A system for the rapid prototyping of real-time control algorithms for open-circuit variable displacement axial-piston pumps is presented. In order to establish real-time control, and communication and synchronization with the programmable logic controller of an axial piston pump, the custom CAN communication protocol is developed. This protocol is realized as a Simulink^® S-function, which is a part of main Simulink^® model. This model works in real-time and allows for the implementation of rapid prototyping of various control strategies including advanced algorithms such as H∞ control. The aim of the algorithm is to achieve control system performance in the presence of various load disturbances with an admissible control signal rate and amplitude. In contrast to conventional systems, the developed solution suggests using an embedded approach for the prototyping of various algorithms. The obtained results show the advantages of the designed H∞ controller that ensure the robustness of a closed-loop system in the presence of significant load disturbances. These type of systems with displacement volume regulation are important for industrial hydraulic drive systems with relatively high power.

The article presents a developed embedded system for control of electrohydraulic power steering based on multivariable uncertain plant model and advanced control techniques. The plant model is obtained by identification procedure via “black box” system identification and takes into account the deviations of the parameters that characterize the way that the control signal acts on the state of the model. Three types of controller are designed: Linear-Quadratic Gaussian (LQG) controller, H _∞ controller and μ-controller. The main result is a performed comparative analysis of time and frequency domain properties of control systems. The results show the better performance of systems based on µ-controllers. Also the robust stability and robust performance are investigated. All three systems achieved robust stability which guarantees their workability, but only the system with µ-controller has robust performance against prescribed uncertainties. The control algorithms are implemented in specialized 32-bit microcontroller. A number of real world experiments have been executed, which confirm the quality of the electrohydraulic power steering control system.

Fractional-order models provide a powerful framework for capturing memory-dependent and viscoelastic dynamics in mechanical systems, which are often inadequately represented by classical integer-order characterizations. This study addresses the identification of dynamic parameters in both single-degree-of-freedom (1-DOF) and three-degree-of-freedom (3-DOF) Duffing oscillators with fractional damping, modeled using the Grünwald–Letnikov characterization. The 1-DOF system includes a cubic nonlinear restoring force and is excited by a harmonic input to induce steady-state oscillations. For both systems, time domain simulations are conducted to capture long-term responses, followed by Fourier decomposition to extract steady-state displacement, velocity, and acceleration signals. These components are combined with a GL-based fractional derivative approximation to construct structured regressor matrices. System parameters—including mass, stiffness, damping, and fractional-order effects—are then estimated using pseudoinverse techniques. The identified models are validated through a comparison of reconstructed and original trajectories in the phase space, demonstrating high accuracy in capturing the underlying dynamics. The proposed framework provides a consistent and interpretable approach for frequency domain system identification in fractional-order nonlinear systems, with relevance to applications such as mechanical vibration analysis, structural health monitoring, and smart material modeling.

This article is devoted to a comparison of two advanced control techniques applied to the same plant. The plant is a certain type of axial-piston pump. A linear-quadratic (LQR) controller and an H-infinity (H_∞) controller were synthesized to regulate the displacement volume of the pump. The classical solution to such a problem is to use a hydro-mechanical controller (by pressure, flow rate, or power) but, in the available sources, there are solutions that implement proportional-integral-derivative (PID), LQR, model predictive control (MPC), etc. Unlike a classical solution, in our case, the hydro-mechanical controller is replaced by an electro-hydraulic proportional valve, which receives a reference signal from an industrial microcontroller. It is used as the actuator of the pump swash plate. The pump swash plate swivel angle determines the displacement volume, respectively, and the flow rate of the pump. The microcontroller is capable of embedding various control algorithms with different structures and complexities. The developed LQR and H_∞ controllers are compared in the simulation and real experiment conditions. For this purpose, the authors have developed a laboratory experimental test bench, enabling a real-time function of the control system via USB/CAN communication. Both controllers are compared under different pump loading modes. Also, this paper contributes an uncertain model of an axial-piston pump with proportional valve control that is obtained from experimental data. Based on this model, the robust stability of the closed-loop system is investigated by comparing the structured singular value (μ). The investigations show that both control systems achieved robust stability. Moreover, they can tolerate up to four times larger uncertainties than modeled ones. The system with the H_∞ controller attenuates approximately at least 30 times the disturbances with frequency up to 1 rad/s while the system with the LQR controller attenuates at least 10 times the same disturbances.

The impossibility of replacing hydraulic drives with other type drives in heavy duty machinery is the main reason for the development of a system for controlling hydraulic power steering. Moreover, the need for remote automatic control of the steering in specific types of mobile machinery leads to significant scientific interest in the design of embedded systems for controlling electro-hydraulic steering units. This article introduces an approach, which has been developed by authors, for robust stability and robust performance analysis of two embedded systems for controlling electro-hydraulic power steering in mobile machinery. It is based on the suggested new more realistic “black box” SIMO model with output multiplicative uncertainty. The uncertainty is obtained by parameters confidence interval and Gauss approximation formula. The embedded control systems used a linear-quadratic Gaussian (LQG) controller and H_∞ controller. The synthesis of the controllers was performed on the basis of a nominal part of an uncertainty model. Robust stability and robust performance analyses were performed in the framework of a so-called structured singular value, μ. The obtained theoretical results were experimentally approved by real experiments with both of the developed control systems, which were physically realized as a laboratory test rig.