Controller Design Research Articles

Robust observer-based-α-variable model-free supertwisting fractional order sliding mode control for nonlinear PEMFC system with uncertainties and disturbance

The service life and efficiency of proton exchange membrane fuel cells (PEMFCs) are significantly related to the control performance of the air supply system. Therefore, this research develops a novel robust observer-based- [Formula: see text]-variable model-free supertwisting fractional-order sliding mode control ([Formula: see text]-MF-STFOSMC) for complex nonlinear PEMFC air supply system with unmeasurable state variables, model uncertainties, and external disturbance. First, the fifth-order nonlinear PEMFC air supply system model is presented, and the unmeasured state variables are estimated using a nonlinear disturbance observer (NDOB1). Second, the ultra-local model (ULM) algorithm is employed to reconstruct the complex nonlinear PEMFC air supply system, avoiding the need for precise modeling and reducing the controller design difficulty. To estimate and compensate for the uncertain dynamics in the ULM algorithm, another NDOB2 is proposed to realize zero estimation error and finite-time observation. Besides, to achieve optimal control performance with less input chattering, finite-time convergence, and fast response speed, the [Formula: see text]-MF-STFOSMC is designed using super-twisting fractional-order sliding mode control (STFOSMC) algorithm. Furthermore, the stability of [Formula: see text]-MF-STFOSMC via a closed-loop system is verified using the Lyapunov theorem. Finally, the nonlinear PEMFC air supply system model with the proposed controller is realized in MATLAB/Simulink environment, and the simulation results are given to show the superiority and effectiveness of the proposed technique.

A novel nonlinear controller design of three-phase grid-tied photovoltaic system

A novel nonlinear controller design of three-phase grid-tied photovoltaic system

Finite-Time Fault-Tolerant Control via Fully Actuated System Approaches.

In this article, a finite-time fault-tolerant controller based on the fully actuated system (FAS) theory is presented to realize system stabilization and trajectory tracking. Paralleling to first-order nonlinear state space theory, the high-order FAS (HOFAS) theory contains rich controller design approaches. The existing FAS approaches can only give general global asymptotic stability results. In order to enhance the applicability of FAS approaches in fast control systems, a parameterized FAS stabilization controller based on the homogeneity principle is established for global finite-time stability. Moreover, a finite-time FAS tracking controller based on a finite-time observer is proposed for a HOFAS model with process faults. The proposed observer can yield zero-value convergence of state estimation error and fault estimation error in a finite time, and the proposed fault-tolerant controller can yield zero-value convergence of tracking error in a finite time. The main results are proved theoretically and illustrated experimentally.

Advanced controller design for D-FACTS device in grid-connected photovoltaic system controller

Advanced controller design for D-FACTS device in grid-connected photovoltaic system controller

Analysis and Controller Design for Parameter Varying T-S Fuzzy Systems with Markov Jump

In this paper, we investigate a novel T-S fuzzy parameter varying system with Markov jump, in which parameters depend not only on a Markov chain but also on linear parameter varying elements that take values in convex polytopic sets. Stable conditions and the gain-scheduling controller design method for this system are obtained. Applying Lyapunov function depending on the operation mode and full block S-procedure lemma, we obtain stochastic stabilization conditions. We find that this novel system has two distinct advantages. On the one hand, it inherits the advantages of traditional T-S fuzzy systems in handling nonlinear objects under the frame of T-S fuzzy systems; on the other, it obtains the advantages of dealing with time-varying characteristics from the point of linear parameter varying (LPV) systems. Finally, the theory results are illustrated via numerical simulation.

Development of Path-Finding Controller Design for Hovercraft Model via Neural Network Technique and Meta-Heuristic Algorithms

Development of Path-Finding Controller Design for Hovercraft Model via Neural Network Technique and Meta-Heuristic Algorithms

Lyapunov-based robust model predictive tracking controller design for discrete-time linear systems with ellipsoidal terminal constraint

In this article, a robust model predictive control (MPC) method is introduced based on Lyapunov-theory to control the discrete-time uncertain linear systems due to external disturbances. The structure of the proposed controller consists of two parts designed based on the offline/online schemes. In the offline-scheme, an H ∞ -based robust tracking controller is provided to satisfy the robust and tracking performance. Based on the H ∞ performance, a new linear matrix inequality problem is developed to calculate the offline-controller gains. By considering the Lyapunov-function of the offline-controller as the terminal cost of the MPC and the designed offline-controller, the online optimisation problem (OOP) is structured. This means, the MPC is designed based on the stabilised system to satisfy the physical limitations of the overall controller and the system states. Moreover, to improve the feasibility problem of the OOP, an ellipsoidal terminal constraint is added to the proposed MPC problem. Therefore, compared with the existing min–max MPC and tube MPC, the advantages of the overall controller are feasibility improvement and reducing the computational complexity with less conservatism while the robustness against parametric uncertainties and disturbances is achieved. Two simulation examples are employed to show the superiorities of the proposed robust MPC.

An approach to mismatched disturbance rejection control for uncontrollable systems

This study focuses on the problem of optimal mismatched disturbance rejection control for uncontrollable linear discrete-time systems. In contrast to previous studies, by introducing a quadratic performance index such that the regulated state can track a reference trajectory and minimize the effects of disturbances, mismatched disturbance rejection control is transformed into a linear quadratic tracking problem. The necessary and sufficient conditions for the solvability of this problem over a finite horizon and a disturbance rejection controller are derived by solving a forward–backward difference equation. In the case of an infinite horizon, a sufficient condition for the stabilization of the system is obtained under the detectable condition. Additionally, in combination with the generalized extended state observer, a controller design method is proposed, and the stability analysis of the system under this controller is presented. This paper details our novel approach to disturbance rejection. Finally, four examples are provided to demonstrate the effectiveness of the proposed method.

Hierarchical attitude stabilization controller design and analysis for underactuated spacecraft on SO(3)

In this paper, the complete attitude stabilization of underactuated spacecraft with two parallel single gimbal control moment gyroscopes (SGCMGs) is explored on 3-dimensional special orthogonal group (SO(3)) and its corresponding Lie algebra (so(3)). Instead of assumption on zero total angular momentum in existing article, a less conservative criterion is adopted to ensure system controllability, which does not simplify system dynamics. On the kinematic level, an ideal controller is proposed to globally stabilize attitude without singular initial condition and stagnation behavior. Besides, the ideal kinematic controller is developed on so(3), which avoids singularity or unwinding phenomenon caused by other attitude parameters. On the dynamic level, a hierarchical controller consisting of two parts is proposed. The high-level sliding mode part enforces finite time stabilization of angular velocity about underactuated axis while the low-level part tracks ideal angular velocity commands about actuated axes. A rigorous proof of the whole dynamic-kinematic system that has not been explored before is given. Analysis of hierarchical control from the perspective of linear algebra provides a novel insight into controller design for underactuated systems. Furthermore, the paradigm of controller design which is applicable to other underactuated systems is derived. Simulation results validate the effectiveness of the proposed control logic.

Improved dynamic performance of triple active bridge DC-DC converter using differential flatness control for more electric aircraft applications

The triple active bridge (TAB) converter has been proposed to improve power density and availability in more electric aircraft applications. However, the conventional proportional-integral (PI) controller used for TAB voltage control often exhibits slow response and significant overshoot, which can impact dynamic performance. Moreover, achieving decoupling control among ports introduces computational complexity in controller design. To address these issues, this paper introduces an effective diagonal matrix decoupling strategy based on differential flatness control with single-phase shift modulation applied to a TAB converter. The proposed differential flatness control offers superior transient performance, control flexibility, and precision, ensuring compliance with DC voltage regulations while achieving optimal decoupling among ports. The comparative analysis assesses various criteria, including steady-state and dynamic performance, control complexity, and regulation and tracking properties, against PI control, unit matrix decoupling control, and the proposed differential flatness control. Hardware-in-loop (HIL) experimentation verifies the performance, confirming faster dynamic characteristics and robust port power decoupling. The results show a significant improvement in efficiency, reaching a maximum of 95.5 %, indicating reduced switching losses and enhanced overall system performance. The study concludes with a discussion on the implications of these findings and potential future research directions, such as integrating advanced optimization algorithms further to enhance the control strategy's robustness and adaptability.

Adaptive Fuzzy Filter-based L 1 Adaptive Controller Design for Electromechanical Actuator Containing Uncertainties and Disturbances

Conventional L 1 adaptive controller utilizes high adaptation gain to quickly adapt time varying uncertainties and disturbances. However, it contaminates the control signal with high frequency components. To eliminate this high frequency signal, it uses a low pass filter with fixed structure. Yet, the main problem with this fixed structured filter is that it may cancel the estimated values of uncertainties and disturbances along with the high frequencies. To overcome this problem, in this research work, an adaptive fuzzy low pass filter is proposed in place of the fixed structured filter of the L 1 adaptive controller. In this proposed research work, the filter changes its structure according to the time varying uncertainties and disturbances. Hence, the contributory part of this work is that the proposed adaptive fuzzy filter efficiently cancels out high frequency components without nullifying the estimated values of uncertainties and disturbances from the control signal. The stability of the proposed adaptive fuzzy filter-based L 1 adaptive controller is guaranteed analytically. The proposed method is employed on an electromechanical actuator, viz., DC motor experimental setup to validate its effectiveness. Adequate cancellation of high frequency signal incurs smooth control signal which in turn provides lower control energy.

Evaluation Approach and Controller Design Guidelines for Subsequent Commutation Failure in Hybrid Multi-Infeed HVDC System

Due to the difference in output characteristics between the line-commutated converter-based high-voltage direct current (LCC-HVDC) and voltage-source converter-based high-voltage direct current (VSC-HVDC), the hybrid multi-infeed high-voltage direct current (HMIDC) presents complex coupling characteristics. As the AC side is disturbed, the commutation failure (CF) occurring on the LCC side is the main factor threatening the safe operation of the system. In this paper, the simplified equivalent network model of HMIDC is established by analyzing the output characteristics of VSC and LCC. Hereafter, based on the derived model and the control system of LCC-HVDC, the dynamic equations of the extinction angle are deduced. Consequently, by applying the phase portrait method, the causes of CF occurring in the HMIDC system as well as the impacts of control parameters on the transient stability are revealed. Furthermore, the stabilization boundaries for the reference value of the DC voltage are obtained via the above analysis. Finally, the theoretical analysis is verified by the simulations in the PSCAD/EMTDC.

State of-The-Art Multi-Input DC-DC Converter Topologies and their Control Techniques: A Review

Environmental awareness and technological advancement have made renewable energy sources such as fuel cell,solar photovoltaic (PV), wind energy an emerging research area. Power electronics converters are used as interface betweenthe renewable energy sources and the load unit, aimed at matching these sources with the load demand and improving thesteady-state and dynamic characteristics. Traditional method of using multiple single-input single-output dc-dc converter tointegrate several renewable energy sources, comes with challenges in controller design, poor efficiency, low power densityand increase in cost. To address these limitations, the use of an integrated multi-port converter is a preferable solution.Recently, several multi-port dc-dc converter topologies have been reported each having its peculiarity in terms of number ofcomponent count, relationships between input and output, voltage conversion ratio, control algorithm and efficiency. Thisarticle reviewed multi-port dc-dc converters presented by different research groups from the point of view of topology, inputand output relation and structure. Furthermore, control algorithms proposed to solve various control problems are alsoreviewed.

A Novel Fractional Order Proportional Integral-Fractional Order Proportional Derivative Controller Design Based on Symbiotic Organisms Search Algorithm for Speed Control of a Direct Current Motor

A Novel Fractional Order Proportional Integral-Fractional Order Proportional Derivative Controller Design Based on Symbiotic Organisms Search Algorithm for Speed Control of a Direct Current Motor

Dual Channels Event-Triggered Asymptotic Consensus Control for Fractional-Order Nonlinear Multiagent Systems.

This article investigates the event-triggered leaderless consensus control problem for fractional-order multiagent systems (FOMASs), where both the agent-to-agent communication channel and the controller-to-actuator communication channel are based on the events. A filter is introduced to transform the original high-order system into a first-order one, greatly simplifying the complexity of controller design compared to the traditional backstepping. Further, the convergence of filtered output signals is proved to be consistent with that of the outputs of agents themselves. Superior to the traditional event-triggered scheme, two dynamic variables are designed for the triggering conditions of the communication among agents and the controller update, respectively. Via elaborately constructing the dynamic variables, zero-error leaderless consensus can be achieved instead of only ultimately uniformly bounded result. It is proved that the proposed control strategy can guarantee better control performance of leaderless consensus under limited communication resources, and Zeno behavior is excluded. Finally, two examples are provided to verify the effectiveness of our proposed control approach.

A Simplified 4-DOF Dynamic Model of a Series-Parallel Hybrid Electric Vehicle

To research the dynamic response of a new type of dedicated transmission for a hybrid electric vehicle, a detailed dynamics model should be built. However, a model with too many degrees of freedom has a negative effect on controller design, which means the detailed model should be simplified. In this paper, two dynamic models are established. One is an original and detailed powertrain dynamics model (ODPDM), which can capture the transient response, and it is validated that the ODPDM can be used to accurately describe the real vehicle in some specific operating conditions. The other is a simplified torsional vibration dynamics model to study the torsional vibration characteristics of the hybrid electric vehicle. Compared with the full-order model, which is based on the ODPDM, the simplified model has a very similar vibration in low frequency. This study provides a basis for further vibration control of the hybrid powertrain during the process of a driving-mode switch.

Study on a nonlinear dynamic characteristic of the positive flow pump in its pilot hydraulic cylinder

The displacement of the positive flow pump is controlled by its pilot hydraulic cylinder. The tracking performance of the pump displacement directly affects the energy saving of the hydraulic excavator through power matching. In this article, a nonlinear dynamic characteristic of the positive flow pump in its pilot hydraulic cylinder is studied to improve the mathematical model for controller design. The concept of relative water hammer is first proposed to describe the relative pressure wave acting on the hydraulic piston to illustrate the mechanism of the nonlinearity. Chaotic motion can be generated by the relative water hammer when the hydraulic piston is in a partial stroke. The mathematical model is derived and its critical parameters are analyzed. The simulation and experimental results verify the existence of the relative water hammer and the effect of each critical parameter on the pilot hydraulic cylinder and the positive flow pump.

Differential Flatness Based Unmanned Surface Vehicle Control: Planning and Conditional Disturbance-Compensation

To achieve precise control of the symmetrical unmanned surface vehicle (USV) under strong external disturbances, we propose a disturbance estimation and conditional disturbance compensation control (CDCC) scheme. First, the differential flatness method is applied to convert the underactuated model into a fully actuated one, simplifying the controller design. Then, a nonlinear disturbance observer (NDOB) is designed to estimate the lumped disturbance. Subsequently, a continuous disturbance characterization index (CDCI) is proposed, which not only indicates whether the disturbance is beneficial to the system stability but also makes the controller switch smoothly and suppresses the chattering phenomenon greatly. Indicated by the CDCI, the proposed CDCC method can not only utilize the beneficial disturbance but also compensate for the detrimental disturbance, which improves the USV’s control performance under strong external disturbances. Moreover, a trajectory-planning method is designed to generate an obstacle avoidance reference trajectory for the controller. Finally, simulations verify the feasibility of applying the proposed control method to USV.

Correction: Refined sinh cosh optimizer tuned controller design for enhanced stability of automatic voltage regulation

Correction: Refined sinh cosh optimizer tuned controller design for enhanced stability of automatic voltage regulation

Water-Coal Ratio Control Strategy of Ultra Supercritical Unit Based on Neural Network Inverse Model

Since the boiler water-coal ratio control system is a complex system with the characteristics of non-linearity and strong coupling, water-coal ratio control is one of the most difficult problems in the coal-fired power generation process control engineering, whose control strategy is of great importance. While, in order to achieve the control of water-coal ratio effectively during the coal-fired power generation process, the neural network inverse system scheme is proposed for the control of the water-coal ratio of ultra-supercritical units. Firstly, the model for the water-coal ratio system of an ultra-supercritical unit is presented in allusion to the characteristics of the water-coal ratio control system. Then the concept of the neural network based inverse system, the principle and method of the design of the neural network inverse controller are discussed. Finally, the control scheme is verified by establishing neural network inverse system on MATLAB toolbox. The experimental results show that the neural network based inverse system models has better control effect in terms of anti-interference ability, stability time than that of PID control system.