficiency.

In this paper, we study cooperative control problems with a multi-UAV system. Specifically, we propose a c consensus-based cooperative formation control strategy with collision-avoidance capability for a group of multiple unmanned aerial vehicles (UAVs). To cooperatively fly in formation, a consensus-based algorithm and a leader-follower structure are applied to the UAVs. Collisions among the UAVs can occur while they are flying with the cooperative control algorithm. Therefore, we describe how the cooperatively controlled UAVs avoid collisions while they are flying to desired position for formation. The collision-avoidance strategy is based on an artificial potential approach. The convergence is guaranteed even when the cooperative formation control algorithm and the collision-avoidance control algorithm are simultaneously applied to the quadrotors. Finally, the proposed approach is validated by some simulations.

A sliding mode control algorithm based on nonlinear disturbance observer (NDO) is proposed for integrated guidance and control (IGC) system in this paper. Firstly, the IGC model is established as a linear system with mismatched uncertainties. Secondly, a NDO with finite time convergence is used to estimate the disturbances and their derivatives. Thirdly, an integral sliding mode surface is designed to obtain the rudder deflection command directly instead of the back-stepping control (BC) algorithm used in conventional IGC system, which achieves the real sense of IGC, and the stability of the system is proved strictly by Lyapunov stability theory. Finally, the superiority of the IGC method based on NDO is verified by simulation.

Three-dimensional low-order finite-time integrated guidance and control design with side-window constraint

This paper discusses a data-driven, cooperative control strategy to maximize wind farm power production. Conventionally, every wind turbine in a wind farm is operated to maximize its own power production without taking into account the interactions between the wind turbines in a wind farm. Because of wake interference, such greedy control strategy can significantly lower the power production of the downstream wind turbines and, thus, reduce the overall wind farm power production. As an alternative to the greedy control strategy, we study a cooperative wind farm control strategy that determines and executes the optimum coordinated control actions for maximizing the total wind farm power production. To determine the optimum coordinated control actions of the wind turbines, we employ a data-driven optimization method that seeks to find the optimum control actions using only the power measurement data collected from the wind turbines in a wind farm. In particular, we employ the Bayesian Ascent (BA) algorithm, a probabilistic optimization method constructed based on Gaussian Process regression and the trust region concept. Wind tunnel experiments using 6 scaled wind turbine models are conducted to assess (1) the effectiveness of the cooperative control strategy in improving the power production; and (2) the efficiency of the BA algorithm in determining the optimum control actions of the wind turbines using only the input control actions and the output power measurement data.

Distributed generators (DGs) have been developing rapidly in power systems. Motivated by their intrinsic distributed nature, distributed cooperative control based upon local communication recently emerge as a preferred strategy. For instance, a cooperative power control strategy can regulate the active power from a cluster of DGs at a certain ratio of its maximal available power according to a dispatch command. However, such a networked control system is susceptible to both communication failure and cyber-attack, e.g., denial-of-service attack and deceptive attack. To address this potential problem, an attack-resilient cooperative control strategy is proposed in this paper. With a properly designed observation network, each DG can monitor the behaviors of all its in-neighbors, and gradually isolate the misbehaving DGs (when present) from the network as long as they do not collude with each other. Consequently, even certain DGs misbehave, the rest of them can together accomplish the control objective provided that the remaining communication network is still connected. Simulations of the IEEE standard 34-bus test feeder demonstrate effectiveness of the proposed strategy.

<div class="section abstract"><div class="htmlview paragraph">To meet the traffic control demands of highway merging areas and address the accuracy error of traffic flow prediction models, a cooperative control strategy based on adaptive prediction horizon Model Predictive Control (MPC) has been proposed for variable speed limits (VSL) and dynamic hard shoulder running (HSR). Firstly, the METANET model was improved based on the characteristics of merging areas and the impact of cooperative control strategy. Secondly, to mitigate the negative impact of the METANET prediction errors on control effectiveness, a fuzzy rule-based adaptive prediction horizon controller is designed. Thirdly, a cooperative control strategy for VSL and dynamic HSR is formulated under the MPC framework, aiming to optimize Total Time Spent(TTS)and Total Travel Distance (TTD), using genetic algorithms equipped with sliding time windows for resolution. Finally, using actual traffic flow data from Changtai Highway, simulation experiments are conducted, involving four scenarios: HSR-VSL control, VSL-only control, HSR-only control, and no control. In the cooperative control scenario, both adaptive and fixed prediction horizon approaches are considered. Results show that the proposed HSR-VSL control strategy with fixed prediction horizon reduces the total travel time and mainline density by 20.02% and 10.78% respectively, outperforming single strategies (only HSR or VSL). Compared to a fixed prediction horizon, the VSL-HSR with adaptive prediction horizon delivers even better results, reducing total travel time and mainline density by 24.53% and 12.94% respectively, proving the effectiveness of the cooperative control strategy and the adaptive prediction horizon controller.</div></div>

This study develops a modified integrated guidance and control (IGC) design for the orbit injection phase of a launch vehicle. Firstly, a coupled full-stage position and attitude dynamic model of a launch vehicle is firstly formulated. Secondly, dynamic surface control (DSC) technique is introduced, based on the nonlinear IGC scheme, to achieve the orbit injection mission, with saturation issues in view of the thrust magnitude and swing constraints of the main engines being considered. Besides, the control scheme utilizes a finite-time extended state observer (ESO) to handle various uncertainties in the system. Furthermore, the stability analysis of the closed-loop system is given by using the Lyapunov theory. Finally, numerical simulation is set to verify the proposed IGC method has satisfactory control accuracy and robust performance for the orbit-injection control under various uncertainties.KeywordsLaunch vehicleOrbit injectionIntegrated guidance and controlFinite-time extended state observer design

Compared with the traditional gimbal seeker, the coupling of guidance loop and control loop is more easily caused by the strapdown seeker, so the field-of-view (FOV) limit of the strapdown seeker is more easily violated. To solve this problem, an integrated guidance and control method considering the seeker’s FOV constraints and input constraints is proposed. Firstly, the line-of-sight (LOS) decoupling principle of strapdown seeker was performed on the traditional integrated guidance and control (IGC) model to deal with the problem of FOV constraint, and then the actuator saturation was employed to build a nonlinear strict feedback state equation with unmatched uncertainties. Secondly, the dynamic surface control (DSC) based IGC law considering body line-of-sight angle (BOLS) and input constraints was designed with the extended state observer (ESO) to estimate and compensate the uncertainties. To deal with the FOV and input constraints, the barrier Lyapunov function and Nussbaum function were employed, respectively. Finally, The stability of the closed loop system was proved by using Lyapunov stability theory and numerical simulation verified the effectiveness of the proposed method.

Distributed cooperative controller design considering guidance loop and impact angle

In this paper, the problem of cooperative control of robotic sensor networks (RSNs) for monitoring dynamic pollutant plumes in two‐dimensional (2D) space is studied. The pollutant plume propagation dynamics is governed by a 2D advection‐diffusion partial differential equation (PDE), and the plume front is modelled by a level set with a pre‐specified threshold value. Distributed consensus Luenberger‐type PDE observers are first constructed using local concentration measurements from the RSNs for unanimous estimate of the dynamic concentration field over the entire spatial domain. With the aid of the distributed consensus observers, a leaderless cooperative control scheme is then developed for the RSNs to monitor the dynamic plume front expansion. It is proved using the Lyapunov stability method and set stability concept that the proposed cooperative control scheme guarantees tracking of the dynamic plume front expansion and coverage of the plume front. Extensive numerical simulation results demonstrate the effectiveness and merit of the proposed cooperative control scheme.