Three-Spool Marine Gas Turbine Multi-Objective Switching Control System Design and Optimization

In order to effectively solve a series of problems caused by harmonics in power system, an active power filter based on ANFIS-PI and repetitive control is designed. The traditional single control method cannot balance control accuracy and response speed, so a compound control strategy is adopted. Repetitive control can produce the same output as the harmonic current, so it can achieve zero steady-state error tracking compensation for each harmonic, but its dynamic performance is not good. As a traditional control method, the PI control method has a fast response speed, but in the actual application process, when the load changes suddenly, that is, when the system parameters change, its tracking effect is not ideal. Therefore, a composite control strategy of ANFIS-PI and repeated control is proposed. It has been proved that its compensation accuracy and dynamic response speed have been significantly improved.

Built environment control based on multi-objective optimization algorithm: Optimizing thermal comfort, indoor air quality and HVAC energy efficiency

Under the framework of switched system theory, the system states of three-phase voltage source converters (VSCs) can be regulated by subsystems switching according to the switching rule directly. However, because the subsystem selected for the next control cycle may same as that used in the present control cycle and the incorrect subsystem may be activated under system delay conditions, the unfixed switching frequency problem and the unstable subsystem switching problem can be found using the present switching control strategies. In this paper, a current switching predictive control (CSPC) method is proposed to the three-phase VSCs in the framework of switched system theory. The proposed method realizes the fixed switching frequency and avoids the unstable subsystem switching under system delay conditions, where advantages in the present methods, such as the accurate mathematical model, simple control structure, less control parameters, without vector modulation process are remained. The simulation and experiment results verify the effectiveness of the proposed methodology.

Electric load simulator (ELS) plays a vital role in the ground test and simulation of the electromechanical actuator (EMA) of an unmanned aerial vehicle (UAV), which is preferred by researchers for its dynamic response and high precision. However, clearance is an inevitable problem of the ELS system which can introduce backlash influencing the stability of the system. The backlash nonlinear can induce mechanical impact and impose limitations on the quality of loading torque control. In order to increase the accuracy of loading torque, a switching control method is presented to compensate for the backlash nonlinear. A time-optimal sliding mode control (TOSMC) method is used when the ELS system entering backlash, and a nonlinear proportional integral derivative (PID) controller is presented for the different system dynamic. A switching controller is also introduced to acquire suitable moment switching from TOSMC to nonlinear PID controller, ensuring the stability of the system. Experimental tests show that compared with the traditional PID control, this method can effectively reduce the torque overshoot when ELS crossing backlash and guarantee torque tracking speed and precision of ELS.

The comparison of different multi-loop control structures for a basic triangular system is the focus of the present paper. The idea is originated from game theory, where information is an essential component. Hence, the game-theoretic view of controller design in multi-loop control systems allows the question, how unequally distributed or incomplete information affects the control structure and the selection of the playerspsila strategies. Additionally, if constraints on the control signals are considered, the strategy set of each player is bounded. Thus, the solution of each game provides different Pareto-optimal sets depending on different bounded strategy sets. In the present paper, an asymmetric triangular multi-loop control structure of a reverse osmosis desalination plant was chosen as basis to study and discuss the effects of different information sets, due to the control structure, to the solution of each game.

This paper is concerned with the problems of robust switching control for near-space morphing vehicles (NMVs) with a large range of parameter uncertainty and external disturbance. For this purpose, a novel linear/nonlinear active disturbance rejection switching control method for the longitudinal dynamical model of NMVs based on the type-2 fuzzy logic system is proposed. Both linear active disturbance rejection control (LADRC) and nonlinear active disturbance rejection control (NLADRC) were designed for the velocity and altitude subsystems of NMVs. Then, the stability analysis of the cascade closed-loop and switching control systems were carried out. Furthermore, a switching control strategy based on the interval type-2 fuzzy logic system was developed, and the change rules of aerodynamic parameters with Mach number and angle of attack were examined. Finally, the experimental results validated the superior switching performance of the proposed control strategy.

Switching control of thrust regulation and inlet unstart protection for scramjet engine based on strategy of integral initial values resetting

Due to the limitation of traditional controller circuit integration, the traditional DC motor speed control method has the problem of low control accuracy, which greatly affects the stability of DC motor operation. Therefore, an adaptive control method of DC motor speed based on STC MCU is proposed. Combined with the basic structure and working principle of DC motor, the mathematical model of DC motor is established. Under this model, the running law of motor speed is analyzed, and STC single chip microcomputer is used to optimize and refit the traditional controller. The speed value of DC motor is measured in real time, and the adaptive control value of speed is determined according to the control target of speed, which is used as the input of controller to realize the adaptive control of DC motor speed. Through the control test experiment, the conclusion is drawn: compared with the traditional control method, the speed control error of the design method is reduced by 8.75r/min, and the design method has more advantages in the control accuracy.

The electro-hydraulic proportional position servo system is a kind of highly non-linear and time-varying system as well as parameter uncertainties. It is often difficult to achieve satisfactory control results with the traditional control methods. Considering that the adaptive neural network PID control method has the characteristics of online learning and adjustment PID control parameters adaptively, this paper puts forward to adopt BP-PID control method for the position servo control of electro-hydraulic proportional system. An online adaptive BP-PID controller is designed. The simulation model of the system is established based on Simulink platform. The step response and Sinusoidal tracking characteristics are researched for electro-hydraulic proportional position servo system by using traditional PID and BP-PID control algorithms through simulations and experiments. The results show that BP-PID has a strong ability of online learning and self-tuning PID parameters. Compared with the traditional PID control method, the BP-PID control has strong self-adaptability and robustness, and can significantly improve the step response speed and tracking control precision.

The main theme of this paper is to propose a novel switching control method for bridgeless PFC converter to improve the efficiency by reducing both switching and conduction losses. Comparing to the conventional method, the power device is always on (no switching loss) to provide a current path via the turn-on resistor of MOSFET to reduce conduction losses under light load condition. As the load increases, the power device is always off (no switching loss) to provide a current path via the body diode of MOSFET to reduce conduction losses under heavy load condition. In this paper, both simulation and experimental results will be shown to confirm the effectiveness of the proposed switching control method. Test results derived from a digital-controlled 1.2 kW PFC show the efficiency improvement can go up to 0.73% and 0.57% under full load and light load conditions, respectively. It will also be confirmed this efficiency improvement has no impact on the power factor and just simply changing the switching control method. Both measured steady state and transient waveforms will be shown for confirmation.

To improve the dynamic and steady-state control performance of permanent magnet synchronous motors under the three-vector model predictive current control method, this study proposes a switching current predictive control method based on the exponential moving average algorithm, which evaluates the magnitude of the change of the q-axis current slope in real time to discriminate the motor’s operating conditions and selects the optimal control method for different operating conditions. Meanwhile, the traditional three-vector model predictive current control method is improved by introducing a comparison mechanism for the q-axis current slope to select the second effective voltage vector, avoiding the secondary optimization calculation of the value function and reducing the computational complexity of the traditional method. By comparing the proposed method with the traditional three-vector model predictive current control method, the experimental results prove that the proposed method improves the system’s dynamic response and steady-state performance.

Research on Control Methods of Brake Resistance of HEV

Aiming at the problem that reactive power is too high caused by the control method of electric drive system of pump station, an artificial intelligence control method of reactive power of electric drive system of pump station is proposed. The transmission signal of the electric drive system of pumping station is processed by the non-linear operation of proportion, integral and differential through the structure of fuzzy PID algorithm. The transmission signal enters the nonlinear function estimator of the neural network controller, and through the function processing of the inverse process, the nonlinear mapping ability of the neural network is utilized to finally realize the artificial intelligence control. In order to verify the control reaction rate and the optimization effect of the proposed control method, compared with the traditional control method, the simulation comparison experiment and the actual comparison experiment were respectively designed. Experimental results: The simulation comparison experiments show that the control response rate of artificial intelligence control method is better than the traditional control method; the actual contrast experiment shows that the artificial intelligence method can effectively reduce the reactive power of the transmission system and can be popularized.

ABSTRACTDue to the challenges in determining the parameters of traditional controllers, achieving efficient performance during the control process remains difficult. To improve control performance, this paper presents a novel speed control scheme based on the parameter tuning of a linear quadratic regulator (LQR). The proposed control approach begins by establishing the speed state error in the rotor reference coordinate system, followed by the design of a custom parameter switching surface and control law. LQR theory is then utilized to adjust the state‐space equations, allowing for the calculation of the parameters for the tracking error function and control law. This controller incorporates both the speed tracking error and the integral of the speed tracking error. Simulations and experiments are designed to validate the effectiveness of the proposed control scheme. Comparison results with traditional control methods, such as PI control based on motor parameters, sliding mode control, and PI control with state feedback, indicate that the proposed LQR parameter tuning control scheme excels in the speed control of PMSM.

This article is based on the multi-agent technology, the structure framework of the dynamic and switched control system for arterial traffic signal system based on multi-agent is constructed. The intersection phase agent, the switching control agent and the arterial coordinated control agent are respectively designed, and the fuzzy inference module to realize each agent's intelligence is introduced in detail. In this system structure, the chaos genetic algorithm is applied to optimize the fuzzy membership function of intersection phase agent in real time to make it possess the ability of self-learning and improve the dynamic performance of the system, and the switching control agent is introduced to optimize the ordering of phases. Using matlab simulation software, simulation experiments were carried out for three consecutive intersections of arterial. The average queue length curve of vehicles at the intersection under different control methods is given. The results show that the proposed method has better control effect.