Upper-level Control Research Articles

СИНЕРГЕТИЧЕСКИЙ СИНТЕЗ НАБЛЮДАТЕЛЯ ВОЗМУЩЕНИЙ ДЛЯ СИСТЕМЫ УПРАВЛЕНИЯ «ЛЕТАЮЩЕЙ ПЛАТФОРМОЙ»

The work is devoted to the synergetic synthesis of the harmonic disturbance asymptotic observerfor the aircraft hierarchical control system. The paper contains the general description of “flying platform”type vertical take-off & landing aircraft & an asymptotic observer of external disturbing influences(for example, wind) that have a harmonic dynamics & cause periodic changes in flight height, aswell as in pitch & roll angles. An asymptotic observer must ensure the asymptotic stability of a reservedsystem, the implementation of technological invariants, the estimation of unobservable external influencesfrom the current values of the observed state-space variables, & the absorption of harmonic winddisturbances. The article also presents an extended mathematical model of the “flying platform” in thevertical movement mode under external harmonic disturbing influences, including a mathematical descriptionof the disturbance dynamics, & the upper hierarchy level control algorithms based on thegiven technological invariants are synthesized. In addition, the equations of the disturbing influencesasymptotic observer are calculated, which supplement the mathematical model of the “flying platform”under disturbed motion, & the equations for asymptotic estimates of unobserved variables are calculated,which are further included in the upper hierarchy level control laws. The possibility of the disturbanceobserver synthesis was verified using the observability criterion. Finally, the results of computersimulation of the upper & the lower hierarchy levels’ nonlinear dynamics under disturbed motion withsuppression of external disturbances by an asymptotic observer are shown, as well as the results ofcomputer simulation of the vehicle’s nonlinear dynamics under disturbed motion without an asymptoticobserver to allow a visual assessment of the observer’s performance by comparison. The relevance ofthe work consists in the necessity of “flying platform” type vertical take-off & landing aircraft creationto increase the effectiveness of people rescue operations in those disaster areas where helicopters &other modern means don’t cope with a task. The scientific novelty of the work consists in synergeticapproach application to the design of the vehicle’s spatial position system equipped with an asymptoticobserver to suppress disturbing influences.

Adaptive Sliding Mode-Based Lateral Stability Control of Steer-by-Wire Vehicles With Experimental Validations

In this paper, a robust adaptive sliding mode (ASM) controller for improving vehicle maneuverability and lateral stability of steer-by-wire (SBW) vehicles. The proposed stability control algorithm is composed of the following three remarkable characteristics: 1) As the vehicle sideslip angle which is very useful in vehicle stability control is often unavailable or unmeasurable for practical applications, a sliding mode-based state observer is proposed to online estimate the actual sideslip angle via the yaw rate and the lateral acceleration measurements. 2) ASM lateral stability controller, as an upper level controller, is designed to calculate the corrected steering angle for driving both the yaw rate and the sideslip angle to achieve their desired values in the presence of modelling uncertainties and external disturbances. Moreover, an adaptive law is incorporated in the control law to estimate the switching gain such that the complex uncertainty bound information can be avoided. 3) The desired steering angle is realized by a lower steering controller via ASM for an SBW system. The hardware-in-the-loop simulation results demonstrate the excellent stability control performance of the proposed control for different steering maneuvers.

Yaw rate tracking-based path-following control for four-wheel independent driving and four-wheel independent steering autonomous vehicles considering the coordination with dynamics stability

The path-following problem for four-wheel independent driving and four-wheel independent steering electric autonomous vehicles is investigated in this paper. Owing to the over-actuated characters of four-wheel independent driving and four-wheel independent steering autonomous vehicles, a novel yaw rate tracking-based path-following controller is proposed. First, according to the kinematic relationships between vehicle and the reference path, the yaw rate generator is designed by linear matrix inequality theory, with the ability to minimize the disturbances caused by vehicle side slip and varying curvature of path. Considering that the path-following objective and dynamics stability are in conflict with each other in some extreme path-following conditions, a coordinating mechanism based on yaw rate prediction is proposed to satisfy the two conflicting objectives. Then, according to the desired yaw rate and longitudinal velocity, a hierarchical structure is introduced for motion control. The upper-level controller calculates the generalized tracking forces while the allocation layer optimally distributes the generalized forces to tires considering tire vertical load and adhesive utilization. Finally, simulation results indicate that the proposed method can achieve excellent path-following performances in different driving conditions, while both path-following objective and dynamics stability can be satisfied.

Data Analysis of MYO Signals during Upper Limb Movements of Enhanced Exoskeleton

Equipped with enhanced exoskeleton in the individual combat system can effectively enhance the soldiers’long-term load-bearing capacity and enhance the combat effectiveness of the army. In the exoskeleton control system, accurate recognition of human movement intentions plays an important role as upper-level control. This paper uses MYO armband as a sEMG sensor to collect 8 channels sEMG signals. Neural network method is applied to estimate the joint angles during arm movement. Motion capture system is used to verify the estimation accuracy. PCA (Principle Component Analysis) method is performed on the 8 channels data collected by MYO and processed dimensions were selected by experiments to make the estimation accuracy the highest. The results show that when the principal component dimension is selected as 8, which makes the estimation accuracy of the joint angles the highest.

Hierarchical predictive energy management of hybrid electric buses based on driver information

To improve the energy efficiency of hybrid electric city buses, a hierarchical predictive energy management strategy (HP-EMS) based on driver behavior and type is proposed in this paper. Within the model predictive control (MPC) framework, the k-Nearest Neighbor (kNN) method is applied to identify the driver type, and the deep neural network (DNN) is adopted to predict future speed based on the historical speed, driver type, and driver behavior. Combined with the city bus driving characteristics, the hierarchical strategy aims to reduce the frequent starts of the engine. The upper-level controller implements a rule-based strategy to limit the engine start-stop frequency. The lower-level controller uses dynamic programming (DP) to search for the best control strategy in the prediction horizon. Simulation results show that, compared with speed prediction without driver information, the new method can effectively improve the accuracy of future speed prediction, and RMSE between the prediction and measurement drops from 1.58 m/s to 1.45 m/s. The HP-EMS without driver information can reduce the number of engine starts by 30% while increase only 2% energy consumption compared with predictive energy management without hierarchical control. The paper also studies the benefits of considering driver behavior and type. The same HP-EMS controller is implemented with and without driver behavior and type. The one with the additional information reduces the energy consumption by 3.34% compared to the one without the information.

Robust Cooperative Control of Multiple Autonomous Vehicles for Platoon Formation Considering Parameter Uncertainties

This paper proposes a robust cooperative control strategy for multiple autonomous vehicles to achieve safe and efficient platoon formation, and it analyzes the effects of vehicle stability boundaries and parameter uncertainties. The cooperative vehicle control framework is composed of the upper planning level and lower tracking control level. In the planning level, the trajectory of each vehicle is generated by using the multi-objective flocking algorithm to form the platoon. The parameters of the flocking algorithm are optimized to prevent the vehicle speed and yaw rate from going beyond their limits. In the lower level, to realize the stable platoon formation, a lumped disturbance observer is designed to gain the stable-state reference, and a distributed robust model predictive controller is proposed to achieve the offset-free trajectory tracking while downsizing the effects of parameter uncertainties. The simulation results show the proposed cooperative control strategy can achieve safe and efficient platoon formation.

A new control approach for automated drifting in consideration of the driving characteristics of an expert human driver

This paper presents a new control approach for automated drifting in consideration of how expert drivers conduct drifting. The expert drivers stabilize their vehicles at high sideslip angle using not prior knowledge of tire dynamics and equilibrium but current vehicle states. By mimicking how these expert drivers control their vehicles at high sideslip angle, the proposed controller is able to control the vehicle at high sideslip angle using only current vehicle states, i.e without prior knowledge of tire and drift equilibria. Specifically, the proposed controller can perform steady state drifting without the knowledge of the equilibrium of the vehicle system. The proposed controller consists of three consecutive parts. First, the supervisor determines the desired yaw rate and rear longitudinal slip ratio. Second, the upper-level controller calculates the desired front lateral force and rear longitudinal force to track the desired motions. Third, the lower-level controller converts the upper-level controller’s desired forces into steering wheel angle and gas pedal input, which are actual control inputs of vehicles. The proposed algorithm has been investigated via vehicle tests. A rear wheel driven mid-sized vehicle with limited slip differential and internal combustion engine was utilized for testbed. The test results indicate that the proposed algorithm can successfully conduct automated drift maneuvers. Furthermore, the stability of the closed-loop drift control system has been proved by using Lyapunov stability analysis and estimating Region of Attraction (RoA). The vehicle test results are superimposed on the estimate of RoA, and it has been shown that vehicle states within the estimate of RoA converge well to the desired motions. In addition, the comparison of the proposed algorithm with the previously developed drifting control algorithm was conducted. In contrast to the drifting control algorithm that was based on drift equilibrium, the proposed control algorithm is capable of conducting drift maneuvers on both high friction roads and low friction roads without prior knowledge of the tire model and road friction coefficient.

Vertical hierarchical MPC for constrained linear systems

A hierarchical Model Predictive Control (MPC) formulation is presented for discrete-time linear systems with state and input constraints. A vertical hierarchical controller, with one controller per level, reduces the computational burden associated with the solution of centralized MPC having long prediction horizons and short time steps. To guarantee satisfaction of state and input constraints in the presence of both known and unknown disturbances, a robust MPC formulation is used at each level while waysets are used as a novel coordination mechanism between controllers at different levels. These waysets are implemented as terminal state constraints on lower-level controllers and are computed on-line based on the optimal state trajectory of upper-level controllers. To achieve the computational efficiency necessary for on-line calculation, waysets are represented as constrained zonotopes. State and input constraint satisfaction is proven for a hierarchical controller with an arbitrary number of levels and two numerical examples demonstrate the key features, performance, and scalability of the approach.

Heavy-duty vehicle longitudinal automation with hydraulic retarder via H infinity control and off-policy reinforcement learning

A novel hierarchical heavy-duty vehicle (HDV) longitudinal control strategy with a hydraulic retarder is proposed in this paper to achieve the HDV down-hill longitudinal automation in the deceleration process. The upper level controller generates the optimal desired retarder torque through the H infinity control and the off-policy reinforcement learning (RL), in which the H infinity control is able to attenuate those disturbances and the off-policy RL can solve the H infinity control with completely unknown system dynamics. Then, according to the optimal desired retarder torque, the lower level controller can calculate the desired control pressure for the retarder to control the HDV. The effectiveness of this HDV longitudinal control strategy is verified by simulations based on an experimentally verified retarder model. Compared to the sliding-mode-control (SMC) based controller, the simulation result shows the proposed control strategy has better capability to attenuate the disturbances and guarantee the longitudinal speed tracking performance.

Coordinated Chassis Control of 4WD Vehicles Utilizing Differential Braking, Traction Distribution and Active Front Steering

This paper proposes a coordinated chassis control (CCC) utilizing four-wheel differential braking, electronically controlled real-time four-wheel drive (4WD) and active front steering (AFS), aiming to improve the driving performance and handling stability during cornering. First, the performance of the single system is tested; then the hierarchical-structure control algorithm is designed: a supervisory controller to monitor vehicle states and determine the desired yaw rate, upper-level controller to decide the desired longitudinal forces and the desired yaw moment based on the driver intention and the consideration of vehicle stability, and the control allocation layer to distribute the actual control inputs to the actuators applying an optimal control allocation algorithm. Simulations of moderate driving/aggressive deceleration scenarios and a comprehensive test on a handling road are conducted to validate the effectiveness of the proposed control algorithm. The results of the simulations suggest that the proposed algorithm can effectively improve the driving speed in limit cornering without losing lateral stability, and reduce the tire dissipation energy compared with other control algorithms such as the electronic stability control system, the four wheel independent brake system and an integrated chassis control system proposed in a previous research.

Feeding control of anaerobic co-digestion of waste activated sludge and corn silage performed by rule-based PID control with ADM1

Anaerobic co-digestion (AcoD) of corn silage (CS) and waste activated sludge (WAS) co-substrates, compared with anaerobic digestion (AD) of mono-substrate WAS, was simulated under mesophilic conditions with the adapted IWA Anaerobic Digestion Model No. 1 (ADM1), and a rule-based PID control system for control of the AcoD of CS and WAS, through control of their ratios in the feed, was developed, implemented with the model as a test platform. Tests on AcoD of co-substrates were conducted at the COD mass-based feeding ratios of CS to WAS 1:2.5, 1:2.0 and 1:1.2. The maximal biogas production was 0.94 m3/kgVS·d at the feeding ratio 1:1.2. The ADM1 was adapted, and the high-sensitivity kinetic parameters were calibrated and optimised using the data from the tests of steady state mono-digestion of WAS and AcoD of CS and WAS. The simulated data of biogas and methane production, methane content, VFA and pH agreed well with the test data. The rule-based PID control was developed with an additional expert system, in which the lower level controller operated the level of VFA/TIC and the upper level controller manipulated the setpoints of methane production. The feeding ratio of CS to WAS was used as a manipulated variable. With the constraint boundaries, the test on the control system showed that it could keep methane production stable to the setpoint and maximise methane production while resisting the disturbances to AcoD by adjusting the feeding ratios of CS to WAS.

Integrated Longitudinal and Lateral Control System Design and Case Study on an Electric Vehicle

This paper presents the design of an integrated longitudinal and lateral controller for autonomous vehicle and field tests with an electric vehicle. First, the longitudinal design was studied which includes the spacing policy as the upper level controller and throttle and brake control as the lower level controller. A safety spacing policy was proposed considering both the vehicle states and the vehicle capability. A coordinated throttle and brake controller was also designed to ensure the vehicle pursuing the desired acceleration. Second, a multimodel lateral controller was proposed which can perform the lane tracking and lane changing manoeuvres. Then, an integrated control structure was proposed to manage both the longitudinal and lateral controller. Finally, simulation and visualization works were carried out to validate the proposed solutions. An electric vehicle experiment platform was also built, and field tests showed encouraging results.

Cost-Function-Based Microgrid Decentralized Control of Unbalance and Harmonics for Simultaneous Bus Voltage Compensation and Current Sharing

Power quality of inverter-based microgrids is a challenging issue due to nonlinearities of inverters, multiple resonance modes of network impedance, and unbalanced and nonlinear loading condition. The ideal solution is to assure the best power quality at the common bus to which loads are connected, and share the negative and harmonic sequence currents between the inverters without any communication. However, it is difficult to achieve this objective with existing virtual-impedance-based methods when nonlinearities of inverters, e.g., dead time, are not negligible. In this paper, a novel cost-function-based method is proposed to solve this problem. The proposed cost functions are optimized using continuous-control-set model predictive control. As unknown nonlinearities of inverters can be observed by introducing disturbance models, even when they are not negligible, the presented method can compensate bus voltage unbalance and harmonics and share the compensated current between inverters autonomously, with neither communication nor upper level controller. Parameter tuning of the proposed method is the key to achieve the balance between bus voltage quality and current sharing, and between stability and fast response. Experimental results demonstrate that the proposed control scheme is effective even under conditions of large inverter nonlinearities.

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

This paper proposes an electronic stability control and shows MIL and HIL simulations performed for evaluation. Two designs are presented, one based on two-degrees-of-freedom linear model that includes side-slip and yaw motion and other based on three-degrees-of-freedom linear model that includes roll motion. Model-in-the-loop and Hardware-in-the-loop simulations were performed to test ESC on vehicle represented by a nonlinear model that considers lateral, yaw and roll motions and an intelligent driver model to generate the steering wheel command as driver reaction to vehicle motion in respect with desired path. It’s found from simulations for double lane change maneuver that the proposed controller is effective in reducing of side-slipping, rolling and yaw rate errors, keeping the steering stable in scenarios where the driver loses control of the vehicle, even in presence of disturbances in vehicle response in relation with response predicted by linear model used for control design.

Distributed Optimal Control for Multiple Microgrids in a Distribution Network

The ever-increasing demand for more reliable and flexible energy supply for customers has pushed up the microgrids (MGs) to the center stage in the developments of distribution networks. If managed and coordinated efficiently, MGs can provide distinct benefits to the suppliers as well as energy consumers. In this paper, a distributed optimal control framework is proposed to coordinate the multiple MGs in a distribution network as well as to achieve the optimal control within the MGs. For each MG, a two-level control methodology is adopted. The upper-level control optimizes the generation output of multiple MGs cooperatively in a distributed manner, while the lower-level control tracks the optimal generation setting of each generator in the MG under both the grid-connected and islanded modes. The proposed control facilitates the autonomous operation of MGs in the distribution network while still achieves the optimal operation. Simulation studies with a four-MG system demonstrate the effectiveness of the proposed distributed approach.

Distributed Discrete Robust Secondary Cooperative Control for Islanded Microgrids

It is desirable to develop robust controllers for fast frequency/voltage regulation and active/reactive power sharing in an islanded microgrid with high penetration level of renewable energy sources. This paper proposes a fully distributed discrete two-level control strategy for islanded microgrids. The upper-level control determines the active/reactive power generation references to minimize the overall voltage deviations while achieving accurate active/reactive power sharing. The lower-level control enables the inverter to track the power references by adjusting inverter output voltage magnitude and angle. A flexible finite-step convergence tracking controller, which considers the uncertainties and disturbances, is introduced to improve the robustness and control accuracy. The convergence and optimality of the proposed discrete control algorithm are validated by rigorous analysis. The effectiveness of the proposed distributed control approach is verified by simulation results.

Mode control of electro-mechanical suspension systems for vehicle height, levelling and ride comfort

This paper proposes a mode control algorithm of electro-mechanical suspension for vehicle height, attitude control and improvement of ride quality. The proposed control algorithm consists of mode selector, upper-level and lower-level controllers, and suspension state estimator. The mode selector determines the present driving mode using vehicle signals, such as longitudinal speed, steering wheel angle, accelerator pedal position, brake pedal position and vertical acceleration of wheels. The upper-level controller determines the desired suspension state using the present driving mode. The lower-level controller derives the desired stroke speed of the actuator in each suspension by linear quadratic control theory. The suspension state estimator has been designed using accessible sensor measurement by discrete-time Kalman filter theory. The control and estimation algorithms have been developed based on a novel reduced-order vehicle model that includes only the vehicle body dynamics. The model enables the observer to completely remove the effect of unknown road disturbance on the estimation error. The performance of the proposed control algorithm has been evaluated via computer simulation study. The simulation results show that the proposed control algorithm is effective at controlling the electro-mechanical suspension systems. The paper also shows that the considered actuator is suited for vehicle height and levelling control, but not for improvement of ride comfort, due to voltage input constraints.

Optimization of control allocation with ESC, AFS, ARS and TVD in integrated chassis control

This paper presents an optimization of control allocation in integrated chassis control with active front steering, active rear steering, electronic stability control and torque-vectoring device under the saturation of lateral tire forces on front wheels. After a control yaw moment is calculated in the upper-level controller, a weighted pseudo-inverse based control allocation is used for yaw moment generation in the lower-level controller. Variable coefficients of the weighted pseudo-inverse based control allocation are used to represent various actuator combinations and are optimized for each actuator combination to enhance control performances using simulation on vehicle simulation package, CarSim. Due to severe cornering on low friction road, the front lateral tire forces can be easily saturated. Under the condition, the active front steering has little effect on control performance and, consequently, the desired control yaw moment cannot be generated. So, the lateral force generated by AFS should be restricted to its maximum, and a constrained weighted pseudoinverse based control allocation with electronic stability control, active rear steering and torque-vectoring device is applied to compensate the loss of the control yaw moment. Variable coefficients of the constrained weighted pseudo-inverse based control allocation with electronic stability control, active rear steering and torque-vectoring device are also optimized using simulated-based tuning. To validate the proposed method, simulation was done on CarSim. From simulation, it was verified which actuator combination is effective for integrated chassis control if the lateral forces on front wheels are saturated.

Effects of ACC and CACC vehicles on traffic flow based on an improved variable time headway spacing strategy

An improved variable time headway (VTH) spacing strategy for the adaptive cruise control (ACC) and cooperative ACC (CACC) system is proposed. On the basis of the novel strategy, the typical two-modes of ACC/CACC upper-level controller are redesigned. Numerical simulations for two traffic scenarios are performed to verify the efficiency of the improved strategy. The results demonstrate the suitability and advantages of the improved VTH strategy in comparison with the constant time headway strategy and the VTH strategy. Furthermore, the authors study the impact of ACC and CACC vehicles on traffic flow by multiple-types mixed scenarios: ACC/manual vehicles, CACC/manual vehicles and ACC/CACC/manual vehicles. The results illustrate that introducing the ACC/CACC vehicles into mixed traffic can improve traffic flow stability, enhance road capacity and alleviate the increasingly serious traffic congestion problem.

Oscillatory Yaw Motion Control for Hydraulic Power Steering Articulated Vehicles Considering the Influence of Varying Bulk Modulus

In this investigation, a detailed hydraulic steering system of articulated steer vehicles (ASVs) and a 12-DOF ASV model are developed for vehicle dynamics performance research. The real-time changing characteristic of oil bulk modulus is considered. Field test and multibody dynamics model by Adams/View software are compared with the established mathematical model, respectively, to verify the correctness of the model at low speed and high speed. The snaking and oscillatory area is confirmed to reveal the influence of varying bulk modulus on the stability of ASV. To improve the stability of ASV, the direct yaw moment control system and driving force distribution system are designed with the application of the optimal control theory. The upper level controller calculates the expected yaw moment by feedforward and feedback compensatory strategies. Different from zero-sideslip control in most studies, an Ackermann-based sideslip angle is used for feedforward compensatory gain derivation and reference model design. The lower level controller distributes the driving force for each wheel aiming at the optimal utilization rate of tires. High-speed weave test by sinusoidally steering for loaded ASV is simulated to verify the effectiveness of the control algorithms.