As hydraulic Euler–Lagrange systems evolve to encompass high-dimension and intricate structures, the formulation of the mechanical dynamics model becomes impractical, even though the hydraulic dynamic information remains accessible. In this article, we make the first attempt to establish model-data hybrid driven controller for hydraulic Euler–Lagrange systems. The proposed strategy commences with the formulation of model-based nonlinear robust controller, followed by the introduction of actor–critic reinforcement learning to effectively tackle uncertainties associated with unknown mechanical dynamics. Employing Lyapunov analysis, we have proven the asymptotic stability of the model-based nonlinear robust controller, along with the convergence and (sub)optimality of the introduced actor–critic reinforcement learning. Building upon this foundation, the newly devised hybrid-driven controller still guarantees asymptotic stability through the reconstruction of the error auxiliary function. We validated the efficacy of the proposed strategy on a well-established six-degree-of-freedom hydraulic manipulator and conducted a comparative analysis with the purely data-driven approach to demonstrate the superior performance of the developed controller. The integration of model-based and data-driven terms in our strategy signifies notable advancements in the control paradigm for hydraulic Euler–Lagrange systems, and the conceptual control framework also holds the potential to address control challenges within diverse and intricate industrial systems.

Active road noise control (ARNC) systems have been widely investigated for low-frequency road noise attenuation in vehicle cabins. Multiple reference and error sensors are usually required to ensure noticeable noise reduction. However, this tends to slow down the convergence speed of adaptive algorithms due to the coupling of secondary paths and the cross correlation of reference signals. Furthermore, the high computational burden of normally utilized multichannel control algorithms exacerbates the difficulty of practical implementations. In this paper, an online decoupling-whitening frequency domain filtered-error least mean square (ODW-FDFeLMS) algorithm is proposed to address the aforementioned problems. Secondary path decoupling through inner-outer product decomposition and online reference whitening through spectral factorization effectively accelerate the convergence rate. Additionally, the utilization of the filtered-error algorithm based on frequency domain processing mitigates the computational complexity. Simulations with measured road noise data confirm the superiority of the ODW-FDFeLMS algorithm over existing algorithms in terms of convergence speed and computational complexity. Real-time experiments in a vehicle cabin further confirm the effectiveness of the proposed algorithm.

The reflection of audio sounds generated by a parametric array loudspeaker (PAL) is investigated in this paper. The image source method and the non-paraxial PAL radiation model under the quasilinear approximation are used to calculate the reflected audio sound from an infinitely large surface with an arbitrary incident angle. The effects of the surface absorption in the ultrasound frequency range are studied, and the simulation and experiment results show that the reflection behavior of audio sounds generated by a PAL is different from those generated by traditional audio sources. The reason is that the reflected sound generated by the PAL consists of the reflection of audio sounds generated by incident ultrasounds and the audio sounds generated by the reflected ultrasound, and it is the latter that determines the directivity of the reflected audio sound.

Near-field error sensing is beneficial to the compactness and stability of an active noise control system. This paper proposes an error sensing strategy based on the spatial Fourier transform to achieve active directivity control of radiated sound. The error microphone array is located on a plane close to the primary source and the cost function is the weighted sum of the error signals from the microphones. The weighting factor is related to the phase shift from the error microphones to the plane perpendicular to the direction where noise reduction is required. The geometric configurations of the error microphone array for effective directivity control are investigated. It is found that the distance between neighboring error microphones must be less than approximately half the wavelength of the frequency of interest and the equivalent size of the microphone array should be larger than twice the size of the primary source. Numerical simulations and experiments demonstrate the feasibility of the proposed strategy.

Previous work has demonstrated that installing secondary sources at the edge of a cavity opening can reduce sound radiation through it, but the mechanisms are not clear, which is investigated in this paper by using the modal decomposition method. It is found that a double layer edge system achieves better performance than a single layer system because secondary sources at the edge of the same layer cannot excite some modes effectively and those at different heights compensate this. There exists an upper limit frequency for the systems with boundary installed secondary sources, which is mainly decided by the length of the short side of the opening. More secondary source layers at the edge will increase the upper limit frequency.