Smart Inspection Equipment Manufacturer
- Commodity name： Smart Inspection Equipment Manufacturer
- Commodity ID： 1191888242341466112
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What we commonly refer to as conventional control encompasses both control methods based on classical control theory and those based on modern control theory. The defining characteristic of conventional control is its reliance on accurate mathematical models. The primary research approach involves first establishing a mathematical model of the system, then analyzing that model, and finally synthesizing a control law based on the system’s mathematical representation. Conventional control has achieved significant successes throughout history; however, it also faces numerous challenges.
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What we commonly refer to as conventional control encompasses both control methods based on classical control theory and those based on modern control theory. The defining characteristic of conventional control is its reliance on accurate mathematical models. The primary research approach involves first establishing a mathematical model of the system, then analyzing that model, and finally synthesizing a control law based on the system’s mathematical model. Conventional control has achieved significant accomplishments throughout history; however, it also faces numerous challenges:
(1) The complexity, strong nonlinearity, and uncertainty of the system make system identification and modeling challenging;
(2) The task of classical control theory and modern control theory is to design feedback control that ensures the stability of closed-loop systems. However, as control tasks become increasingly complex and challenging, and as we confront such intricate plant characteristics and demanding control objectives, traditional linear system control theory has long since fallen short of meeting these requirements.
(3) Control methods such as qualitative analysis, logical reasoning, and linguistic control face significant challenges in mathematical treatment. Precisely because of these difficulties, new concepts, theories, and methodologies remain to be developed.
With the advancement of control technology and related scientific disciplines, intelligent inspection equipment manufacturing has emerged to address the various challenges inherent in conventional control systems. The core research focus has consistently been on tackling the uncertainties that are difficult to resolve using traditional control theories and methods. To effectively manage the developmental nature, complexity, and inherent uncertainty of the control objects in intelligent inspection equipment manufacturing, an ideal system should possess both learning capability and adaptability. Learning capability refers to the system’s ability to identify, memorize, and learn from information provided by an unknown environment, and to continuously and autonomously improve its performance based on accumulated experience. Adaptability, on the other hand, implies that the intelligent system must exhibit a certain degree of fault tolerance and robustness: when conflicts or errors arise, the intelligent controller should be able to resolve them within a defined range, thereby enabling the system to meet multi-objective, high-standard requirements. Today, intelligent control has entered a new phase; as the scale of control objects expands and process complexity increases, a pluralistic approach to intelligent control has taken shape, while groundbreaking advances have been made in practical applications, leading to an ever-wider range of application domains.
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Address: No. 7, Meijia Road, Nan’an District, Chongqing
Email: fenghai@cqfenghai.com
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Company email：fenghai@cqfenghai.com
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