Multi-objective Control Research Articles

A Multiobjective Control Strategy for Harmonic Current Mitigation With Enhanced LVRT Operation of a Grid-Tied PV System Without PLL Under Abnormal Grid Conditions

This article proposes a novel multiobjective control strategy (MOCS) for improving the performance of grid-tied photovoltaic (GTPV) system without phase-locked loop (PLL) operating under abnormal grid voltage conditions such as harmonically distorted voltages, grid faults, and weak grid. The proposed control strategy effectively mitigates the harmonics in grid injected current, eliminates the oscillations in grid injected power, and enhances the low-voltage ride-through (LVRT) capability simultaneously during abnormal grid conditions. The LVRT capability of the GTPV system is enhanced by incorporating an active power regulator (APR) with dynamic reactive power support (DRPS) controller in the proposed control strategy. The proposed MOCS is designed in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha \beta $ </tex-math></inline-formula> stationary reference frame. Furthermore, the proposed MOCS consists of an advanced phase compensated multiresonant (APCMR) current controller and a phase-shifted reference current generator (PSRCG) integrated with the APR with DRPS controller. The APCMR suppresses the grid current harmonics under weak and distorted grid voltages and the PSRCG eliminates active and reactive power oscillations at the grid side caused by grid faults. The synchronization mechanism of the GTPV system is included in the PSRCG, and therefore, the requirement of PLL is avoided. Consequently, the associated computational burden on the digital controller is reduced. The effectiveness of the proposed control strategy is validated using the OPAL-RT digital simulator and offers superior performance compared to the conventional control strategy (COCS).

Lateral Shared Sliding Mode Control for Lane Keeping Assist System in Steer-by-Wire Vehicles: Theory and Experiments

The lane-keeping assistance design for steer-by-wire road vehicles is a multi-objective control problem that addresses lane tracking, improvement of driver comfort and ensuring vehicle stability. The designed architecture must be sensitive to various driver behaviors, provide assistance to drivers whenever required and ensure a smooth transition of authority between manual and automated driving modes. In this work, we propose a novel shared lane-keeping controller-based on quasi-continuous high-order sliding mode control dealing with the above challenges. The parameters of the controller are characterized by an upper bound estimate of the lateral winds force and the road curvature which acts as disturbances. Using the sharing parameter dependent on the monitored driver attribute, the authority is smoothly transitioned between various modes while accounting for driver behaviors. Experimental results on the SHERPA vehicle simulator shows the real-time implementation feasibility. Extensive results and discussions are provided to demonstrate the effectiveness and the applicability of the proposed controller.

Research on modeling and control strategy of lithium battery energy storage system in new energy consumption

Energy storage technology is one of the effective means to promote the consumption of new energy. It has the advantages of improving the flexibility and stability of power grid. Energy storage plays an important role in improving the peaking and valley filling function of the load side of the power grid. Based on the two-stage topology of the energy storage system, this paper establishes the mirror model of the practical application engineering of the energy storage system, and uses the data-driven method to establish the energy storage battery model. On this basis, the multi-objective control strategy is adopted for the peak regulating power of the energy storage system and the load state balance of the battery. The support vector machine algorithm is used to predict the daily load data of the power grid, and the constant power algorithm is proposed to control the battery control node signal. Finally, taking the battery compartment of the energy storage system as the simulation object, the effectiveness of the proposed control strategy is verified, which provides a theoretical basis for the topic research.

A grid‐based searching algorithm for observer‐based multiobjective control of T–S fuzzy stochastic jump‐diffusion systems

Most studies on a multiobjective optimal control problem (MOCP) with nonlinear stochastic jump-diffusion system (NSJDS) constraints assume the state vector is available, but in practice, this is not necessarily the case. The observer-based MOCP is worthy of further research. Furthermore, the hybrid multiobjective differential evolution algorithm (HMODEA) is usually employed to help solve MOCPs with dynamical system constraints, and such problems often have a higher computational burden. To address these two issues, a grid-based front-squeezing searching algorithm (GBFSA) is proposed to solve the observer-based MOCP with NSJDS. Takagi-Sugeno (T-S) fuzzy model is used to approximate the NSJDS and convert the problem into an MOCP with linear matrix inequality (LMI) constraints. Then, the GBFSA efficiently searches for the Pareto front by merging the LMIs and the squeezing theorem. To automatically select a preferred Pareto controller, the minimum Manhattan distance (MMD) approch is applied. Mathematical proofs are given to show that the obtained Pareto optimal controller can concurrently stabilize the associated NSJDS and achieve the desired performance indices. In addition, computational complexity and convergence analysis are also provided.

Performance enhancement of smart grid integration using a novel intellectual multi-objective control technique

Performance enhancement of smart grid integration using a novel intellectual multi-objective control technique

Research on Longitudinal Static Stability Compensation of Aircraft

An aircraft is unstable in longitudinal motion, the variation of aerodynamic derivatives and center-of-gravity position caused by altitude, speed, and fuel have a great impact on the control and stability of the aircraft. By using the Linear Matrix Inequality (LMI) approach, the longitudinal static stability of the aircraft is compensated. In addition, the pitch attitude control system is designed, and multi-objective control, including pole assignment and controlled variable constraints, is achieved during the designing process. As a result, the robustness of the system is also achieved. Finally, the simulation results of the pitch attitude control system show that this design approach is feasible.

Multi-objective control of transient process of hydropower plant with two turbines sharing one penstock under combined operating conditions

This paper studies the multi-objective control of transient process of hydropower plant with two turbines sharing one penstock under combined operating conditions (COCs). Firstly, the model of transient process of hydropower plant is presented. The illustration of four COCs is provided. Then, the multi-objective control strategy of transient process under COCs is designed. The decision variables and objective functions are selected. The control scheme and decision method are determined. Finally, the most favourable superposition time and the most unfavourable superposition time under COCs are determined. The results indicate that the objective function contains three objectives, i.e. spiral case outlet pressures, draft tube inlet pressures and rotational speeds of turbines. The most favourable superposition time under COC-1 can realize that the objectives reach control requirements simultaneously. The most favourable superposition time under COC-2 and the most unfavourable superposition time under COC-1 and COC-2 cannot realize that the objectives reach control requirements simultaneously, but can balance the objectives to the maximum extent. It is unnecessary to distinguish the most favourable superposition time and the most unfavourable superposition time strictly under COC-3. There is no the concepts of the most favourable superposition time and the most unfavourable superposition time under COC-4.

A MIMO–ANFIS-Controlled Solar-Fuel-Cell-Based Switched Capacitor Z-Source Converter for an Off-Board EV Charger

The efficiency of a nation’s progress is determined by a variety of factors; however, transportation plays a critical role in boosting progress because it facilitates trade and communication between countries. The majority of transportation is powered by fossil fuels such as gasoline or diesel, which will be depleted in less than 50 years. Another option is to operate transportation systems after replacing conventional vehicles with electric vehicles (EV). Powering these vehicles with green electricity contributes zero carbon emissions from production to the final product. Together with the controller, an efficient charger ensures that the entire system is reliable and stable. The current work focuses on charging an off-board EV from greener energy sources (both a fuel cell and PV array forming a micro-grid) based on their availability via an efficient converter controlled by an adaptive multi-objective controller. A novel multi-output-based adaptive neuro fuzzy inference system (ANFIS) controller for charging the off-board EV at a constant current and voltage for both line and load regulations is proposed, in the current work. A comparison study of grid partitioning and subtractive clustering was conducted in order to select an optimized algorithm for generating FIS. Novelty is achieved by ensuring closed-loop stability is the main aim of the work. The entire work was created with the MATLAB/Simulink software.

Optimal control of satellite system model using Linear Matrix inequality approach

In this paper, a robust control strategy has been proposed for the satellite attitude control system, namely, ℋ∞ with regional pole constraints. This design method has been applied to eliminate the effects of disturbances and uncertainties, which are inevitable in aerospace applications. A convex optimization approach using Linear Matrix Inequalities (LMIs) has been utilized in this work. The concept of LMI region constraints have been used to guarantee the closed-loop poles lie within a defined region in the complex plane, which helps improve performance in addition to the robustness properties. Therefore, the designed controller can be viewed as a multi-objective controller that guarantees both robustness and performance. Simulation results demonstrate that the developed controller (ℋ∞ with LMI region constraint) performs better than only ℋ∞ and pole placement controllers, in terms of disturbance attenuation, transient response, and control effort.

A novel design for balancing capacitor voltage of multilevel inverter using space vector pulse width modulation (SVPWM)

The multi objective control of modular multilevel converter (MMC) can be achieved by a superior modulation strategy (SVPWM), In this paper, a novel -fangled control technique is employed on the multilevel inverters to attain the balance in the capacitor voltage using the SVPWM strategy. A MLI used for higher-power mid-voltage schemes. The proposed methodology includes the single-phase modulator for which we attain the balance in the voltage of flying capacitors. The efficacy and practicality of the SVPWM are estimated using the simulation models for steady and transient state analysis with given modulating indexes and loads. The efficiency of the proposed model for a pulse with modulation is analyzed using results attained by balancing the voltages of flying capacitors.

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.

ADMM-Based Multi-Objective Control Scheme for Mitigating the Impact of High Penetration DER Integration in the Modern Distribution Systems

The high penetration of renewable energy sources in modern distribution networks poses challenges for grid voltage regulation. In this study, a multi-agent distributed voltage control strategy based on the proximal Jacobian alternating direction method of multipliers (PJ-ADMM) is proposed for distribution power systems with a high penetration of photovoltaic (PV) resources coordinated with battery energy storage systems (BESS). In this context, all active and reactive power outputs of the PV are locally optimized through smart inverters to improve the grid voltage with minimum power loss. Uncertainties associated with the solar energy generation and load demands are considered in the defined scenarios. This study consists of two phases. In the first phase, the voltage control problem is formulated as an optimization problem to regulate the voltages within an acceptable limit with fast convergence. In the second phase, a coordinated voltage control strategy for smart PV inverters and BESS is proposed to allocate the power capacity of the battery energy storage systems and the active power loss reduction. Finally, the proposed method is tested on modified IEEE 13-bus, 33-bus and 141-bus distribution systems using MATLAB/Simulink and MATPOWER. A comparison of the results of the voltage profiles with and without the control algorithm demonstrated the efficacy, robustness, and scalability of the distributed scheme for voltage improvement and optimal utilization of PV power under different scenarios.

Data Driven Model Predictive Control for Modular Multilevel Converters With Reduced Computational Complexity

Model predictive control (MPC) has become increasingly popular among researchers for modular multilevel converters (MMCs) due to its ability to incorporate multiobjective control and provide superior dynamic response. However, it is computationally challenging to implement it on MMCs when the number of submodules is increased. This paper proposes a finite control set (FCS) model predictive control (MPC) with reduced computational complexity for modular multilevel converters (MMCs). To accomplish this goal, a reduced order data-driven model is obtained using sparse identification of nonlinear systems (SINDy) by incorporating the input terms in the load current and circulating current dynamics. As a result, the need to use the arm voltages or the submodule capacitor voltages dynamic equations as in the case of a conventional FCS-MPC is eliminated. To improve the output current total harmonic distortion (THD) and reduce the effect of higher switching frequencies caused by the FCS-MPC, an updated cost function is proposed. The effectiveness of the proposed technique is validated by simulation and experimental results.

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.

Multi-Objective Control Architecture for an Autonomous In-wheel Driven Electric Vehicle

This paper investigates the high-level control of an in-wheel-motor-drive autonomous electric vehicle. Four distinct objectives are achieved, including lateral and longitudinal control, as well as stability and maneuverability control. Actuators designated at the low level are active front steering specified for the lateral control and the 4 independent in-wheel motors for the remnant objectives. Stability and maneuverability are realized using the direct yaw control by distributing driving and braking torques among the motors, along with the longitudinal control within a torque allocation unit. In contrast to critical situations, maneuverability is promoted while relaxing the stability objective during normal driving situations. Hence, a decision layer is developed to coordinate the stabilizing and maneuvering objectives on the same actuator, thus a multi-layer Global Chassis Control (GCC) architecture is established. The control architecture is tested and validated within a MatLab/Simulink environment. Simulation results carried out on a full nonlinear vehicle model emphasize the objectives’ achievement and demonstrate the superior performance of such system.

Control of ILC in an Autonomous AC–DC Hybrid Microgrid With Unbalanced Nonlinear AC Loads

This article presents a multiobjective control scheme for a bidirectional interlinking converter (ILC) of renewable energy based ac–dc hybrid microgrid. The prime focus of the power management algorithm is to feed the ac loads, and dc loads from ac source, and photovoltaic battery energy storage (BES), respectively. The second objective is to utilize the solar power to maximum capacity, by feeding it to dc load, BES, and ac load, in the given order of priority. The ac and dc subgrids operate independently, while supporting each other in case of overloading/underloading, thus reducing the amount of power reserve required in each, and eliminating the need of dump loads. The ANFIS-MN-based power quality control is integrated in order to ensure the total harmonics distortion of ac source current remains below 5% as per IEEE 519 standard, irrespective of the nature of load connected. In addition, the ILC control prevents any negative sequence currents from entering the ac source, even if there is any open circuit fault leading to unbalanced loading on the three phases. The performance of ANFIS-MN-based ILC control is demonstrated to be superior when compared with the conventional and contemporary techniques under different scenarios.

Multi-Objective Finite-Frequency H ∞/GH 2 Static Output-Feedback Control Synthesis for Full-Vehicle Active Suspension Systems: A Metaheuristic Optimization Approach

In this paper, the problem of multi-objective control for active suspension systems with polytopic uncertainty is addressed via <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> / <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GH</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> static output feedback with a limited-frequency characteristic. For the overall analysis of the performance demanding both vehicle-ride comfort related to vertical- and transversal-directional dynamics and the time-domain constraints related to the driving maneuverability, a seven-degree-of-freedom full-vehicle model with an active suspension system is investigated. The robust static output-feedback control strategy is adopted because some state variables may not be directly measured in a realistic implementation. In designing this control, the finite-frequency H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance using the generalized Kalman—Yakubovich—Popov lemma is optimized to improve the passenger’s ride comfort, while the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GH</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> performance is optimized to guarantee the constraints concerning the suspension deflection limitation, road-holding ability, and actuator saturation problem. This control synthesis problem is formulated as nonconvex bilinear matrix inequalities and requires simultaneous consideration of different finite-frequency domain ranges for vertical and transversal motions for evaluating the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance. These design difficulties are overcome by the proposed multi-objective quantum-behaved particle swarm optimizer, which efficiently explores the relevant trade-offs between the considered multiple performance objectives and eventually provides the desired Pareto-optimal control set. Further, the numerical simulation cases of a full-vehicle active suspension system are presented to illustrate the effectiveness of the proposed control synthesis methodology in frequency and time domains.

Cooperative Multi-Objective Control of Heterogeneous Vehicle Platoons on Highway with Varying Slopes

Stability, vehicle safety, energy saving, and passenger comfort are the major objectives of vehicle platooning control. These objectives are coupled, interrelated, and even conflicting, so integrated optimization of multiple objectives is quite challenging. Particularly for heterogeneous platoons, the difficulties are intensified for the differences in vehicle dynamics. In this paper, the concept of symmetry is utilized in the platooning control, that is, the design method of each vehicle’s controller is the same. For each controller, it is to solve the optimal solution of multi-objective collaborative optimization. The concept of asymmetry is meanwhile embodied in the parameter setting of each controller, for the vehicle heterogeneity. The contents of this study are as follows. First, a mathematical model is established, in which the differences in vehicle dynamic characteristics of heterogeneous platoon, road slope, and aerodynamics are all taken into account. Then, based on distributed nonlinear model predictive control (DNMPC) method, multi-objective control strategies are proposed for the leader and followers, cooperatively. Furthermore, a weight coefficient optimization method is presented, to further improve the platoon’s multi-objective synthesis performance. Finally, comparative experiments are carried out. Results demonstrate that, compared with the classic cruise control method of vehicle platoons, the proposed approach can reduce energy consumption by more than 5% and improve tracking performance on the premise of passenger comfort. Real-road experiments verify that the proposed control system can function effectively and satisfy the computational requirements in real applications.

Research on Six-Wheel Distributed Unmanned Vehicle Path Tracking Strategy Based on Hierarchical Control.

For the multi-objective control problem of tracking effect and vehicle stability in the path tracking process of six-wheel distributed unmanned vehicles, a control strategy based on hierarchical control (HC) theory is proposed. A hierarchical kinematic model is designed considering the structural advantages of independent steering and independent driving of the unmanned vehicle, and this model is applied to the path tracking strategy. The strategy is divided into two levels of control. The upper level of control is to use the upper-level kinematic model as the prediction model of model predictive control (MPC), and to convert the solution problem of future control increments into the optimal solution problem of quadratic programming by setting the optimal objective function and constraints. The lower level of control is to map the optimal control quantities obtained from the upper level control to the six-wheel speeds and the four-wheel turning angles through the lower-level kinematics, and to design the six-wheel torque distribution rules based on deterministic torque and stability-based slip rate control for executing the control requirements of the upper level controller to prevent the unmanned vehicle from generating sideslip and precisely generating transverse moment to ensure the stable driving of the unmanned vehicle. Experiments were conducted on the Trucksim/Simulink simulation platform for a variety of road conditions, and the results showed that hierarchical control improved the accuracy of tracking the desired path and the driving stability on complex road surfaces more than MPC.

A New MPC Formulation Based on Suboptimal Voltage Vectors for Multilevel Inverters

Different new model predictive control (MPC) formulations have been recently proposed to reduce the real-time computation load, which makes the MPC algorithm promising for multilevel power converters. Unlike the conventional MPC formulation, which searches for the optimal switching state at each sampling time, the existing computationally efficient MPC formulations are to search for the optimal output voltage in the first stage. In the second stage, only the switching state redundancy under this optimal output voltage established in the first stage will be employed to achieve multiobjective. These computationally efficient MPC formulations based on searching an optimal voltage vector are usually validated on the power converter topologies with abundant switching redundancy or without floating capacitors. However, for the emerging topologies with less switching redundancy and floating capacitors, such as the five-level (5L) T-type nested neutral point clamped (T-NNPC) converters topology, the existing computationally efficient formulations based on optimal output voltage vector can lead to potential capacitor control failure due to the sacrificed multiobjective control performance. To address this issue, this article presents a novel MPC formulation based on suboptimal output voltage vectors considering both the system’s multiobjective control performance and computation burden reduction. With the determined suboptimal voltage vectors, a small group of the switching state candidate can be established to improve the system’s multiobjective control performance and efficiency. The proposed MPC formulation is finally validated on a 5L T-NNPC topology.