The optimal state of charge (SoC) balancing control for series-connected lithium-ion battery cells is presented in this paper. A modified SoC balancing circuit for two adjacent cells, based on the principle of a bidirectional Cuk converter, is proposed. The optimal SoC balancing problem is established to minimize the SoC differences of cells and the energy loss subject to constraints of the normal SoC operating range, the balancing current, and current of cells. This optimization problem is solved using the sequential quadratic programming algorithm to determine the optimal duties of PWM signals applied to the SoC balancing circuits. An algorithm for the selection of the initial points for the optimal problem-solving process is proposed. It is applied in cases where the cost function has no decreasing part. Experimental tests are conducted for seven series-connected Samsung cells. The optimal SoC balancing control and SoC estimation algorithms are coded in MATLAB and embedded in LabVIEW to control the SoC balancing in real time. The test results show that the differences between the SoCs of cells converges to the desired range using the proposed optimal SoC balancing control strategy.

Background/Objectives: Axial spondyloarthritis (axSpA) includes ankylosing spondylitis (AS) and nonradiographic axial spondyloarthritis (nr-axSpA). Both are managed with biologic therapies; however, there is a lack of evidence for nr-axSpA therapies. The primary objective was to compare persistence to first biologic between AS and nr-axSpA patients in a longitudinal cohort. Secondary objectives were to examine disease activity markers over time and to evaluate predictors for drug discontinuation. Methods: Data were obtained from persons enrolled in the SpondyloArthritisResearch Consortium of Canada registry between 2003 and 2018. Kaplan-Meier curves were constructed from the time of biologic initiation until discontinuation and compared using the log-rank test. Subanalyses were performed according to calendar year and disease activity. Cox proportional hazards models were used to identify factors associated with discontinuation. Results:We identified 385 biologic-naive persons. Overall, the 349 AS participants had longer persistence to their first biologic than the 36 nr-axSpA subjects (p < 0.01). The Bath Ankylosing Spondylitis Disease Activity Index and Bath Ankylosing Spondylitis Functional Index decreased by 2.3 points (95% confidence interval [CI], 1.9-2.7) and 3.2 points (95% CI, 2.6-3.7), respectively, in the first year and were stable thereafter. Adjusting for sex, human leukocyte antigen B27, and smoking status, nr-axSpA patients were more likely to discontinue their biologic than AS patients (hazards ratio, 1.65; 95% CI, 1.03-2.62). Conclusions:In this real-world study, AS patients had longer persistence to their first biologic compared with nr-axSpA, with disease subtype being the most significant predictor of treatment persistence. Future studies should be targeted at assessing long-term clinical outcome of axSpA in the real-world setting.

In this paper, a tracking control approach is developed based on an adaptive reinforcement learning algorithm with a bounded cost function for perturbed nonlinear switched systems, which represent a useful framework for modelling these converters, such as DC–DC converter, multi-level converter, etc. An optimal control method is derived for nominal systems to solve the tracking control problem, which results in solving a Hamilton–Jacobi–Bellman (HJB) equation. It is shown that the optimal controller obtained by solving the HJB equation can stabilize the perturbed nonlinear switched systems. To develop a solution to the translated HJB equation, the proposed neural networks consider the training technique obtaining the minimization of square of Bellman residual error in critic term due to the description of Hamilton function. Theoretical analysis shows that all the closed-loop system signals are uniformly ultimately bounded (UUB) and the proposed controller converges to optimal control law. The simulation results of two situations demonstrate the effectiveness of the proposed controller.

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