Differential Evolution Algorithm-Based Iterative Sliding Mode Control of Underactuated Ship Motion

The differential evolution algorithm (DEA)-based iterative sliding mode control (ISMC) method was proposed for the path tracking problem of three-degree-of-freedom (3-DoF) underactuated ships under external interference, with the nonlinear separate model proposed by mathematical model group (MMG). To improve control quality and enhance robustness of the control system, a swarm intelligence optimization algorithm is used to design a controller parameter optimization system. The DEA was adopted in the system to solve the minimum system evaluation index function, and the optimal controller parameters are acquired. Considering the impact of chattering on the actual project, a chattering measurement function is defined in the controller design and used as an input of the controller parameter optimization system. Finally, the 5446TEU container ship is carried out for simulation. It is verified that the designed controller with strong robustness can effectively deal with the disturbances; meanwhile, the chattering of the output is significantly reduced, and the control rudder angle signal conforms to the actual operation requirements of the ship and is more in line with the engineering reality.

A Unified Framework for the H∞ Mixed-Sensitivity Design of Fixed Structure Controllers through Putinar Positivstellensatz

In this paper, we present a novel technique to design fixed structure controllers, for both continuous-time and discrete-time systems, through an H∞ mixed sensitivity approach. We first define the feasible controller parameter set, which is the set of the controller parameters that guarantee robust stability of the closed-loop system and the achievement of the nominal performance requirements. Then, thanks to Putinar positivstellensatz, we compute a convex relaxation of the original feasible controller parameter set and we formulate the original H∞ controller design problem as the non-emptiness test of a set defined by sum-of-squares polynomials. Two numerical simulations and one experimental example show the effectiveness of the proposed approach.

Predictive visual control network for occlusion solution in human-following robot

Purpose The purpose of this paper is to propose a new video prediction-based methodology to solve the manufactural occlusion problem, which causes the loss of input images and uncertain controller parameters for the robot visual servo control. Design/methodology/approach This paper has put forward a method that can simultaneously generate images and controller parameter increments. Then, this paper also introduced target segmentation and designed a new comprehensive loss. Finally, this paper combines offline training to generate images and online training to generate controller parameter increments. Findings The data set experiments to prove that this method is better than the other four methods, and it can better restore the occluded situation of the human body in six manufactural scenarios. The simulation experiment proves that it can simultaneously generate image and controller parameter variations to improve the position accuracy of tracking under occlusions in manufacture. Originality/value The proposed method can effectively solve the occlusion problem in visual servo control.

Sub/Super-Synchronous Oscillation Oriented Dominant Controller Parameters Stability Region Based on Gerschgorin Disk Theorem

Since the development of renewable power generation, Sub/Super-Synchronous Control Interac-tion (SSCI), has attracted wide attention. Sub/super-synchronous oscillation (SSO) belongs to the category of small signal stability, and its characteristics are closely related to the operation mode and controller parameters in power grid. The operation mode of renewable power system changes frequently, a method to construct controller parameter stability region (PSR) is proposed for online assessment of the matching degree of controller parameters in power grid under current operation mode. Based on Gerschgorin disk theorem (GDT), eigenvalue distribution range of the system state matrix is estimated, thus the feasible value set of the controller parameter is deduced through small signal stability criterion. The stability margin evaluation index is proposed for guiding the prevention and control of SSO. Specifically, the preconditions of the application of the GDT on the PSR construction are discussed, and a construction method of transition matrix is proposed for the PSR construction. Furthermore, to reduce the conservativeness of PSR, an extension method for PSR is given. Finally, the validity of the proposed method is verified by a realistic benchmark. The efficiency of the proposed method is highlighted by comparing with the point-wise eigenvalue calculation of the state matrix.