Multi-objective Control Method Research Articles

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables. The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets. For this purpose, a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities. Then, an asynchronous fuzzy sampled-data controller, featuring distinct premise variables from the active suspension system, is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership. Furthermore, novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous H2 and H∞ performance requirements. Finally, the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Performance Enhancement of Single-Phase Two-Stage AC-DC Converter With Reduced DC-Link Capacitance

Single-phase two-stage AC-DC converters employed in electric vehicle (EV) chargers have the tendency to produce low frequency ripple due to input/ output power mismatch, making it necessary to use bulky DC-link capacitors. High voltage ripple at DC-link due to reduced capacitance, prompts poor input power quality and high low-line frequency ripple at the output of secondary-stage. In state-of-art, input power quality in converters with low DC-link capacitance is enhanced by using a digital low-pass filter (LPF). However, employing LPF to sensed DC-link voltage results in a non-optimum dynamic response and deteriorated stability margins. With the objective to improve input power quality, enhance dynamic performance and reduce secondary-side ripple for low valued DC-link capacitance AC-DC converters, a modified unit-template based model predictive (MUT-MPC) and a DC-link feedforward (DFF) controls are presented in this paper. The current feed-forward for the unit-template is controlled by predictive voltage error through an optimization process of cost function to improve input power quality and dynamic performance for primary AC-DC converter. Furthermore, a DC-link feedforward (DFF) control is implemented for secondary DC-DC stage, which reduces the low-frequency current ripple at the load. Finally, to verify the effectiveness of presented multi-objective control method in comparison with traditional controls, MATLAB simulations and experimental results are provided.

Mu-Synthesis PID Control of Full-Car With Parallel Active Link Suspension Under Variable Payload

This article presents a combined <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> -synthesis PID control scheme, employing a frequency separation paradigm, for a recently proposed novel active suspension, the Parallel Active Link Suspension (PALS). The developed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> -synthesis control scheme is superior to the conventional <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> control, previously designed for the PALS, in terms of ride comfort and road holding (higher frequency dynamics), with important realistic uncertainties, such as in vehicle payload, taken into account. The developed PID control method is applied to guarantee good chassis attitude control capabilities and minimization of pitch and roll motions (low frequency dynamics). A multi-objective control method, which merges the aforementioned PID and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> -synthesis-based controls is further introduced to achieve simultaneously the low frequency mitigation of attitude motions and the high frequency vibration suppression of the vehicle. A seven-degree-of-freedom Sport Utility Vehicle (SUV) full car model with PALS, is employed in this work to test the synthesized controller by nonlinear simulations with different ISO-defined road events and variable vehicle payload. The results demonstrate the control scheme's significant robustness and performance, as compared to the conventional passive suspension as well as the actively controlled PALS by conventional <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> control, achieved for a wide range of vehicle payload considered in the investigation.

Multi-objective model predictive control method for T-type three-level grid-connected

Based on the mathematical model of T-type three-level topology, a T-type three-level inverter model is proposed to predict the multi-objective control method, which mainly includes DC neutral voltage (NP-V), switching state, inverter voltage vector, and multi-objective cost function. Different emphases can be selected according to the application requirements, and coordinated control of different control objectives can be realized by giving different weight values to different control objectives. An extended observer (ESO) is added to observe the error part of the grid-connected inverter system, and the observed results are compensated to the grid-connected reference voltage. The simulation results show that the total harmonic distortion rate of the output current of the inverter is lower than that of the traditional finite control set model predictive control strategy. In addition, the proposed method can realize the balance control of the midpoint potential, and the principle is simple.

Multiobjective Model Predictive Current Control Method of Permanent Magnet Synchronous Traction Motors With Multiple Current Bounds in Railway Application

For multiobjective model predictive current control (MPCC) method with penalties, the penalty weights are introduced into the cost function to determine the relative importance of control targets. However, the dimensions and value ranges of each control target are different. Thus, the penalty coefficient is difficult to determine. To avoid the difficulty of dimensionless parameter design, this article proposes a multiobjective control method called MPCC with multiple current bounds. In this article, the switching frequency and the common-mode voltage (CMV) are selected as the control target. Their control is converted into the limitation of the current ripple so that the control parameters have a clear physical meaning. On the one hand, the proposed method can realize the cooperative control of reference current tracking, switching frequency suppression, and CMV suppression. On the other hand, the key control parameters have the same dimension and strong correlation with others. Therefore, appropriate parameter design can be realized. Experimental investigations for permanent magnet synchronous motor prove the effectiveness of the control method.

Fruit fly optimization algorithm multi-objective control method for MMC traction power supply system with unbalanced distribution network

Fruit fly optimization algorithm multi-objective control method for MMC traction power supply system with unbalanced distribution network

Multi-Objective Comprehensive Control of Trajectory Tracking for Four-In-Wheel-Motor Drive Electric Vehicle With Differential Steering

For 4MIDEV with differential steering, the trajectory tracking multi-objective control method is studied. The dynamics model of the four-in-wheel motor independent-drive vehicle (4MIDEV) is established comprehensively considering the differential steering dynamics characteristics, longitudinal dynamics characteristics, and lateral dynamics characteristics. Takagi Sugeno (T-S) fuzzy method is adopted to deal with the nonlinear and time-varying characteristics of the model parameters such as vehicle longitudinal speed and the front steering wheel angle. The trajectory tracking control targets are divided into the kinematic control target considering the trajectory tracking accuracy and the dynamics control target considering longitudinal speed tracking as well as lateral stability performance. The generalized $H_{2}$ norm and $H_{\infty }$ norm are selected to constrain the kinematic control target and the dynamics control target respectively. The generalized $H_{2}/H_{\infty }$ trajectory tracking controller is designed to improve the trajectory tracking accuracy and longitudinal speed tracking as well as lateral stability performance. The hardware in the loop test (HIL) verified that the designed trajectory tracking multi-objective controller can improve the comprehensive performance of vehicle and balance the trajectory tracking accuracy between the longitudinal and lateral dynamics performance.

A Multi-Objective Control Strategy for Three Phase Grid-Connected Inverter During Unbalanced Voltage Sag

This paper presents a new multi-objective control strategy for inverter-interfaced distributed generation (IIDG) to ensure its safe and continuous operation under unbalanced voltage sags. The proposed control strategy can effectively improve the low voltage ride through (LVRT) capability, reduce active power oscillations, and limit overcurrent simultaneously, which are marked as the most important control objectives of IIDG during unbalanced voltage sags. The advanced voltage support scheme, which utilizes positive sequence component, is firstly proposed to maximize the LVRT capability of IIDG during unbalanced voltage sags. Then, to ensure the safety of IIDG, the active power oscillation suppression and current limitation algorithm are designed individually. Based on the control algorithms of such objectives, the multi-objective control method, including scenario classification and reference current determination, is then presented to achieve such three objectives under various system conditions simultaneously. Finally, case studies and evaluations based on MATLAB/Simulink are carried out to illustrate the effectiveness of the proposed method.

Robust multiobjective control method for power sharing among distributed energy resources in islanded microgrids with unbalanced and nonlinear loads

This paper proposes a robust control method for power sharing among dispatchable electronically-coupled distributed energy resources (DERs) in an autonomous microgrid. The DER units operate in parallel to meet the total aggregated load demand. The aggregated load is assumed to be uncertain, unbalanced and/or nonlinear, thus it is considered as a source of unmodeled dynamics. The main objective of this paper is to design an H∞ robust controller to enable tracking reference commands of the voltages at the output of the DERs in the presence of unmodeled dynamics. In addition, the H∞ control design problem is combined with other control methods, such as constrained optimal control and regional pole placement, to achieve an optimal control objective, and to improve transient response. The optimal controller is achieved by minimizing an upper bound on H2 performance. The regional pole placement is achieved by defining a linear matrix inequalities (LMI) region. This multiobjective H2/H∞ problem, combined with regional pole placement are expressed as a set of LMIs, and solved by using standard convex optimization algorithms. To show the effectiveness of the proposed method in maintaining the desired voltage at the DER outputs, in presence of unbalanced and nonlinear loads, simulation results are provided for a single DER unit, and the performance of the proposed control strategy is compared with three different controller strategies. Power sharing among multi DER units in autonomous networks is then demonstrated through digital time-domain simulation studies using MATLAB/SimPowerSystems Toolbox.

Multi-objective optimization design and control of deviation-correction trajectory with undetermined target

In the horizontal drilling process, when the actual trajectory deviates from the planned trajectory, it is necessary to take corrective action. The target point is difficult to determine explicitly; however, it is assumed to be in a certain interval of the planned trajectory. This paper presents a mathematical formulation for deviation-correction trajectory design in the case of an undetermined target point, and an optimum design model is established that considers two cases of planned trajectory. The criteria to evaluate the deviation-correction trajectory are summarized as the total trajectory length, the coincidence rate and the well profile energy. The optimum trajectory based on multi-objective optimization is discussed in terms of comprehensive criteria and different weight factors, and a novel heuristic algorithm to solve the established optimization model is presented. The results demonstrate that the maximum value of curvature results in a trajectory with a minimum total length and maximum coincidence rate yet a maximum well profile energy, whereas the maximum horizontal displacement leads to a trajectory with minimum well profile energy. Additionally, the multi-objective optimization model can guarantee a smaller trajectory length, high coincidence rate and low well profile energy. Finally, the multi-objective control method is proposed to obtain an optimization trajectory in different situations.

Multi-objective control for active vehicle suspension with wheelbase preview

This paper presents a multi-objective control method with wheelbase preview for active vehicle suspension. A four-degree-of-freedom half-car model with active suspension is considered in this study. H∞ norm and generalized H2 norm are used to improve ride quality and ensure that hard constraints are satisfied. Disturbances at the front wheel are obtained as preview information for the rear wheel. Static output-feedback is utilized in designing controllers, the solution is derived by iterative linear matrix inequality (ILMI) and cone complementarity linearization (CCL) algorithms. Simulation results confirm that multi-objective control with wheelbase preview achieves a significant improvement of ride quality (a maximum 27 percent and 60 percent improvement on vertical and angular acceleration, respectively) comparing with that of control without preview, while suspension deflections, tyre deflections and actuator forces remaining within given bounds. The extent of the improvement on the ride quality for different amount of preview information used is also illustrated.

Velocity-dependent multi-objective control of vehicle suspension with preview measurements

This paper presents a velocity-dependent multi-objective control method to solve the problem of preview control with velocity uncertainty. A half-car model is considered, the Padé approach is used to approximate the preview delay so as to rewrite it in a finite-dimensional description. It is assumed that the forward velocity of the vehicle resides in an interval and can be measured in real time. The controller, whose gain matrix depends on the information of the velocity, is designed by utilizing the polynomial parameter-dependent idea. The design procedure is developed based on homogeneous polynomial parameter-dependent matrices with arbitrary degree, with quadratic and linear parameter-dependent frameworks as special cases of this method. As the degree increases, the proposed controller can yield less conservative result. A linear parameter-dependent (LPV) controller has also been proposed for the system under time-varying velocity. Simulation results illustrate the usefulness and the advantages of the proposed methods.

Multi-Objective Control Method in Structural Displacement Interval Reliability Based on Epsilon Algorithm

In this article, a kind of structural displacement controlled reliability method was presented. The interval extension of multi-objective control algorithm was applied to control the structural displacement reliability. The method has realized the goal of controlling the multiple static interval reliability indexes by the control of the structural interval parameters. In order to accelerate the speed of the structural reanalysis, the Epsilon algorithm was used in the process of the structural reanalysis when a wide range of modification happened in the interval parameters. This method can both get a satisfactory accuracy, and improve the speed of the reanalysis. Numerical examples show that the method is effective and feasible.

Multi-Objective Control Method in Structural Strain Interval Reliability Based on Epsilon Algorithm

In this article, a kind of structural strain controlled reliability method was presented. The interval extension of multi-objective control algorithm was applied to control the structural strain reliability. The method has realized the goal of controlling the multiple static interval reliability indexes by the control of the structural interval parameters. In order to accelerate the speed of the structural reanalysis, the Epsilon algorithm was used in the process of the structural reanalysis when a wide range of modification happened in the interval parameters. This method can both get a satisfactory accuracy, and improve the speed of the reanalysis. Numerical examples show that the method is effective and feasible.

Multi-Objective Control Method in Structural Stress Interval Reliability Based on Epsilon Algorithm

A kind of structural stress reliability control method was presented. In this article, the interval extension of multi-objective control algorithm was applied to control the structural stress reliability. By the control of the structural interval parameters, this method has realized the goal of controlling the multiple static interval reliability indexes. To insure the accuracy of the structural reanalysis, the Epsilon algorithm was used in the process of the structural reanalysis when a wide range of modification happened in the interval parameters. This method can both get a satisfactory accuracy, and improve the speed of the reanalysis. The results of the example further proved that the proposed method can be effectively applied in the multi-objective control of the structural stress interval reliability.

Multi-Objective Optimization Model for Urban Traffic Intersection Control Based on Data Fusion

A new multi-objective optimization control strategy for urban intersection is proposed, which takes the degree of smooth and the degree of equilibrium as objectives. The new method is not limited to the traditional basic traffic parameters, such as delay and queue length.etc, but Applying data fusion technology, by multiple integrating on the basic traffic parameters, the real-time multi-objective values are achieved. The degree of the smooth quantitatively denotes the forced travel time extension because of traffic signal control, saturated traffic flow.ect. The degree of equilibrium denotes the equilibrium degree of traffic flow in space. Illustrating an intersection in Beijing, a simulation model in Paramics is built. The simulation results show that the proposed multi-objective control methods can not only reduce the traffic flow delay, but also makes traffic flow distributing equilibrium in each phase of intersection. This approach is consistent with Chinese saturated traffic flow characteristics.

MORA routing and capacity building in disruption-tolerant networks

Disruption-tolerant networks (DTNs) differ from other types of networks in that capacity is created by the movements of network participants. This implies that understanding and influencing the participants’ motions can have a significant impact on network performance. In this paper, we introduce the routing protocol MORA, which learns structure in the movement patterns of network participants and uses it to enable informed message passing. We also propose the introduction of autonomous agents as additional participants in DTNs. These agents adapt their movements in response to variations in network capacity and demand. We use multi-objective control methods from robotics to generate motions capable of optimizing multiple network performance metrics simultaneously. We present experimental evidence that these strategies, individually and in conjunction, result in significant performance improvements in DTNs.