A continuous adaptive fast terminal sliding mode based speed regulation control is proposed for a permanent magnet synchronous motor (PMSM) drive, where an improved super-twisting algorithm with linear terms (STLT) is constructed in the super-twisting speed observer. First, the STLT observer introduces a first-order term on the basis of conventional super-twisting sliding mode observer to improve the speed estimation convergence rate and to reduce the estimation error. Second, an adaptive function is added to the reaching law for the continuous fast terminal sliding mode speed controller to produce a faster response speed and stronger control robustness. In addition, the total disturbance of the system is estimated via Luenberger disturbance observer, which contributes to the feedforward compensation control component. The closed-loop stability analysis is rigorously given by the Lyapunov stability theory. Finally, real-time experiments on a PMSM platform are carried out to show the effectiveness and superior performance of the proposed control approach.

For the purpose of simplifying the physical structure, improving the anti-disturbance performance and enhancing the response performance of permanent magnet synchronous motor (PMSM), this article proposes a novel sensorless fixed-time sliding mode control scheme with fast fixed-time convergence for PMSM. First, to realize sensorless control, a barrier function (BF)-based adaptive super-twisting observer (BF-ASTO) is designed to accurately estimate the rotor's position and speed of the PMSM. The BF is chosen as an adaptive algorithm for online tuning the parameters of BF-ASTO to achieve a better speed estimation performance. Then, an adaptive fixed-time integral sliding mode controller (AFTISMC) is proposed based on fixed-time stability theory, which guarantees both the independence of the settling time on the initial conditions and the finite time speed tracking error convergence. Lyapunov stability analysis is rigorously given for both the designed BF-ASTO and the AFTISMC, respectively. Finally, real-time experimental results are provided to verify the effectiveness of the proposed control method with the BF-ASTO.

Neuromorphic computing can solve computationally hard problems with energy efficiencies unattainable for von Neumann architectures. A locally-active memristor, which possesses the capability to amplify infinitesimal fluctuations in energy and can be used to generate neuromorphic behaviors, is a natural candidate for constructing an electronic equivalent of biological neurons. This paper identifies some unknown neuromorphic dynamics of the Chua corsage memristor (CCM), and shows that the CCM, when biased at the edge of chaos domain, can exhibit rich dynamics of biological neurons. Using Chua’s theories of local activity and edge of chaos, we demonstrate that under the destabilizing of the input voltage and the circuit parameters (inductance or capacitance), two CCM-based circuits can produce thirteen types of neuromorphic behaviors either on, or near the edge of chaos domain via supercritical or subcritical Hopf bifurcation. In addition, we give the conditions to test the edge of chaos of the CCM and the CCM-based circuit only by using the poles and the zero of their admittance functions.

S-type locally-active memristor (LAM) has a great potential for brain- inspired neuromorphic computing, where the S-type LAM-based oscillator is a fundamental building block. Concerning the S-type LAM, this paper constructs a material-independent model in simple mathematical expression, which can be relatively easily analyzed. By biasing the memristor into the locally- active region, and connecting it with a capacitor, a second-order oscillator can be built. The small-signal equivalent circuit of the memristor and its frequency response are applied to determine the period oscillation frequency range and compensation capacitance. Hopf bifurcation theory is used to analyze oscillation mechanism of the second-order circuit and appropriate capacitance. By adding an extra inductor into the second-order oscillator, a novel third-order chaotic circuit is developed, where a saddle-focus is derived to create chaos. Its dynamic characteristics are investigated via Lyapunov exponents, bifurcation diagrams, dynamic route map, and so on. The local activities of the single memristor, second-order oscillator, and third-order chaotic circuit are verified through the mathematical analysis. Finally, physical circuit realizations of the S- type LAM-based oscillators, including the memristor emulator, are presented. Both simulation and experimental results demonstrate the practicability of the proposed mathematical model and the validity of the theoretical analysis.

In this brief, we propose a novel locally active memristor based on a voltage-controlled generic memristor model and use the analysis methods of standard nonlinear theory to analyze its characteristics and illustrate the concept of local activity via the dc v-i loci of memristor and non-volatile memory via the power-off plot of memristor. A chaotic attractor is observed with a simple nonlinear circuit that only includes three circuit elements in parallel: 1) a nonlinear locally active memristor; 2) a linear passive inductor; and 3) a linear passive capacitor. Then, we analyze the dynamical characteristics of the above circuit and show complex bifurcation behaviors.