Intelligent proportional integral control of a polar axis solar tracker

Abstract

Weathering and ageing effects often cause parameter changes in solar trackers. Such parameter variations lead to the degradation of the performance of model-based controllers used in solar tracking. This paper presents the design and performance validation of the model-tolerant intelligent proportional integral (iPI) controller, for sustaining the tracking performance of a polar-axis solar tracking system in the presence of model-parameter changes. The paper clarifies the stability and robustness requirements for the iPI controller, and also validates its performance by comparison with a classical PID controller derived using Nichol Zeigler tuning rules. Results show that the iPI controller is both easier to tune, and can better sustain control function in the presence of model parameter variations.

Double-loop PI controller design of the DC-DC boost converter with a proposed approach for calculation of the controller parameters

“…1 proportional-integral/proportional-integral-derivative (PI/PID) control methods are widely used and preferred in most of control applications. PI/PID controller parameters are calculated in literature using heuristic methods such as Ziegler Nichols, particle swarm optimization (PSO), genetic algorithm (GA) and simulated annealing (SA) [2][3][4][5][6][7] or analytic methods such as frequency response, Bode plot and root-locus technique [8][9][10][11][12][13][14] or intelligent methods [15][16][17][18][19] such as neural network (NN) and fuzzy logic.…”

Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

“…• which is inherently robust, since the perturbations are easily taken into account, -easy to implement both from software and hardware viewpoints, has already been successfully applied a number of times, and in many countries. See, e.g., the references in [21], [1] and the references therein, and [2], [5], [13], [14], [17], [18], [28], [29], [30], [35], [38], [40], [41], [42], [43], [45], [47], [48], [51], [53], [55], [56], [57], [62], [66], [68], [69], [70], [71], [73], [74], [75], [76], [78], . .…”