A novel discrete compound integral terminal sliding mode control (C-ITSMC) is proposed for permanent magnet synchronous motor (PMSM) speed system in this article. In this control scheme, the integral terminal sliding mode control (ITSMC) is first introduced to realize state convergence in finite time. Then, an extended state observer-based compensator is designed to solve the problem that sliding mode control needs large switching gain to handle disturbances. Third, a predictive control-based optimal control signal is obtained, and this optimal control signal is considered as an assistant control signal to drive the state to reach quasi-sliding mode in an optimal manner. In this way, reaching quality is improved and the tracking error band is further reduced. Finally, a compound control scheme is obtained. The major advantages of this scheme are characterized by output-based information only used, low order of controller, excellent model adaptability, and disturbance rejection ability. Experimental results show that the proposed control scheme can effectively reduce the output error and enhance the robustness of PMSM speed system.

Electrical load forecasting is a vital process for balancing the electricity supply and demand sections. In order to make a precise prediction, many intelligent methods aiming at forecasting future load of different horizons have been proposed in recent years. Regardless of the great progress in this field, yet two major problems widely exist in the field of midterm load forecasting, which are pseudo midterm forecast and divergence of the forecasting error. This article proposes a multistep forecasting approach, mainly based on phase space reconstruction and support vector machine (SVM) methods, to solve these two problems. The relations between the forecasting step in the future and the historical data points that need to be fed into the SVM model are derived, which endue the model with the real ability to forecast adjustable steps of future load without the divergence of error and, therefore, have a notable engineering application significance. The proposed methodology is implemented on the European Network on Intelligent Technologies dataset. Compared with previous methods, the results show that the multistep implemented model is of more accurate prediction and stronger robustness. Moreover, the method is easy to implement and able to be combined with other intelligent methods to get better performance.

In this article, taking the hydraulic system of mining hydraulic excavator boom and stick as the plant, an adaptive robust impedance controller based on an extended state observer and backstepping method is designed. The energy-saving operation and position tracking performance are considered in system modeling and control law design. The system effects on electro-hydraulic proportional valves with open centers and flow regeneration valves (FRVs) are considered. When hydraulic cylinders are extended, the proposed control strategy adopts a pump-controlled pressure closed-loop to shorten the dead time. When hydraulic cylinders are retracted, less oil is output to meet the idle demand. The valve-controlled position subsystem with impedance mode ensures smoother digging processes. Comparative simulations show that the proposed control strategy has better position tracking and smaller velocity fluctuations. Compared with the system without FRVs, the proposed system can reduce energy consumption by 27.32%.

Addressing the issue to restrain the nonlinear coupling disturbance in the multimotor parallel drive system and acquiring perfect driving control performance, a novel super-twisting terminal sliding mode synchronous control (STSC) is proposed. In this control scheme, a lumped error (LE) with a synchronization coefficient is designed to transform coupled control into LE convergence. Then, a recursive terminal sliding mode function with two layers is introduced. Based on this sliding mode function, the STSC scheme is proposed, and it can guarantee the LE finite-time convergence and the continuous control action in nature. A nonlinear extended state observer (NESO) is introduced to enhance robustness. Moreover, the NESO not only provides an estimation of disturbance but also provides a smooth velocity signal. Therefore, differential operations and filtering operations are avoided. Finally, a compound control scheme is obtained. Compared with conventional super-twisting algorithm (STA), the robustness is enhanced by embedding NESO-based disturbance compensation, and the advantage of continuous control action is inherited. The major advantages of this scheme are characterized by output-based information only used, good model adaptability, and strong disturbance rejection ability. Experimental results show the effectiveness of the proposed control law.

In order to meet stringent temperature-control requirements in a high-speed airflow wind tunnel (HAWT) for thermal simulation under complicated work conditions such as thermal strength experiment of aero engine blade and dynamic calibration of high temperature thermal coupler, this paper proposes a novel cascade fuzzy-PID (C-Fuzzy-PID) compound control method for regulating the fuel-oil flow rate in the inner loop and temperature in the outer loop. The mathematical models that characterize the dynamics of the heat airflow temperature in the combustor and the fuel-oil flow rate for combustion are derived, upon which the improved PID control laws for the inner and outer loops are described. The former employs a fuzzy-PID controller with a predictor for controlling flow rate in the inner loop, which effectively overcomes influences according to its characteristics of large inertia and transport lag in fuel-oil supply system on the temperature responses. The latter combines disturbance compensation and a fuzzy-PID feedback law to suppress influences due to factors such as change in work conditions, disturbances, and time-varying parameter variations. The C-Fuzzy-PID method has been numerically investigated by comparing simulation results against two traditional PID-based methods, as well as experimentally validated confirming that the proposed control algorithm has strong robustness and excellent adaptability for temperature control of an HAWT.