The Language of Systems Thinking for Control Systems

Author(s):  
Piero Mella
Kybernetes ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 58-78 ◽  
Author(s):  
Piero Mella ◽  
Patrizia Gazzola

Purpose Accepting the assumption that our intelligence depends on the ability to construct models which may allow us to acquire, update and transmit our knowledge, this paper aims to highlight the role of Systems Thinking in developing the “intelligence” of managers for all types and sizes of organization. Design/methodology/approach Four relevant contributions for improving the “intelligence” of managers will be examined: the ability to understand and model dynamic systems, the structure of Control Systems, the rules of the decision-making process and the identification of systems archetypes. Findings The paper will show that Systems Thinking, through the logic of Control Systems, offers managers a comprehensive representation of the problem-solving and decision-making processes, teaching them how to distinguish problems from symptoms and to acquire a leverage effect. Additionally, Senge’s system archetypes will be presented and new archetypes will be added to Senge’s list. Practical implications The viability of every organization and its effective resilience and survival make it more than ever necessary for managers to adopt Systems Thinking, not only as a technique but also primarily as a discipline for efficient and effective thinking, learning, communication and explanation with regard to the dynamics of the world. Originality/value The message of the paper is that by continually applying the rules and language of Systems Thinking, managers develop the capability to continually adapt their models to the dynamics of the world, increase their learning capacity and better gauge their consequent judgments, decisions and behavior, thereby removing the mental impediments to intelligence (inappropriate mental models, defensive routines, judgmental biases, rules, etc.).


10.14311/522 ◽  
2004 ◽  
Vol 44 (2) ◽  
Author(s):  
D. J. Murray-Smith

Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control. 


1988 ◽  
Vol 104 (3) ◽  
pp. 363-372 ◽  
Author(s):  
Nicholas C. Barrett ◽  
Denis J. Glencross

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