This paper implements fractional order controller to the compound control, taking the first-order inverted pendulum system as the plant, In which, using direct compensator to reach steady. Then we give the design method of fractional order PID controller (PI^λD^μ controller), fractional order (PD^μ controller controller), integer order PID controller and optimize parameters based on genetic algorithm. The simulation results prove that the proposed method can achieve high performance comparing the PID controller.

Subsurface damage (SSD) induced during the processing of optical components, which are key parts of large optical systems, can deteriorate optical system performance or damage the complete system. To eliminate the SSD of optical components in subsequent processing, it must be accurately detected. This paper presents a review of the principle, characteristics, research status, and development trends of SSD detection methods for optical components. This review finds that destructive detection methods can damage the components and cannot detect SSD online, but they are reliable and accurate and characterized by facile principles, easy implementation, and inexpensive equipment. Consequently, such methods are widely used for the validation of non-destructive methods and quality control of components in industrial production. In comparison, non-destructive detection methods can detect SSD online without destroying the components, shorten the detection cycle, increase the overall production efficiency, and decrease the cost. Therefore, non-destructive detection methods have promising development prospects.

In today’s automation control systems, the PID controller, as a core technology, is widely used to maintain the system output near the set value. However, in some complex control environments, such as the application of ball screw-driven rotating motors, traditional PID parameter adjustment methods may not meet the requirements of high precision, high performance, and fast response time of the system, making it difficult to ensure the stability and production efficiency of the mechanical system. Therefore, this paper proposes a cuckoo search optimisation coupled with an improved grey wolf optimisation (CSO_IGWO) algorithm to tune PID controller parameters, aiming at resolving the problems of the traditional grey wolf optimisation (GWO) algorithm, such as slow optimisation speed, weak exploitation ability, and ease of falling into a locally optimal solution. First, the tent chaotic mapping method is used to initialise the population instead of using random initialization to enrich the diversity of individuals in the population. Second, the value of the control parameter is adjusted by the nonlinear decline method to balance the exploration and development capacity of the population. Finally, inspired by the cuckoo search optimisation (CSO) algorithm, the Levy flight strategy is introduced to update the position equation so that grey wolf individuals are enabled to make a big jump to expand the search area and not easily fall into local optimisation. To verify the effectiveness of the algorithm, this study first verifies the superiority of the improved algorithm with eight benchmark test functions. Then, comparing this method with the other two improved grey wolf algorithms, it can be seen that this method increases the average and standard deviation by an order of magnitude and effectively improves the global optimal search ability and convergence speed. Finally, in the experimental section, three parameter tuning methods were compared from four aspects: overshoot, steady-state time, rise time, and steady-state error, using the ball screw motor as the control object. In terms of overall dynamic performance, the method proposed in this article is superior to the other three parameter tuning methods.

The liquid crystal spatial light modulator (LCSLM) is an optical device that can realise non-mechanical beam scanning. However, the traditional integer-order model cannot adequately characterise the dynamic performance of LCSLM beam steering because of the viscoelasticity of liquid crystals. This paper uses the memory characteristics of fractional calculus to construct a fractional constitutive equation for liquid crystals. Combining this equation with the LCSLM beam steering principle, a fractional-order model of the beam steering system is established, and the Legendre wavelet integration operational matrix method is used to estimate the model parameters. In addition, we established a test platform for the dynamic characteristics of LCSLM beam steering system and verified the effectiveness of the established model through experiments. The fitting effects of the integer-order and fractional-order models are compared, and the influence of different model orders on the dynamic performance of beam steering is analysed. Experimental results show that the fractional-order model can accurately describe the dynamic process of beam steering, and this model can be applied to the study of LCSLM-based two-dimensional non-mechanical beam steering control strategies to achieve fast, accurate, and stable beam scanning.

<!-- *** Custom HTML *** --> To compensate for disturbances in an aircraft’s forward flight and variations in its attitude and angular velocity in the imaging process of photoelectric imaging system, a method of image motion compensation using a fast steering mirror was put forward. First, the working sequence of the image motion compensation system was designed. The position of the fast steering mirror is established by increasing the oblique wave to allow the fast steering mirror to move at the desired speed and compensate for the image motion speed. Then, a mathematical model of the fast steering mirror was established. A linear extended-state observer is designed to estimate the disturbance in real-time, and disturbance compensation is generated to offset the disturbance. Finally, a step response experiment and a tracking experiment were performed to test the characteristics. The step response curve shows that the system’s stable time is 1.8 ms. The tracking characteristic is determined by a given scan curve. The fast steering mirror can satisfy the requirement for a high-speed and highly precise tracking system. It improves the system’s interference rejection performance and reduces the difficulty of controller design.