Maximum power point tracking (MPPT) control of pressure retarded osmosis (PRO) salinity power plant : development and comparison of different techniques

This paper presents two new methods for the maximum power point tracking (MPPT) control of a pressure retarded osmosis (PRO) salinity power plant, including mass feedback control (MFC) and fuzzy logic control (FLC). First, a brief overview of perturb & observe (P&O) and incremental mass resistance (IMR) control is given as those two methods have already demonstrated their merit in good control performance. Then, two new methods employing variable-step strategy, MFC and FLC, are proposed to address the trade-off relationship between rise-time and oscillation of P&O and IMR. Genetic algorithm (GA) is used for finding the optimum parameters of membership functions of FLC. From the case-study of start-up of the PRO adopting MPPT control, MFC and FLC have shown faster convergence to the target performance without oscillation compared with P&O and IMR. These four MPPT techniques are further evaluated in case-studies of state transitions of the PRO due to operational fluctuations. It is proven that the MPPT using FLC and modified MFC has better performance than the other two methods. Finally, the paper reports a comparison of major characteristics of the four MPPT methods, which could be considered as guidance for selecting a MPPT technique for the PRO in practice

An evaluation of membrane properties and process characteristics of a scaled-up pressure retarded osmosis (PRO) process

YesThis work presents a systematic evaluation of the membrane and process characteristics of a scaled-up pressure retarded osmosis (PRO). In order to meet pre-defined membrane economic viability ( ≥ 5 W/m2), different operating conditions and design parameters are studied with respect to the increase of the process scale, including the initial flow rates of the draw and feed solution, operating pressure, membrane permeability-selectivity, structural parameter, and the efficiency of the high-pressure pump (HP), energy recovery device (ERD) and hydro-turbine (HT). The numerical results indicate that the performance of the scaled-up PRO process is significantly dependent on the dimensionless flow rate. Furthermore, with the increase of the specific membrane scale, the accumulated solute leakage becomes important. The membrane to achieve the optimal performance moves to the low permeability in order to mitigate the reverse solute permeation. Additionally, the counter-current flow scheme is capable to increase the process performance with a higher permeable and less selectable membrane compared to the co-current flow scheme. Finally, the inefficiencies of the process components move the optimal APD occurring at a higher dimensionless flow rate to reduce the energy losses in the pressurization and at a higher specific membrane scale to increase energy generation

Control Of An Underactuated Double-Pendulum Overhead Crane Using Improved Model Reference Command Shaping: Design, Simulation And Experiment

This paper presents a new control scheme based on model reference command shaping (MRCS) for an overhead crane, with double-pendulum mechanism effects. The approach has an advantage in achieving an accurate trolley positioning, with low hook and payload oscillations, under various desired trolley positions and parameter uncertainties, without the requirement for measurement or estimation of system parameters. These are challenging in practice. The previously developed MRCS algorithm is improved in order to reduce its design complexity, as well as to ensure that it can be augmented with a feedback controller so that a concurrent controller tuning can be realised. The combined MRCS and feedback controller is used to achieve both, precise trolley positioning, and low hook and payload oscillations. To evaluate the effectiveness and the robustness of the approach, simulations and experiments using a nonlinear model and a laboratory double-pendulum crane are carried out. Under various desired positions and parameter uncertainties that involve varying the cable lengths (payload hoisting) and the payload mass variations, the superiority of the proposed approach is confirmed by achieving higher hook and payload oscillation reductions when compared with a recently proposed feedback controller. In addition, the desired trolley positions are achieved with smoother responses

Input shaping with an adaptive scheme for swing control of an underactuated tower crane under payload hoisting and mass variations

An underactuated tower crane exhibits a significant payload sway especially under three simultaneous motions involving trolley displacement, jib rotation and payload hoisting. This paper proposes an input shaper with an adaptive scheme for payload swing control of a tower crane under those effects together with varying cable lengths for payload hoisting and various payload masses. The control approach has an advantage in its capability to adapt and update the Zero Vibration Derivative shaper parameters in real-time according to the changes in the system parameters. This is achieved by using a non-linear input–output mapping of the parameters developed using the neural network. To test the effectiveness of the proposed controller, experiments are carried out on a laboratory tower crane under several challenging conditions involving payload lowering and lifting operations, variation in speeds of motion, and using different payload masses up to ± 50% variations from an original mass. Experimental results show that the proposed shaper is robust towards the parameter uncertainties with low overall and residual payload sways under all testing conditions. Its superiority is confirmed by improvements of at least 49% and 76% in the payload lifting operation while 38% and 68% in the payload lowering operation for the overall and residual sways respectively over a robust Extra Insensitive shaper designed using an average operating frequency. In addition, the performance of the proposed controller is not affected by the variations in the payload masses and motion speeds