Global optimization of second-order sliding mode controller parameters using a new sliding surface: An experimental verification to process control system

The chattering effect, robustness and stability are the major issues in a typical Sliding Mode Control (SMC). The selection of sliding manifold parameters are complicated, time-consuming and tedious. The parameter convergence is also a challenging work. Hence, the paper accords a global optimization of Second-Order Sliding Mode Controller (SOSMC) parameters with new sliding surface using the Jaya algorithm for non-linear uncertain process tank systems. The controller (SOSMC) role is to direct the sliding surface and it's first order time derivative to zero in a finite time. The Jaya algorithm uses 'optimal features' by updating the solutions in populations. The effectiveness of proposed strategy is evaluated for five objective functions and compared with Artificial Bee Colony (ABC) based SOSMC, classical SOSMC, typical SMC, Non-dominated Sorting Genetic Algorithm based First-order SMC (NSGA-II FOSMC) and Proportional+Integral+Derivative (PID) controller which is validated through real-time experimentation. The asymptotic stability is guaranteed through direct Lyapunov candidate function. The statistical significance of algorithms has been verified by using Friedman, Dunn, critical time efficiency and p-value tests. The Jaya algorithm shows a better performance over reported methods concerning process speed, settling time, rise time, reaching time, overshoot, response time and parameter convergence as explored from simulation, statistical, and experimental results. Furthermore, the elevated dead-time and oscillatory processes have been presented to show the efficacy of proposed strategy.

Enhancement in Cathodic Redox Reactions of Single-Chambered Microbial Fuel Cells with Castor Oil-Emitted Powder as Cathode Material

Microbial fuel cell (MFC) would be a standalone solution for clean, sustainable energy and rural electrification. It can be used in addition to wastewater treatment for bioelectricity generation. Materials chosen for the membrane and electrodes are of low cost with suitable conducting ions and electrical properties. The prime objective of the present work is to enhance redox reactions by using novel and low-cost cathode catalysts synthesized from waste castor oil. Synthesized graphene has been used as an anode, castor oil-emitted carbon powder serves as a cathode, and clay material acts as a membrane. Three single-chambered MFC modules developed were used in the current study, and continuous readings were recorded. The maximum voltage achieved was 0.36 V for a 100 mL mixture of domestic wastewater and cow dung for an anodic chamber of 200 mL. The maximum power density obtained was 7280 mW/m². In addition, a performance test was evaluated for another MFC with inoculums slurry, and a maximum voltage of 0.78 V and power density of 34.4093 mW/m² with an anodic chamber of 50 mL was reported. The present study’s findings show that such cathode catalysts can be a suitable option for practical applications of microbial fuel cells.

Evolutionary optimization of sliding mode controller for level control system

This paper accords the level control of single-input-single-output (SISO) level control system based on the fusion of sliding mode control (SMC) and evolutionary techniques or bio-inspired techniques. The non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO) are considered as two evolutionary techniques. Here, a comparative analysis of performances of an optimal proportional-integral (PI) controller, proportional-integral-derivative (PID) controller, conventional SMC, NSGA-II based tuned SMC and SMC parameter tuning using MOPSO algorithm has been carried out through MATLAB/SIMULINK. The objective functions, integral absolute error (IAE), integral squared error (ISE) and an integration of weighted objective function aggregated approach of the error performance indices, IAE and ISE are considered. Realistic conditions are used in a plant for testing the robustness of controller. The stability of the controller is successfully obtained which satisfies the Lyapunov stability criteria. Reduction in long settling time with tiny magnitude variations about an equilibrium point is achieved using bio-inspired techniques. The simulation as well as experimental results reveal that SMC parameter tuning based on NSGA-II algorithm gives a better performance as compared to the other design strategies.